WO2014065111A1 - Energy management system - Google Patents

Energy management system Download PDF

Info

Publication number
WO2014065111A1
WO2014065111A1 PCT/JP2013/077285 JP2013077285W WO2014065111A1 WO 2014065111 A1 WO2014065111 A1 WO 2014065111A1 JP 2013077285 W JP2013077285 W JP 2013077285W WO 2014065111 A1 WO2014065111 A1 WO 2014065111A1
Authority
WO
WIPO (PCT)
Prior art keywords
factory
production
management system
energy
energy management
Prior art date
Application number
PCT/JP2013/077285
Other languages
French (fr)
Japanese (ja)
Inventor
明 田村
正博 吉岡
Original Assignee
株式会社日立製作所
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 株式会社日立製作所 filed Critical 株式会社日立製作所
Publication of WO2014065111A1 publication Critical patent/WO2014065111A1/en

Links

Images

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00Systems controlled by a computer
    • G05B15/02Systems controlled by a computer electric
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004Generation forecast, e.g. methods or systems for forecasting future energy generation
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381Dispersed generators
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20The dispersed energy generation being of renewable origin
    • H02J2300/22The renewable source being solar energy
    • H02J2300/24The renewable source being solar energy of photovoltaic origin
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/10The network having a local or delimited stationary reach
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
    • H02J7/35Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225Demand response systems, e.g. load shedding, peak shaving
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion systems, e.g. maximum power point trackers
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00Climate change mitigation technologies for sector-wide applications
    • Y02P80/10Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00Climate change mitigation technologies for sector-wide applications
    • Y02P80/20Climate change mitigation technologies for sector-wide applications using renewable energy
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/50Energy storage in industry with an added climate change mitigation effect
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20End-user application control systems
    • Y04S20/222Demand response systems, e.g. load shedding, peak shaving

Definitions

  • the present invention relates to technologies such as an energy management system and a production management system.
  • FEMS Factory Energy Management System
  • FEMS Factory Energy Management System
  • FEMS monitors and records the energy used (in other words, electric power, load, demand, etc.) for each target factory and each production line to save energy.
  • production management system or production planning system
  • production planning system there is a system for creating and managing production plans for products and parts in a factory production line.
  • energy load leveling is achieved by predicting energy load and setting future energy reduction targets based on energy records related to manufacturing and production processes and input information such as future production plans. In this way, it is possible to formulate / plan production plans.
  • the energy consumption unit (required for production of unit quantity) is the value obtained by dividing the energy consumption by the number of production. Using energy such as power consumption).
  • Patent Document 1 JP 2010-26836 A
  • Patent Document 2 JP 2004-151830 A
  • Patent Document 3 JP 2005-92828 A
  • Patent Document 4 Japanese Unexamined Patent Application Publication No. 2005-261021
  • Patent Document 1 energy plan support system describes that a user is supported so that an energy plan that achieves a reduction target of energy intensity can be easily created.
  • the system of Patent Document 1 has an energy usage record and an energy intensity reduction target, uses the energy usage plan and production plan value for the current year as input information, calculates the energy intensity for the current year, By calculating the reduction rate of the previous year and calculating the planned value of monthly energy consumption based on the target value of reduction rate, it may be necessary to create an energy usage plan to achieve the energy reduction target.
  • the system of Patent Document 1 has an energy usage record and an energy intensity reduction target, uses the energy usage plan and production plan value for the current year as input information, calculates the energy intensity for the current year, By calculating the reduction rate of the previous year and calculating the planned value of monthly energy consumption based on the target value of reduction rate, it may be necessary to create an energy usage plan to achieve the energy reduction target.
  • Patent Document 2 energy demand optimization system and production plan creation support system describes that the amount of energy demand for existing equipment is optimized without introducing new equipment.
  • energy consumption per unit production of a product is used as an energy basic unit
  • equipment operating time required for production is used as a time basic unit
  • energy consumption and equipment operating time are predicted
  • an air conditioner non-production equipment
  • Patent Document 3 scheduling system or the like describes that a system capable of creating a schedule that minimizes the amount of energy used after satisfying various production conditions is described.
  • Patent Document 4 (operation planning system or the like) describes that an operation plan for an energy supply system that is optimal for a consumer can be made after satisfying various conditions in the energy supply system.
  • an energy consumption unit is obtained from an electric power usage plan and actual information, and an energy usage plan for achieving an energy reduction target is established.
  • the planned usage plan is monthly, and more detailed energy management and production plan management is not performed on a daily or hourly basis. Therefore, it is insufficient from the viewpoint of more efficient energy management.
  • Patent Document 3 it is described that a schedule including energy demand prediction information is created, but it is not intended to achieve cooperation with a production plan and peak cut in consideration of renewable energy or distributed power sources, It is insufficient in terms of efficiency.
  • Patent Document 4 it is described that an overall multi-purpose operation plan is generated based on energy demand prediction of facilities including factories and buildings. Similarly, cooperation with a production plan and renewable energy are described. It is not intended to achieve peak cut or the like considering a distributed power source, and is insufficient from the viewpoint of efficiency.
  • the main object of the present invention is to increase the accuracy of prediction related to energy demand by first linking with a production management system / production plan, and more efficient energy management for energy management systems such as FEMS. Second, it is possible to realize more efficient energy management for the entire factory by actively utilizing and considering renewable energy and distributed power sources.
  • a typical embodiment of the present invention is an energy management system such as FEMS targeted at a factory (customer) and has the following configuration.
  • the energy management system of this embodiment includes a factory energy management system (FEMS) that manages energy for factories, a production management system (PMS) that manages production plans in factory production facilities, and renewable energy for the factories. Or a power supply system capable of supplying power from a distributed power source.
  • FEMS is a process for coordinating with the production plan planned by PMS, a process for predicting the energy load or demand of the factory, a process for predicting the power that can be supplied by the power supply system, and the production plan information. , Including the amount of supply from the power that can be supplied by prediction, make adjustments including peak cuts or peak shifts to equalize the energy load or demand of the factory by prediction and achieve more efficient energy management.
  • the process of outputting the adjusted production plan information to the PMS is performed.
  • the FEMS uses the PMS as information on the production plan, including information on the power used for each product and each production line, information on the constraints related to the production, and information on the basic unit related to the production.
  • the adjustment process using the acquired information, work in a time zone with a large load on a plurality of production lines using production facilities in a factory, a time zone with a low load before and after that Adjustment including peak cut or peak shift is performed so that the load is generally leveled.
  • the PMS as production plan information, includes information including the date and time and electric power used for each product and each production line, information on constraints related to the production, and each product unit and production related to the production.
  • Data processing including production plans with FEMS for processing to store basic unit information including power consumption, personnel, and time for each line, processing to formulate production plans, and FEMS Processing to transmit / receive and processing to carry out production at the production facility of the factory according to the information of the production plan adjusted by FEMS are performed.
  • the accuracy of prediction related to energy demand is improved by linking with a production management system and a production plan, and more efficient energy management.
  • more efficient energy management for the entire factory can be realized by actively utilizing and considering renewable energy and distributed power sources.
  • the FEMS 1 cooperates with the production plan planned by the PMS 2 and the PMS 2, and the data information including the production plan, the constraint condition, and the basic unit information from the PMS 2. And predicting energy demand in the entire production line (production facility) 21 of the factory 20, and adjusting and optimizing the production plan (in other words, energy usage plan / plan) based on the prediction (in other words, Process to change the configuration of the production plan).
  • the FEMS 1 predicts the energy load of facilities (related equipment other than production equipment) such as lighting and air conditioning in the factory 20 in the above adjustment process, and also supplies power from renewable energy and distributed power sources.
  • the supplyable amount and power generation amount by the storage battery system 5 and the solar power generation system 6 which are systems are predicted.
  • the FEMS 1 predicts the overall energy load or demand of the factory 20 based on these predicted amounts and the amount of power used for each product and production line in the production plan. Then, the FEMS 1 is configured so that the above-mentioned predicted amount can be efficiently combined with the power supply plan from the renewable energy / distributed power source (5, 6) so that efficient energy management of the entire factory 20 can be realized. Perform peak cuts or peak shifts to level the load and adjust and optimize production plans.
  • peak cuts or peak shifts are performed so as to level the energy load during peak hours.
  • the shift of the work time zone in parallel operation of a plurality of production lines in the production plan, allocation of power supply from the storage battery, and the like are performed.
  • the system 10 predicts loads by facilities other than the production equipment (21) of the factory 20, such as lighting and air conditioning, and plans to supply power from storage batteries and solar power generation. Optimize energy throughout the 20th.
  • the system 10 performs production based on the modified production plan, and maximizes power supply from storage batteries, solar power generation, and the like, thereby reducing the amount of commercial grid power used. Thereby, the energy load reduction in the whole factory 20 and the efficiency improvement of energy utilization are implement
  • FIG. 1 shows a configuration of a system (energy management system) 10 of the present embodiment.
  • the entire system 10 includes a factory energy management system (FEMS) 1, a production management system (abbreviated as PMS) 2, a watt-hour meter (meter) 3, an illumination / air conditioning system 4, a storage battery system 5, a solar power generation system 6, And a factory 20 to be managed, and these are connected to each other by communication means.
  • the PMS 2 and each unit (3 to 6) are connected to the FEMS 1 by a communication network or a dedicated line.
  • Each system such as 1 to 5 may be provided inside the factory 20 or may be provided outside.
  • This system 10 provides a function for controlling the peak shift of the power (energy) of the factory 20 in particular by strong cooperation between the FEMS 1 and the PMS 2.
  • the system 10 includes a storage battery system 5 and a solar power generation system 6 as a system capable of supplying energy (electric power) to the factory 20 using a renewable energy / distributed power source.
  • the system 10 uses these (5, 6) energy (electric power) to adjust the production plan.
  • the factory 20 has a configuration including a predetermined production line (in other words, a production facility) 21, and predetermined products / parts are produced using the production line 21 in accordance with a production plan by the production management system 2.
  • a predetermined production line in other words, a production facility
  • predetermined products / parts are produced using the production line 21 in accordance with a production plan by the production management system 2.
  • the FEMS 1 targets the factory 20 having the production line (production facility) 21 as an object (customer), and manages the energy of the entire factory 20 to save energy.
  • the FEMS 1 is configured by a known technique such as a server 11 or a DB (database). Each function (101 to 103, etc.) of the FEMS 1 is realized by executing a program process using the CPU and memory in the server 11.
  • the main functions of the FEMS 1 include a production plan cooperation / adjustment function 101, an energy load monitoring function 102, an energy supply control function 103, and the like.
  • the FEMS 1 includes a function of referencing / acquiring necessary information (such as prediction information described later) from the outside via a network.
  • FEMS1 it is possible to set / view various information on the screen by accessing the server 11 from a terminal such as an administrator (U1).
  • the FEMS 1 stores performance information collected from each system (2 to 5), its own prediction information, and the like in the DB.
  • the FEMS 1 has a function (production plan cooperation / adjustment function 101) for adjusting / optimizing the production plan in cooperation with the production plan planned by the PMS2.
  • This function (101) includes performing processing such as peak cut and peak shift so as to level the energy load of the factory 20.
  • the FEMS 1 has an energy load monitoring function 102 for the PMS 2, the watt-hour meter 3, and the lighting / air conditioning system 4, and predicts / monitors the energy load or demand related to the factory 20.
  • the FEMS 1 collects measurement information from the watt-hour meter 3 to visualize and monitor the energy load of the factory 20.
  • the FEMS 1 grasps the power consumption of facilities such as lighting and air conditioning for the lighting and air conditioning system 4 and performs control according to demand (demand).
  • the FEMS 1 has an energy supply control function 103 for the storage battery system 5 and the photovoltaic power generation system 6, and supplies and controls energy (renewable energy / distributed power source) to the factory 20.
  • the FEMS 1 controls and controls the storage battery system 5 by charging / discharging the storage battery. Electric power is supplied to the factory 20 by discharging from the storage battery.
  • the FEMS 1 predicts and grasps the power generation amount of solar power generation for the solar power generation system 6.
  • the power generated by the solar power generation system 6 is stored (charged) in the storage battery of the storage battery system 5.
  • the production management system (PMS) 2 is also referred to as a production planning system or the like, and creates a production plan for production of products using the production line (production equipment) 21 of the factory 20, and performs production management (execution of production) based on the production plan. Monitoring, production record information, etc.).
  • the PMS 2 can be applied to an existing system.
  • the PMS 2 has a function of producing a production plan corresponding to cooperation with the FEMS 1.
  • the PMS 2 stores and manages data including production plan information, production result information, production constraint information, production basic unit information, and the like in a DB or the like.
  • the FEMS 1 and the PMS 2 have an interface for cooperating with the PMS 2 and the FEMS 1 and a common format, respectively, and can transmit and receive necessary data information.
  • the watt-hour meter (meter) 3 is installed on a distribution board or the like in the factory 20, and measures and collects loads (such as the amount of power used in the production line 21) of the factory 20.
  • the meter 3 may be a smart meter or the like having an information processing function.
  • the lighting / air-conditioning system 4 is a device / system including lighting equipment, air-conditioning equipment, OA equipment, etc., which are related equipment that uses electric power, other than the production line (production equipment) 21 of the factory 20.
  • the illumination / air conditioning system 4 may include a predetermined control system, for example, a system (a publicly known technology) having a function of automatically controlling the state of illumination and air conditioning, a function of predicting loads of illumination and air conditioning, and the like.
  • the lighting / air conditioning system 4 autonomously controls / monitors the operating state / temperature state of lighting / air conditioning in the factory 20.
  • facilities such as lighting and air conditioning are basically handled and controlled independently of the production line 21 of the factory 20.
  • the amount of electric power used in facilities such as lighting and air conditioning is measured and grasped by the meter 3, but may be used if it can be grasped by the lighting and air conditioning system 4 itself.
  • the conditions such as lighting and air-conditioning directly related to the production itself in the production line 21 of the factory 20 for example, conditions for keeping the temperature constant during a predetermined process
  • the production plan of the PMS 2 (such as the amount of power used in the production line) It is managed and reflected in. Therefore, with respect to facilities such as lighting and air conditioning, the FEMS 1 and the lighting and air conditioning system 4 control the portion of the entire power, excluding the amount used as the above-mentioned production conditions, according to demand.
  • the storage battery system 5 includes a storage battery (for example, a lithium ion secondary battery) and its control board (power conditioner).
  • the storage battery system 5 is charged and discharged according to a charging / discharging plan (schedule) that the FEMS 1 plans in accordance with the adjustment of the production plan.
  • the photovoltaic power generation system 6 includes a photovoltaic power generation panel and its control board.
  • the photovoltaic power generation system 6 supplies electric power generated by photovoltaic power generation to the storage battery system 5 or the factory 20.
  • the present system 10 may be similarly controlled in cooperation with the FEMS 1 by using a known system that generates power or stores electricity using the exhaust heat of the factory 20, for example.
  • this Embodiment is a case where it applies to the line production of the factory 20 as an object of energy management, it is applicable not only to this but another production system similarly.
  • this Embodiment is a form which cooperates with PMS2 by making FEMS1 into a subject, it is good also as a form which cooperates with FEMS1 by making PMS2 a subject. That is, the PMS 2 may acquire information related to energy management from the FEMS 1 and adjust the production plan. Further, FEMS1 and PMS2 may be integrated into one system. Other system elements (3 to 6) may be appropriately separated or integrated.
  • FIG. 2 shows a detailed functional block configuration of mainly the FEMS 1 of the system 10 of FIG.
  • the FEMS 1 (its server 11) includes, as processing units, a production plan adjustment / optimization unit 12, a load visualization / collection unit 13, an equipment load prediction / demand control unit 14, a charge / discharge control unit 15, a power generation amount prediction unit 16, It includes an energy (E) demand prediction unit 111, an addition unit 112, a recalculation control unit 113, a target control unit 114, and the like.
  • the FEMS 1 stores performance information d11 and prediction information d12 in the DB.
  • the production plan adjustment / optimization unit 12 adjusts and optimizes the production plan (K1) prepared by the PMS 2 including peak cut and peak shift.
  • the production plan adjustment / optimization unit 12 includes a charge / discharge planning unit 121, a target value setting unit 122, and the like.
  • the charge / discharge planning unit 121 creates a charge / discharge plan for the storage battery system 5.
  • the target value setting unit 122 sets a target value related to peak cut.
  • the load visualization / collection unit 13 collects measurement information from the meter 3 and visualizes the energy load of the factory 20, that is, displays various information such as a load graph on a GUI (graphical user interface) screen. Perform processing to enable operation.
  • GUI graphical user interface
  • the equipment load prediction / demand control unit 14 obtains information from the lighting / air conditioning system 4 and predicts the energy load of the equipment such as lighting / air conditioning, and performs control processing on demand for the lighting / air conditioning system 4. No. 14 predicts the amount of power that is fixedly consumed by facilities such as lighting and air conditioning.
  • the charging / discharging control unit 15 performs a process for controlling the charging / discharging of the storage battery system 5 according to the charging / discharging plan.
  • the power generation amount prediction unit 16 performs processing for predicting the power generation amount of the solar power generation system 6 based on weather information and the like.
  • the energy demand prediction unit 111 predicts the energy demand by using the estimated equipment load by 14 and the predicted power generation by 16.
  • the adding unit 112 adds the amount of power scheduled to be used in the production plan (K1) before adjustment to the energy demand predicted amount by 111.
  • the recalculation control unit 113 controls the recalculation of 111, 112, 12 and the like according to the execution / actual result of production and the production plan (K1).
  • the target control unit 114 performs predetermined control by comparing the target value with the energy demand.
  • PMS2 is composed of a server, a DB, and the like, and implements the functions of PMS2 by executing program processing using a CPU, memory, and the like.
  • the PMS 2 includes a production planning unit 201 as a main function / processing unit.
  • the server can be accessed from a terminal such as an administrator (U2) and various information can be set and viewed on the screen.
  • the PMS 2 stores and manages the constraint condition d21, work item d22, basic unit information d23 and the like related to the production process in the DB. Further, the PMS 2 stores production plan (K1, K2) information that has been planned and adjusted, production result information collected from the production line 21 of the factory 20, and the like in the DB.
  • K1, K2 production plan
  • Constraint condition d21 indicates a constraint condition such as power consumption, personnel, and time required for each product unit and each production line.
  • the basic unit information d23 indicates basic units such as electric power used, personnel, and time required for each product unit and each production line.
  • the work item d22 is information on a work item corresponding to the production plan.
  • the basic unit information (d23) or the like may be managed not by PMS2 but by FEMS1 or the like.
  • the production plan drafting unit 201 creates and drafts a production plan (K1) based on DB information (d21 to d23, etc.). Information on the created production plan K1 is input to FEMS1. At this time, the information may be acquired by accessing the PMS 2 from the FEMS 1 or may be transmitted by accessing the FEMS 1 from the PMS 2.
  • information such as managers (U1, U2) can be browsed on the GUI screen.
  • GUI screen For example, graphs and tables as shown in FIGS. Is possible.
  • Information displayed on the GUI screen includes at least information on production plans (K1, K2) before and after adjustment and information on visualization of the load (actual value) of the factory 20.
  • FIG. 3 shows a concept of the system 10 in which the production plan information of the PMS 2 is input to the FEMS 1 for adjustment in the cooperation between the FEMS 1 and the PMS 2 and energy management linked with the production plan is performed in a cycle.
  • s1 etc. indicate processing steps
  • d1 etc. indicate data information.
  • the PMS 2 transmits the information of the production plan (K1) planned by 201 to the FEMS 1 via the communication network (s1).
  • the information of the production plan (K1) before adjustment or the information transmitted along with this information includes the amount of power used for each product to be produced and for each production line 21 and information on constraint conditions related to the production plan (for example, production line Including the maximum amount of electricity, personnel, and delivery date).
  • the FEMS 1 acquires the production plan (K1) from the PMS2.
  • FEMS1 performs equipment load prediction by 14 and power generation prediction by 16 on a regular basis, for example, every morning, based on performance information and weather information (s2). Predict the load of equipment such as lighting and air conditioning based on the results information, and also predict the amount of photovoltaic power generation based on weather information. Then, the E demand prediction unit 111 predicts the energy demand based on the predicted amounts.
  • d1 shows an example of graph data of the predicted amount of energy demand, which is data obtained by subtracting the predicted power generation amount from the estimated equipment load amount of s2.
  • the FEMS 1 adds the amount of power used for each production line 21 in the production plan (K1) received from the PMS 2 to the energy demand predicted amount (d1) of s2 (s3).
  • d2 is an example of graph data of the predicted energy demand after the addition.
  • the FEMS 1 (production plan adjustment / optimization unit 12) performs load leveling processing including peak cut and peak shift on the data d2 of s3 (s4).
  • a peak cut / peak shift process the production plan in the time zone where the load is at a peak (production process of the production line) is shifted to the previous and next time zones to lower the peak value.
  • Adjust and optimize (schedule).
  • the charge / discharge planning unit 121 sets a charge / discharge plan for the storage battery of the storage battery system 5.
  • the target value setting unit 122 sets a target value X to be the target power as shown in the data d3 after the load leveling.
  • the plan is adjusted so that the peak value of the load is as small as possible below the target value X.
  • the above charge / discharge plan is adjusted so that power that exceeds the target value X is supplied from the storage battery.
  • the above target value X may be set as an initial value by a person such as an administrator, or may be set automatically by FEMS1 (target value setting unit 122) as appropriate.
  • the target value X may be set and controlled variably according to demand.
  • the PMS 2 executes and controls the production in the production line 21 of the factory 20 in accordance with the data d3 of the production plan (K2) after the adjustment of s3 (s5), and records production result information and the like.
  • the FEMS 1 recalculation control unit 113 performs predetermined timing, for example, every hour. Then, a recalculation process based on the correction of the prediction / plan is started (s6). In other words, according to the input (s1) of the new production plan (K1), the adjustment / optimization cycle (s2 to s5) is similarly executed.
  • the FEMS 1 uses the target control unit 114 to determine whether the actual demand value exceeds the target value X of d3 (s7), and detects the excess (demand value> X).
  • a request to forcibly stop the production line 21 is issued / transmitted to the PMS 2 or the factory 20 (s8).
  • a predetermined message or the like may be output and reported to an administrator or the like.
  • FIGS. 5A and 5B show graphs before and after load leveling by PC / PS in the energy demand prediction (simulation) of FEMS1 (111).
  • lines # 1 to # 5 there are a plurality of lines # 1 to # 5 that can be operated in parallel.
  • the operations (processes) on the line include, for example, a setup / preparation unit, a manufacturing unit, and a cleaning unit, as shown in the figure.
  • one work (401) on line # 3 is setup / preparation from 13:00 to 13:30, manufacturing from 13:30 to 15:30, and cleaning from 15:30 to 16:00.
  • predetermined power is used.
  • line 402 has work 402 (manufacturing from 11:30 to 16:00).
  • the production of multiple lines overlaps in a specific time zone, such as around 13:00 to 15:00, and the energy load is high and concentrated. ing.
  • the operations 401 and 402 in FIG. 4A are moved to the preceding and following time zones like the operations 411 and 412 in FIG. 4B by the PC / PS in the production plan adjustment / optimization process (12, s6). Shifted. In particular, this is a case where the planned work (401, 402) of lines # 3 and # 5 is shifted to a time zone (11:00 to 12:00) where the load is relatively low before the time zone when the load is concentrated. . As a result, the load is alleviated and leveled over time and the entire production line 21.
  • FIG. 5A the horizontal axis indicates time [h], and the vertical axis indicates the electric energy [kWh] for each of the lines # 1 to # 5.
  • a line 501 indicates an energy demand prediction.
  • FIG. 5B shows the state after PC ⁇ PS. In the energy demand prediction, the unevenness is large at 501 of (a), but is flat at 502 of (b), and the peak value is lowered from about 500 to about 350.
  • FIG. 6 shows an example of data information in an application example of planning a production plan by the PMS 2 (201 described above).
  • An example of a product produced in the production line 21 of the factory 20 is applied to a UPS (uninterruptible power supply), and a case of application to a test line is shown as an example of a production process.
  • A1 is a kind of basic unit information (d23) managed by the PMS2, and indicates a test basic unit for each product.
  • A2 is work item information (d22).
  • A3 is a test process constraint condition which is a kind of the constraint condition (d21).
  • product-specific test basic unit A1 indicates the area, test time, personnel, and maximum power consumption of the test area (corresponding to each production line) required for each product.
  • A1 has (a1) UPS capacity, (a2) test area, (a3) test time, (a4) number of testers, and (a5) maximum power as management items.
  • Work item A2 indicates the number of tests and the test period (time limit for completing the test) for each product item.
  • A2 has (a6) project, (a7) number of units, and (a8) test period as management items.
  • the information on the item a6 includes information such as each company and specification (UPS capacity).
  • the test process constraint condition A3 is a constraint condition that defines an allowable test area, test personnel, a maximum power upper limit value, and the like.
  • A3 has (a9) constraint conditions and (a10) constraint values, which are the values, as management items.
  • Each constraint is defined in each record.
  • the allowable test area is up to 770 m 2
  • the number of testers is up to 5
  • the power upper limit is 2000 kVA.
  • 7A4 shows an example of information on the production plan (K1) created based on A1 to A3 in FIG.
  • the production plan A4 is made by considering the test process restriction condition A3 for the test unit A1 for each product and the work item A2.
  • A4 has, for example, (a11) test date, (a12) test area to (a16) test area, and (a17) maximum power as management items.
  • the five test areas a12 to a16 correspond to the five production lines # 1 to # 5 described above. 7 to 4 can be converted into a table as shown in FIG.
  • the energy load amount of the factory 20 can be calculated from the above A1 to A4, and the energy demand amount can be predicted by simulation calculation as shown in FIG.
  • FIG. 8 shows an example of prediction of energy demand / load in FEMS1.
  • FEMS1 E demand prediction unit 111 performs load prediction per unit time (14) and photovoltaic power generation amount prediction (16) of equipment (lighting, air conditioning, etc.) in the factory 20 from the equipment load prediction amount.
  • An example of calculating a substantial energy load / demand by subtracting the power generation prediction amount will be shown.
  • B1 in FIG. 8 indicates prediction input information used for prediction, and is stored in the DB.
  • B1 can use past performance information (eg, obtainable from 3 or 4), weather information (eg, obtainable from an external weather information provider), work calendar (eg, obtainable from the factory 20 or PMS2), and the like.
  • B2 is a graph of the estimated equipment load based on B1. The horizontal axis represents time, and the vertical axis represents the load amount (power amount).
  • the FEMS 1 (111, 14) predicts an energy load per unit time (mainly a load of facilities such as lighting and air conditioning) based on the predicted input information B1, and stores the result B2 in the DB.
  • B3 indicates photovoltaic power generation prediction information used for prediction, and is stored in the DB.
  • temperature prediction for example, temperature prediction, solar radiation amount prediction (for example, obtainable from an external weather information provider), past results, and the like can be used.
  • the temperature prediction and the solar radiation amount prediction are prediction information such as the temperature and the solar radiation amount per unit time, and the past performance is the past performance information.
  • B4 is a graph of the predicted amount of photovoltaic power generation based on B3.
  • the horizontal axis represents time, and the vertical axis represents the amount of power generation.
  • the FEMS 1 (111, 16) predicts the amount of photovoltaic power generation per unit time based on the photovoltaic power generation prediction information B3, and stores the resulting B4 in the DB.
  • B5 in FIG. 9 is a graph of the predicted energy demand obtained by subtracting B4 from B2 in FIG. 8, and is a predicted equipment load per unit time (that is, a predicted demand), and data d1 in FIG. Corresponding to The horizontal axis shows time, and the vertical axis shows demand.
  • the lower part 901 corresponds to the part obtained by subtracting B4 from B2, and the upper part 902 corresponds to the part B4.
  • FEMS1 (111) subtracts B4 from B2 to create B5 and stores it in DB.
  • FIG. 10 shows an example of obtaining the factory total load amount (C3) by adding the power amount (C2 ⁇ A4) of the production plan (K1) to the energy demand prediction amount (C1) in FEMS1.
  • C1 corresponds to the energy demand (B5, d1) predicted and calculated by the FEMS 1 in FIG.
  • the portion 1001 is the same as the portion 901 in FIG. C1 corresponds to the predicted load amount of equipment (lighting, air conditioning, etc.) in the entire factory 20.
  • C2 corresponds to the data information (A4) of the production plan (K1) planned by the PMS 2 in FIG. 7 and the like, the horizontal axis indicates time, and the vertical axis indicates the power consumption for each production line 21.
  • the adder 112 adds these (C1, C2).
  • FIG. 11 shows an example before and after load leveling (PC / PS) in the factory total load amount (C3) after the addition in FEMS1.
  • C3 in FIG. 11 is before the peak shift
  • C4 in FIG. 11 is after the peak shift.
  • the portion of 1001 is the same amount.
  • the peak value decreases from over 6000 to less than 6000.
  • the load is leveled by shifting the production plan to the preceding and following time zones for each production line 21 around the peak time zone where the load is highest.
  • FIG. 12 is a plan for reflecting and charging / discharging plan information (D3) based on the storage battery information (D2) with respect to the entire factory load (C4) after the load leveling in FIG. An example in which a load is set is shown. D4 corresponds to the entire factory load in the adjusted production plan (K2).
  • the storage battery information of D2 can be obtained by using, for example, information held by a control unit (power conditioner) in the storage battery system 5 and stored in the DB.
  • D2 includes information such as the capacity of the storage battery, the device state, the dischargeable power, and the dischargeable time.
  • D2 includes information such as storage battery capacity and dischargeable power that can be acquired from the storage battery system 5 itself, dischargeable time that can be calculated on the FEMS1 side, and information that is defined as a constraint on the FEMS1 side.
  • the charge / discharge plan information of D3 is information including a schedule of discharge (supply) from the storage battery per unit time for the factory 20 (production line 21) based on C4 and D2.
  • D3 includes information such as target power, storage battery capacity transition, single-time charge / discharge capacity, and charging for power failure.
  • a target reduction value is set as the target power or target load, as indicated by the Y line in D4. This corresponds to the setting of the target value (X) in FIG.
  • the charge / discharge amount per unit time is determined according to the target.
  • the D4 has a 1201 portion that is equal to or smaller than the target Y and a 1202 portion that is equal to or larger than the target Y. About 1202 part, it covers by the discharge from the storage battery system 5 as a plan. In other words, a plan is made to cover the discharge within the range of the storage amount of the storage battery considering the amount of photovoltaic power generation.
  • the FEMS 1 uses the equipment load prediction / demand control unit 14 to perform demand monitoring for the lighting / air conditioning system 4 (equipment).
  • the FEMS 1 can request the production line 21 to pause the production as described above (114).
  • the lighting / air conditioning system 4 can be requested to reduce or stop the use of power.
  • the load of the whole factory 20 can be reduced by the said plan and control.
  • the energy demand can be predicted with higher accuracy than before by predicting the energy demand of the factory 20 in accordance with the production plan information by cooperation between the FEMS 1 and the PMS 2. To do. Based on the prediction, the energy load can be leveled by shifting the operation of the production line 21 in the production plan, and an efficient production plan and power usage plan are possible. Moreover, efficient production is possible by the charge / discharge plan including the load reduction target utilizing the renewable energy / distributed power source (5, 6). Moreover, efficient production is possible, including load reduction by demand control of equipment (4) such as lighting and air conditioning. As a result, it is possible to realize energy saving by more efficient energy management of the entire factory 20 than before.
  • the energy demand prediction accuracy is not high.
  • the prediction accuracy is increased by cooperation as described above, and the efficiency of energy management is realized.
  • SYMBOLS 1 Factory energy management system (FEMS), 2 ... Production management system (PMS), 3 ... Electricity meter (meter), 4 ... Lighting / air-conditioning system, 5 ... Storage battery system, 6 ... Solar power generation system, 10 ... book System (energy management system), 11 ... server, 20 ... factory, 21 ... production line (production equipment).
  • FEMS Factory energy management system
  • PMS Production management system
  • PMS Production management system
  • Electricity meter meter
  • Lighting / air-conditioning system 5
  • Storage battery system 6
  • Solar power generation system 10 ... book System (energy management system), 11 ... server, 20 ... factory, 21 ... production line (production equipment).

Abstract

Provided is a technology with which energy management and the like for an entire factory can be achieved more efficiently in an energy management system such as a factory energy management system (FEMS). This energy management system has, for example, a FEMS (1) that performs energy management for a factory (20), a production management system (PMS) (2) that designs a production plan for the factory (20), and a storage battery system (5) and a solar light power generation system (6) capable of supplying electrical power to the factory (20). In collaboration with the production plan from the PMS (2), the FEMS (1) performs a process whereby: the energy load for the factory (20) is predicted, and the amount of power that can be supplied from the storage battery system (5) and the like is predicted; an adjustment that includes performing a peak cut or a peak shift with respect to the production plan information is performed so as to achieve more efficient energy management by standardizing the predicted factory load, which includes the amount of supplied power from the predicted amount of power that can be supplied; and information about the adjusted production plan is output to the PMS (2).

Description

エネルギー管理システムEnergy management system
 本発明は、エネルギー管理システム、生産管理システムなどの技術に関する。 The present invention relates to technologies such as an energy management system and a production management system.
 エネルギー管理システムとして、工場を対象(需要家)としてエネルギー管理を行う工場エネルギー管理システム(FEMS:Factory Energy Management System)などがある。FEMSでは、対象となる工場ごと、生産ラインごとに、使用するエネルギー(言い換えると電力、負荷、需要など)を監視・記録し、省エネなどを図る。 As an energy management system, there is a factory energy management system (FEMS: Factory Energy Management System) that performs energy management for a factory (customer). FEMS monitors and records the energy used (in other words, electric power, load, demand, etc.) for each target factory and each production line to save energy.
 また、生産管理システム(ないし生産計画システム)として、工場の生産ラインにおける製品・部品などの生産計画を作成・管理するシステムなどがある。 Also, as a production management system (or production planning system), there is a system for creating and managing production plans for products and parts in a factory production line.
 近年、情報通信技術を採り入れたスマートグリッドやマイクログリッドの研究開発が盛んである。これまで低炭素化と経済的電力運用実現を目的とした実証型の技術開発が主流である。しかしながら、2011年以降の電力不足やそれに伴う電気料金の値上げにより、あらゆる分野において節電が求められており、特に電力消費の多い製造業などの業種にとっては大きな負担となっている。このため、再生可能エネルギーや分散型電源の活用によるピークシフト(ないしピークカット)や負荷の低減などが注目を集めている。その他、生産工程におけるエネルギーの効率的な管理が従来以上に求められている。 In recent years, research and development of smart grids and microgrids that incorporate information and communication technologies are thriving. Until now, proof-type technology development aimed at realizing low-carbon and economical power operation has been the mainstream. However, due to the shortage of electricity since 2011 and the accompanying increase in electricity charges, power saving is required in all fields, which is a heavy burden especially for industries such as the manufacturing industry where power consumption is high. For this reason, attention has been focused on peak shift (or peak cut) and load reduction by utilizing renewable energy and distributed power sources. In addition, more efficient energy management in the production process is required than ever before.
 例えば、製造・生産工程に関わるエネルギーの実績や、今後の生産計画などの入力情報をもとに、エネルギー負荷を予測し、今後のエネルギーの削減目標を設定する等、エネルギー負荷の平準化を図るように生産計画を策定・立案することが考えられる。 For example, energy load leveling is achieved by predicting energy load and setting future energy reduction targets based on energy records related to manufacturing and production processes and input information such as future production plans. In this way, it is possible to formulate / plan production plans.
 上記のように生産計画の段階から生産工程で消費するエネルギー負荷を把握するための手段・方法としては、消費エネルギーを生産量数で除算した値であるエネルギー原単位(単位量の生産に必要な消費電力などのエネルギー)を用いるものが挙げられる。 As described above, as a means and method for grasping the energy load consumed in the production process from the stage of production planning, the energy consumption unit (required for production of unit quantity) is the value obtained by dividing the energy consumption by the number of production. Using energy such as power consumption).
 上記エネルギー管理などに関する先行技術例として、特開2010-26836号公報(特許文献1)、特開2004-151830号公報(特許文献2)、特開2005-92827号公報(特許文献3)、特開2005-261021号公報(特許文献4)などがある。 As prior art examples relating to the energy management and the like, JP 2010-26836 A (Patent Document 1), JP 2004-151830 A (Patent Document 2), JP 2005-92828 A (Patent Document 3), Japanese Unexamined Patent Application Publication No. 2005-261021 (Patent Document 4).
 特許文献1(エネルギ計画支援システム)では、エネルギー原単位の低減目標を達成するエネルギー計画が容易に作成できるように利用者を支援する旨が記載されている。特許文献1のシステムでは、エネルギーの使用実績、及びエネルギー原単位低減目標を持ち、当年度のエネルギー使用量計画と生産量計画値を入力情報とし、当年度のエネルギー原単位を算出すると共に、対前年度の低減率を演算し、低減率目標値を基に、月ごとのエネルギー使用量の計画値を算出することで、エネルギーの削減目標を達成するための、エネルギー使用計画を作成する旨が記載されている。 Patent Document 1 (energy plan support system) describes that a user is supported so that an energy plan that achieves a reduction target of energy intensity can be easily created. The system of Patent Document 1 has an energy usage record and an energy intensity reduction target, uses the energy usage plan and production plan value for the current year as input information, calculates the energy intensity for the current year, By calculating the reduction rate of the previous year and calculating the planned value of monthly energy consumption based on the target value of reduction rate, it may be necessary to create an energy usage plan to achieve the energy reduction target. Are listed.
 特許文献2(エネルギー需要最適化システム及び生産計画作成支援システム)では、新たな設備機器を導入することなく、既存の設備の需要エネルギー量の最適化を図る旨が記載されている。特許文献2では、製品の単位量生産あたりの消費エネルギーをエネルギー原単位とし、生産に必要な設備稼働時間を時間原単位として、消費エネルギーと設備稼働時間を予測し、空調機(非生産設備)の消費エネルギーと併せて単位時間における消費エネルギー量の最大値と最小値の差が最小となるようにすることで負荷の平準化を図る旨が記載されている。 Patent Document 2 (energy demand optimization system and production plan creation support system) describes that the amount of energy demand for existing equipment is optimized without introducing new equipment. In Patent Document 2, energy consumption per unit production of a product is used as an energy basic unit, equipment operating time required for production is used as a time basic unit, energy consumption and equipment operating time are predicted, and an air conditioner (non-production equipment) It is described that the load is leveled by minimizing the difference between the maximum value and the minimum value of the energy consumption amount per unit time together with the energy consumption.
 特許文献3(スケジューリングシステム等)では、生産の諸条件を満たした上でエネルギー使用量を最小にしたスケジュールを作成できるシステムを提供する旨が記載されている。 Patent Document 3 (scheduling system or the like) describes that a system capable of creating a schedule that minimizes the amount of energy used after satisfying various production conditions is described.
 特許文献4(運用計画システム等)では、エネルギー供給システムにおける諸条件を満たした上で、需要家にとって最適なエネルギー供給システムの運用計画を立案することができる旨が記載されている。 Patent Document 4 (operation planning system or the like) describes that an operation plan for an energy supply system that is optimal for a consumer can be made after satisfying various conditions in the energy supply system.
 なお他の先行技術例として、工場ないしその建物における照明・空調などの建築設備における使用エネルギーないし電力量を制御する機能や予測する機能などを備えるシステム、例えば照明制御システムや空調制御システムなどは既に存在する。 As other prior art examples, there are already systems having a function for controlling or predicting the energy or electric energy used in building facilities such as lighting and air conditioning in factories or their buildings, such as lighting control systems and air conditioning control systems. Exists.
特開2010-26836号公報JP 2010-26836 A 特開2004-151830号公報JP 2004-151830 A 特開2005-92827号公報JP 2005-92827 A 特開2005-261021号公報Japanese Patent Laid-Open No. 2005-261021
 前記特許文献1では、電力使用計画及び実績情報からエネルギー原単位を取得し、エネルギー削減目標を達成するためのエネルギー使用計画の立案を行っている。しかし、立案される使用計画は月単位であり、1日単位や時単位でのより細かなエネルギー管理や生産計画の管理は行っていない。そのため、より効率的なエネルギー管理の観点では不十分である。 In the above-mentioned Patent Document 1, an energy consumption unit is obtained from an electric power usage plan and actual information, and an energy usage plan for achieving an energy reduction target is established. However, the planned usage plan is monthly, and more detailed energy management and production plan management is not performed on a daily or hourly basis. Therefore, it is insufficient from the viewpoint of more efficient energy management.
 前記特許文献2では、生産設備に関わる負荷、及び空調(非生産設備)に関わる負荷を時間単位で予測し、負荷の平準化を図っている。しかし、再生可能エネルギーや分散型電源の設置、及びそれらとの連携を考慮しているものではない。そのため、エネルギー負荷の削減の観点からは限界がある。 In Patent Document 2, loads related to production equipment and loads related to air conditioning (non-production equipment) are predicted in units of time, and the load is leveled. However, it does not take into account the installation of renewable energy and distributed power sources, and coordination with them. Therefore, there is a limit from the viewpoint of reducing energy load.
 前記特許文献3では、エネルギー需要予測情報を含むスケジュールを作成する旨が記載されているが、生産計画との連携、及び再生可能エネルギーや分散型電源を考慮したピークカット等を図るものではなく、効率などの観点で不十分である。 In Patent Document 3, it is described that a schedule including energy demand prediction information is created, but it is not intended to achieve cooperation with a production plan and peak cut in consideration of renewable energy or distributed power sources, It is insufficient in terms of efficiency.
 前記特許文献4では、工場・ビルを含む施設のエネルギー需要予測に基づき、全体的な多目的運用計画案を生成する旨が記載されているが、同様に、生産計画との連携、及び再生可能エネルギーや分散型電源を考慮したピークカット等を図るものではなく、効率などの観点で不十分である。 In Patent Document 4, it is described that an overall multi-purpose operation plan is generated based on energy demand prediction of facilities including factories and buildings. Similarly, cooperation with a production plan and renewable energy are described. It is not intended to achieve peak cut or the like considering a distributed power source, and is insufficient from the viewpoint of efficiency.
 従来のFEMS等のエネルギー管理システムは、生産管理システムとの連携はしていないので、エネルギー需要に関する予測の精度は高くないという課題があった。また従来のFEMS等は、再生可能エネルギー・分散型電源の利用を考慮していないので、工場全体のエネルギー管理に係わる効率などの観点で課題があった。 Since conventional energy management systems such as FEMS are not linked to production management systems, there is a problem that the accuracy of prediction regarding energy demand is not high. Further, since conventional FEMS and the like do not consider the use of renewable energy / distributed power source, there is a problem in terms of efficiency related to energy management of the entire factory.
 以上を鑑み、本発明の主な目的は、FEMS等のエネルギー管理システムに関して、第1に、生産管理システム・生産計画との連携により、エネルギー需要に関する予測の精度を高め、より効率的なエネルギー管理などを実現できること、第2に、再生可能エネルギー・分散型電源の積極的な活用及びその考慮などにより、工場全体のより効率的なエネルギー管理などを実現できることである。 In view of the above, the main object of the present invention is to increase the accuracy of prediction related to energy demand by first linking with a production management system / production plan, and more efficient energy management for energy management systems such as FEMS. Second, it is possible to realize more efficient energy management for the entire factory by actively utilizing and considering renewable energy and distributed power sources.
 上記目的を達成するため、本発明のうち代表的な形態は、工場を対象(需要家)とするFEMS等のエネルギー管理システム等であって、以下に示す構成を有することを特徴とする。 In order to achieve the above object, a typical embodiment of the present invention is an energy management system such as FEMS targeted at a factory (customer) and has the following configuration.
 本形態のエネルギー管理システムは、工場を対象としてエネルギー管理を行う工場エネルギー管理システム(FEMS)と、工場の生産設備における生産計画を管理する生産管理システム(PMS)と、工場に対して再生可能エネルギーまたは分散型電源による電力を供給可能な電力供給システムとを有する。FEMSは、PMSにより立案される生産計画に連携する処理と、工場のエネルギー負荷ないし需要量を予測する処理と、電力供給システムによる供給可能な電力を予測する処理と、生産計画の情報に対して、予測による供給可能な電力からの供給量を含めて、予測による工場のエネルギー負荷ないし需要量を平準化してより効率的なエネルギー管理となるようにピークカットまたはピークシフトを含む調整を行い、当該調整後の生産計画の情報をPMSに対して出力する処理とを行う。 The energy management system of this embodiment includes a factory energy management system (FEMS) that manages energy for factories, a production management system (PMS) that manages production plans in factory production facilities, and renewable energy for the factories. Or a power supply system capable of supplying power from a distributed power source. FEMS is a process for coordinating with the production plan planned by PMS, a process for predicting the energy load or demand of the factory, a process for predicting the power that can be supplied by the power supply system, and the production plan information. , Including the amount of supply from the power that can be supplied by prediction, make adjustments including peak cuts or peak shifts to equalize the energy load or demand of the factory by prediction and achieve more efficient energy management. The process of outputting the adjusted production plan information to the PMS is performed.
 本エネルギー管理システムでは、FEMSは、PMSから、生産計画の情報として、製品ごと及び生産ラインごとの使用電力を含む情報と、当該生産に係わる制約条件の情報と、当該生産に係わる原単位の情報とを取得する処理と、前記調整の処理として、上記取得した情報を用いて、工場の生産設備を用いた複数の生産ラインにおける負荷の大きい時間帯の作業を、その前後の負荷の小さい時間帯にシフトして全体的に負荷を平準化するようにピークカットまたはピークシフトを含む調整を行う。 In this energy management system, the FEMS uses the PMS as information on the production plan, including information on the power used for each product and each production line, information on the constraints related to the production, and information on the basic unit related to the production. And the adjustment process, using the acquired information, work in a time zone with a large load on a plurality of production lines using production facilities in a factory, a time zone with a low load before and after that Adjustment including peak cut or peak shift is performed so that the load is generally leveled.
 本エネルギー管理システムでは、PMSは、生産計画の情報として、製品ごと及び生産ラインごとの日時及び使用電力を含む情報と、当該生産に係わる制約条件の情報と、当該生産に係わる製品単位ごと及び生産ラインごとの使用電力、人員、及び時間を含む原単位の情報とを記憶する処理と、生産計画を立案する処理と、FEMSとの連携のため、FEMSとの間で生産計画を含むデータ情報を送受信する処理と、FEMSで調整された生産計画の情報に従い工場の生産設備での生産を実施する処理とを行う。 In this energy management system, the PMS, as production plan information, includes information including the date and time and electric power used for each product and each production line, information on constraints related to the production, and each product unit and production related to the production. Data processing including production plans with FEMS for processing to store basic unit information including power consumption, personnel, and time for each line, processing to formulate production plans, and FEMS Processing to transmit / receive and processing to carry out production at the production facility of the factory according to the information of the production plan adjusted by FEMS are performed.
 本発明のうち代表的な形態によれば、FEMS等のエネルギー管理システムに関して、第1に、生産管理システム・生産計画との連携により、エネルギー需要に関する予測の精度を高め、より効率的なエネルギー管理などを実現でき、第2に、再生可能エネルギー・分散型電源の積極的な活用及びその考慮などにより、工場全体のより効率的なエネルギー管理などを実現できる。 According to a typical embodiment of the present invention, first, with respect to an energy management system such as FEMS, the accuracy of prediction related to energy demand is improved by linking with a production management system and a production plan, and more efficient energy management. Secondly, more efficient energy management for the entire factory can be realized by actively utilizing and considering renewable energy and distributed power sources.
本発明の一実施の形態のエネルギー管理システムの全体の構成を示す図である。It is a figure showing the whole composition of the energy management system of one embodiment of the present invention. 本実施の形態のエネルギー管理システムの機能ブロック構成を示す図である。It is a figure which shows the functional block structure of the energy management system of this Embodiment. 本実施の形態のシステムで、FEMSと生産計画との連携・調整の概念及び処理概要を示す図である。It is a figure which shows the concept and process outline | summary of a cooperation and adjustment with FEMS and a production plan in the system of this Embodiment. 本実施の形態のシステムで、生産計画(生産ライン)におけるピークシフトによる負荷の平準化の概念を示す図である。It is a figure which shows the concept of the leveling of the load by the peak shift in a production plan (production line) in the system of this Embodiment. 本実施の形態のシステムで、FEMSのエネルギー需要予測におけるピークシフトによる負荷の平準化の概念を示す図である。It is a figure which shows the concept of the leveling of the load by the peak shift in the energy demand prediction of FEMS in the system of this Embodiment. 本実施の形態のシステムで、生産管理システムによる生産計画の立案の適用例におけるデータ情報例を示す図である。It is a figure which shows the example of data information in the example of application of the production plan drafting by a production management system with the system of this Embodiment. 本実施の形態のシステムで、生産管理システムによる生産計画の立案の適用例における生産計画情報例を示す図である。It is a figure which shows the example of production plan information in the example of application of planning of the production plan by a production management system with the system of this Embodiment. 本実施の形態のシステムで、FEMSでのエネルギー需要予測のための個別要素の予測例を示す図である。It is a figure which shows the example of a prediction of the individual element for the energy demand prediction in FEMS in the system of this Embodiment. 本実施の形態のシステムで、FEMSでのエネルギー需要予測の例を示す図である。It is a figure which shows the example of the energy demand prediction in FEMS in the system of this Embodiment. 本実施の形態のシステムで、FEMSでのエネルギー需要予測量に生産計画の電力量を加算して工場全体負荷量を得る例を示す図である。It is a figure which shows the example which adds the electric energy of a production plan to the energy demand prediction amount in FEMS, and obtains the whole factory load amount with the system of this Embodiment. 本実施の形態のシステムで、FEMSでの加算後の工場全体負荷量における負荷平準化の前後の例を示す図である。In the system of this Embodiment, it is a figure which shows the example before and after the load leveling in the factory whole load amount after the addition by FEMS. 本実施の形態のシステムで、FEMSでの工場全体負荷量に蓄電池の充放電計画及びエネルギー負荷の目標値を設定した例を示す図である。In the system of this Embodiment, it is a figure which shows the example which set the charging / discharging plan of the storage battery, and the target value of energy load to the factory whole load amount in FEMS.
 以下、図面に基づき、本発明の一実施の形態(エネルギー管理システム)を詳細に説明する。なお実施の形態を説明するための全図において同一部には原則として同一符号を付しその繰り返しの説明は省略する。 Hereinafter, an embodiment (energy management system) of the present invention will be described in detail with reference to the drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment, and the repetitive description thereof will be omitted.
 <概要等>
 本実施の形態のエネルギー管理システム10(図1等に示す)では、FEMS1は、PMS2及びPMS2が立案する生産計画と連携し、PMS2から生産計画、制約条件、及び原単位情報などを含むデータ情報を取得し、工場20の生産ライン(生産設備)21の全体におけるエネルギー需要に関する予測を行い、当該予測に基づき、生産計画(言い換えるとエネルギー使用計画・予定)を調整・最適化する処理(言い換えると生産計画を構成変更する処理)を行う。
<Summary>
In the energy management system 10 (shown in FIG. 1 and the like) of the present embodiment, the FEMS 1 cooperates with the production plan planned by the PMS 2 and the PMS 2, and the data information including the production plan, the constraint condition, and the basic unit information from the PMS 2. And predicting energy demand in the entire production line (production facility) 21 of the factory 20, and adjusting and optimizing the production plan (in other words, energy usage plan / plan) based on the prediction (in other words, Process to change the configuration of the production plan).
 本システム10では、FEMS1は、上記調整の処理では、工場20の照明・空調などの設備(生産設備以外の関連設備)のエネルギー負荷を予測し、また、再生可能エネルギー・分散型電源による電力供給システムである蓄電池システム5や太陽光発電システム6による供給可能量・発電量を予測する。そしてFEMS1は、これら予測量と、生産計画の製品及び生産ラインごとの使用電力量とをもとに、工場20の全体のエネルギー負荷ないし需要量を予測する。そしてFEMS1は、上記予測量について、再生可能エネルギー・分散型電源(5,6)からの電力供給の計画と併せて、工場20全体の効率的なエネルギー管理を実現できるように、工場20全体の負荷を平準化するピークカットないしピークシフトを行って、生産計画を調整・最適化する。 In this system 10, the FEMS 1 predicts the energy load of facilities (related equipment other than production equipment) such as lighting and air conditioning in the factory 20 in the above adjustment process, and also supplies power from renewable energy and distributed power sources. The supplyable amount and power generation amount by the storage battery system 5 and the solar power generation system 6 which are systems are predicted. The FEMS 1 predicts the overall energy load or demand of the factory 20 based on these predicted amounts and the amount of power used for each product and production line in the production plan. Then, the FEMS 1 is configured so that the above-mentioned predicted amount can be efficiently combined with the power supply plan from the renewable energy / distributed power source (5, 6) so that efficient energy management of the entire factory 20 can be realized. Perform peak cuts or peak shifts to level the load and adjust and optimize production plans.
 特に、ピークとなる時間帯におけるエネルギー負荷の平準化を図るように、ピークカットないしピークシフト等を行う。この平準化に対応して、生産計画における複数の生産ラインの並列的な稼働における作業の時間帯のシフトや、蓄電池からの電力供給の充当などを行う。 In particular, peak cuts or peak shifts are performed so as to level the energy load during peak hours. Corresponding to this leveling, the shift of the work time zone in parallel operation of a plurality of production lines in the production plan, allocation of power supply from the storage battery, and the like are performed.
 本システム10は、上記生産計画の変更にあたり、工場20の生産設備(21)以外の、照明や空調などの設備による負荷の予測、及び蓄電池・太陽光発電などからの電力供給の計画により、工場20全体でのエネルギーの最適化を図る。本システム10は、上記変更された生産計画による生産を実施し、蓄電池・太陽光発電などからの電力供給を最大限に活用して、商用系統電力の使用量を削減する。これにより工場20全体でのエネルギー負荷低減、及びエネルギー利用の効率化を実現する。 When the system 10 is changed, the system 10 predicts loads by facilities other than the production equipment (21) of the factory 20, such as lighting and air conditioning, and plans to supply power from storage batteries and solar power generation. Optimize energy throughout the 20th. The system 10 performs production based on the modified production plan, and maximizes power supply from storage batteries, solar power generation, and the like, thereby reducing the amount of commercial grid power used. Thereby, the energy load reduction in the whole factory 20 and the efficiency improvement of energy utilization are implement | achieved.
 [システム構成(1)]
 図1は、本実施の形態のシステム(エネルギー管理システム)10の構成を示す。本システム10の全体は、工場エネルギー管理システム(FEMS)1、生産管理システム(PMSと略す)2、電力量計(メータ)3、照明・空調システム4、蓄電池システム5、太陽光発電システム6、及び管理対象である工場20を有し、これらが相互に通信手段で接続される構成である。FEMS1に対してPMS2及び各部(3~6)が通信ネットワークや専用線などによって接続される。なお1~5等の各システムは、工場20内部に設けられてもよいし、外部に設けられてもよい。
[System configuration (1)]
FIG. 1 shows a configuration of a system (energy management system) 10 of the present embodiment. The entire system 10 includes a factory energy management system (FEMS) 1, a production management system (abbreviated as PMS) 2, a watt-hour meter (meter) 3, an illumination / air conditioning system 4, a storage battery system 5, a solar power generation system 6, And a factory 20 to be managed, and these are connected to each other by communication means. The PMS 2 and each unit (3 to 6) are connected to the FEMS 1 by a communication network or a dedicated line. Each system such as 1 to 5 may be provided inside the factory 20 or may be provided outside.
 本システム10は、特にFEMS1とPMS2との強い連携により工場20の電力(エネルギー)のピークシフト等を制御する機能を提供する。また本システム10は、工場20に対して再生可能エネルギー・分散型電源によるエネルギー(電力)の供給が可能なシステムとして、蓄電池システム5及び太陽光発電システム6を含んで成る。本システム10はこれら(5,6)のエネルギー(電力)を活用して生産計画を調整する。 This system 10 provides a function for controlling the peak shift of the power (energy) of the factory 20 in particular by strong cooperation between the FEMS 1 and the PMS 2. The system 10 includes a storage battery system 5 and a solar power generation system 6 as a system capable of supplying energy (electric power) to the factory 20 using a renewable energy / distributed power source. The system 10 uses these (5, 6) energy (electric power) to adjust the production plan.
 工場20は、所定の生産ライン(言い換えると生産設備)21を含む構成であり、生産管理システム2による生産計画に従い、生産ライン21を用いて、所定の製品・部品などが生産される。 The factory 20 has a configuration including a predetermined production line (in other words, a production facility) 21, and predetermined products / parts are produced using the production line 21 in accordance with a production plan by the production management system 2.
 FEMS1は、生産ライン(生産設備)21を持つ工場20を対象(需要家)として、工場20の全体のエネルギー管理を行い、省エネ化などを図る。FEMS1は、サーバ11やDB(データベース)などの公知技術で構成される。サーバ11でCPU及びメモリ等を用いてプログラム処理を実行することによりFEMS1の各機能(101~103等)を実現する。FEMS1の主な機能として、生産計画連携・調整機能101、エネルギー負荷監視機能102、エネルギー供給制御機能103等を有する。その他、FEMS1は、ネットワークを介して外部から必要な情報(後述の予測用情報など)を参照/取得する機能などを含む。またFEMS1では、管理者(U1)等の端末からサーバ11にアクセスして画面で各種情報の設定・閲覧などが可能となっている。FEMS1は、各システム(2~5)から収集した実績情報や、自身の予測情報などをDBに格納する。 FEMS 1 targets the factory 20 having the production line (production facility) 21 as an object (customer), and manages the energy of the entire factory 20 to save energy. The FEMS 1 is configured by a known technique such as a server 11 or a DB (database). Each function (101 to 103, etc.) of the FEMS 1 is realized by executing a program process using the CPU and memory in the server 11. The main functions of the FEMS 1 include a production plan cooperation / adjustment function 101, an energy load monitoring function 102, an energy supply control function 103, and the like. In addition, the FEMS 1 includes a function of referencing / acquiring necessary information (such as prediction information described later) from the outside via a network. Moreover, in FEMS1, it is possible to set / view various information on the screen by accessing the server 11 from a terminal such as an administrator (U1). The FEMS 1 stores performance information collected from each system (2 to 5), its own prediction information, and the like in the DB.
 特にFEMS1には、PMS2の立案する生産計画に連携して当該生産計画を調整・最適化する機能(生産計画連携・調整機能101)を備える。この機能(101)は、工場20のエネルギー負荷を平準化するようにピークカット・ピークシフト等の処理を行うことが含まれる。 Especially, the FEMS 1 has a function (production plan cooperation / adjustment function 101) for adjusting / optimizing the production plan in cooperation with the production plan planned by the PMS2. This function (101) includes performing processing such as peak cut and peak shift so as to level the energy load of the factory 20.
 またFEMS1は、PMS2、電力量計3、及び照明・空調システム4に対する、エネルギー負荷監視機能102を有し、工場20に関するエネルギーの負荷ないし需要の予測・監視を行う。FEMS1は、電力量計3による計測情報を収集して、工場20のエネルギー負荷の見える化・監視を行う。FEMS1は、照明・空調システム4に対しては、照明・空調などの設備の使用電力量を把握すると共に、デマンド(需要)に応じた制御を行う。 The FEMS 1 has an energy load monitoring function 102 for the PMS 2, the watt-hour meter 3, and the lighting / air conditioning system 4, and predicts / monitors the energy load or demand related to the factory 20. The FEMS 1 collects measurement information from the watt-hour meter 3 to visualize and monitor the energy load of the factory 20. The FEMS 1 grasps the power consumption of facilities such as lighting and air conditioning for the lighting and air conditioning system 4 and performs control according to demand (demand).
 またFEMS1は、蓄電池システム5及び太陽光発電システム6に対する、エネルギー供給制御機能103を有し、工場20に対するエネルギー(再生可能エネルギー・分散型電源)の供給・制御を行う。FEMS1は、蓄電池システム5に対しては、蓄電池の充電・放電の計画(スケジュール)を立てて制御する。蓄電池からの放電により工場20へ電力を供給する。FEMS1は、太陽光発電システム6に対しては、太陽光発電の発電量を予測・把握する。太陽光発電システム6の発電力を蓄電池システム5の蓄電池に蓄電(充電)する。 Further, the FEMS 1 has an energy supply control function 103 for the storage battery system 5 and the photovoltaic power generation system 6, and supplies and controls energy (renewable energy / distributed power source) to the factory 20. The FEMS 1 controls and controls the storage battery system 5 by charging / discharging the storage battery. Electric power is supplied to the factory 20 by discharging from the storage battery. The FEMS 1 predicts and grasps the power generation amount of solar power generation for the solar power generation system 6. The power generated by the solar power generation system 6 is stored (charged) in the storage battery of the storage battery system 5.
 生産管理システム(PMS)2は、生産計画システム等とも称し、工場20の生産ライン(生産設備)21を使用した製品等の生産における生産計画を立案し、その生産計画による生産管理(生産の実施のモニタ、生産実績情報の記録など)を行う。なおPMS2は既存システムの適用も可能である。PMS2は、FEMS1との連携に対応した、生産計画の立案の機能などを有する。PMS2は、生産計画情報、生産実績情報、生産の制約条件の情報、及び生産の原単位情報などを含むデータをDB等に記憶・管理する。FEMS1及びPMS2はそれぞれPMS2及びFEMS1との連携のためのインタフェース及び共通のフォーマット等を有し、互いに必要なデータ情報を送受信可能である。 The production management system (PMS) 2 is also referred to as a production planning system or the like, and creates a production plan for production of products using the production line (production equipment) 21 of the factory 20, and performs production management (execution of production) based on the production plan. Monitoring, production record information, etc.). The PMS 2 can be applied to an existing system. The PMS 2 has a function of producing a production plan corresponding to cooperation with the FEMS 1. The PMS 2 stores and manages data including production plan information, production result information, production constraint information, production basic unit information, and the like in a DB or the like. The FEMS 1 and the PMS 2 have an interface for cooperating with the PMS 2 and the FEMS 1 and a common format, respectively, and can transmit and receive necessary data information.
 電力量計(メータ)3は、工場20内の分電盤などに設置され、工場20の負荷(生産ライン21で使用する電力量など)の計測・収集を行う。メータ3は、情報処理機能を備えるスマートメータ等としてもよい。 The watt-hour meter (meter) 3 is installed on a distribution board or the like in the factory 20, and measures and collects loads (such as the amount of power used in the production line 21) of the factory 20. The meter 3 may be a smart meter or the like having an information processing function.
 照明・空調システム4は、工場20の生産ライン(生産設備)21以外の、電力を使用する関連する設備である、照明機器・空調機器・OA機器などを含む機器・システムである。照明・空調システム4は、所定の制御系、例えば照明や空調の状態を自動的に制御する機能や、照明や空調の負荷を予測する機能などを持つシステム(公知技術)を含んでもよい。例えば照明・空調システム4は、工場20内の照明・空調などの運転状態・温度状態などを自律的に制御・監視する。 The lighting / air-conditioning system 4 is a device / system including lighting equipment, air-conditioning equipment, OA equipment, etc., which are related equipment that uses electric power, other than the production line (production equipment) 21 of the factory 20. The illumination / air conditioning system 4 may include a predetermined control system, for example, a system (a publicly known technology) having a function of automatically controlling the state of illumination and air conditioning, a function of predicting loads of illumination and air conditioning, and the like. For example, the lighting / air conditioning system 4 autonomously controls / monitors the operating state / temperature state of lighting / air conditioning in the factory 20.
 なお本実施の形態では、工場20の生産ライン21に対して、照明・空調などの設備は基本的に独立的に扱われ制御される。照明・空調などの設備で使用する電力量については、メータ3で計測・把握されるが、照明・空調システム4自体で把握可能な場合はそれを利用してもよい。また工場20の生産ライン21での生産自体に直接係わる照明・空調などの条件(例えば所定の工程時に温度を一定にするための条件)についてはPMS2の生産計画(生産ラインの使用電力量など)で管理・反映されている。よって、照明・空調などの設備に関して、全体の電力のうち、上記の生産時の条件として使用する分を除いた分を、FEMS1及び照明・空調システム4により、デマンドに応じて制御する。 In this embodiment, facilities such as lighting and air conditioning are basically handled and controlled independently of the production line 21 of the factory 20. The amount of electric power used in facilities such as lighting and air conditioning is measured and grasped by the meter 3, but may be used if it can be grasped by the lighting and air conditioning system 4 itself. In addition, regarding the conditions such as lighting and air-conditioning directly related to the production itself in the production line 21 of the factory 20 (for example, conditions for keeping the temperature constant during a predetermined process), the production plan of the PMS 2 (such as the amount of power used in the production line) It is managed and reflected in. Therefore, with respect to facilities such as lighting and air conditioning, the FEMS 1 and the lighting and air conditioning system 4 control the portion of the entire power, excluding the amount used as the above-mentioned production conditions, according to demand.
 蓄電池システム5は、蓄電池(例えばリチウムイオン二次電池)、及びその制御基板(パワーコンディショナー)などを含んで成る。蓄電池システム5は、FEMS1が生産計画の調整に伴って立案する充放電計画(スケジュール)に従い、充電及び放電が行われる。 The storage battery system 5 includes a storage battery (for example, a lithium ion secondary battery) and its control board (power conditioner). The storage battery system 5 is charged and discharged according to a charging / discharging plan (schedule) that the FEMS 1 plans in accordance with the adjustment of the production plan.
 太陽光発電システム6は、太陽光発電パネル及びその制御基板などを含んで成る。太陽光発電システム6は、太陽光発電による電力を蓄電池システム5あるいは工場20内に供給する。 The photovoltaic power generation system 6 includes a photovoltaic power generation panel and its control board. The photovoltaic power generation system 6 supplies electric power generated by photovoltaic power generation to the storage battery system 5 or the factory 20.
 その他、本システム10は、例えば工場20の排熱を利用して発電や蓄電する公知のシステムを用いてFEMS1に連携して同様に制御するようにしてもよい。 In addition, the present system 10 may be similarly controlled in cooperation with the FEMS 1 by using a known system that generates power or stores electricity using the exhaust heat of the factory 20, for example.
 なお本実施の形態は、エネルギー管理の対象として、工場20のライン生産に適用した場合であるが、これに限らず他の生産方式にも同様に適用可能である。また本実施の形態は、FEMS1を主体としてPMS2に連携する形態であるが、逆に、PMS2を主体としてFEMS1に連携する形態としてもよい。即ちPMS2がFEMS1からエネルギー管理関連の情報を取得して生産計画を調整するようにしてもよい。またFEMS1とPMS2を1つのシステムに統合してもよい。また他のシステム要素(3~6)についても適宜分離や統合した形態としてもよい。 In addition, although this Embodiment is a case where it applies to the line production of the factory 20 as an object of energy management, it is applicable not only to this but another production system similarly. Moreover, although this Embodiment is a form which cooperates with PMS2 by making FEMS1 into a subject, it is good also as a form which cooperates with FEMS1 by making PMS2 a subject. That is, the PMS 2 may acquire information related to energy management from the FEMS 1 and adjust the production plan. Further, FEMS1 and PMS2 may be integrated into one system. Other system elements (3 to 6) may be appropriately separated or integrated.
 [システム構成(2)]
 図2は、図1のシステム10の主にFEMS1の詳しい機能ブロック構成を示す。FEMS1(そのサーバ11)は、処理部として、生産計画調整・最適化部12、負荷見える化・収集部13、設備負荷予測・デマンド制御部14、充放電制御部15、発電量予測部16、エネルギー(E)需要予測部111、加算部112、再計算制御部113、目標制御部114、等を有する。FEMS1はDBに実績情報d11や予測情報d12を格納する。
[System configuration (2)]
FIG. 2 shows a detailed functional block configuration of mainly the FEMS 1 of the system 10 of FIG. The FEMS 1 (its server 11) includes, as processing units, a production plan adjustment / optimization unit 12, a load visualization / collection unit 13, an equipment load prediction / demand control unit 14, a charge / discharge control unit 15, a power generation amount prediction unit 16, It includes an energy (E) demand prediction unit 111, an addition unit 112, a recalculation control unit 113, a target control unit 114, and the like. The FEMS 1 stores performance information d11 and prediction information d12 in the DB.
 生産計画調整・最適化部12は、PMS2の立案した生産計画(K1)を、ピークカット・ピークシフト等を含め、調整・最適化する処理を行う。生産計画調整・最適化部12は、充放電計画部121、目標値設定部122等を含んで成る。充放電計画部121は、蓄電池システム5の充放電計画を作成する。目標値設定部122は、ピークカットに関する目標値を設定する。 The production plan adjustment / optimization unit 12 adjusts and optimizes the production plan (K1) prepared by the PMS 2 including peak cut and peak shift. The production plan adjustment / optimization unit 12 includes a charge / discharge planning unit 121, a target value setting unit 122, and the like. The charge / discharge planning unit 121 creates a charge / discharge plan for the storage battery system 5. The target value setting unit 122 sets a target value related to peak cut.
 負荷見える化・収集部13は、メータ3から計測情報を収集し、工場20のエネルギー負荷を見える化する処理、即ちGUI(グラフィカルユーザインタフェース)画面に負荷のグラフなどの各種情報を表示してユーザ操作可能とする処理などを行う。 The load visualization / collection unit 13 collects measurement information from the meter 3 and visualizes the energy load of the factory 20, that is, displays various information such as a load graph on a GUI (graphical user interface) screen. Perform processing to enable operation.
 設備負荷予測・デマンド制御部14は、照明・空調システム4から情報を取得して照明・空調などの設備のエネルギー負荷を予測する処理や、照明・空調システム4に対するデマンドによる制御の処理を行う。14では、照明・空調などの設備で固定的に消費する分の電力量を予測している。 The equipment load prediction / demand control unit 14 obtains information from the lighting / air conditioning system 4 and predicts the energy load of the equipment such as lighting / air conditioning, and performs control processing on demand for the lighting / air conditioning system 4. No. 14 predicts the amount of power that is fixedly consumed by facilities such as lighting and air conditioning.
 充放電制御部15は、蓄電池システム5に対して充放電計画に従い充電・放電を制御する処理を行う。 The charging / discharging control unit 15 performs a process for controlling the charging / discharging of the storage battery system 5 according to the charging / discharging plan.
 発電量予測部16は、気象情報などに基づき太陽光発電システム6の発電量を予測する処理などを行う。 The power generation amount prediction unit 16 performs processing for predicting the power generation amount of the solar power generation system 6 based on weather information and the like.
 エネルギー需要予測部111は、14による設備負荷予測量や、16による発電予測量を用いて、エネルギー需要量を予測する。加算部112は、111によるエネルギー需要予測量に、調整前の生産計画(K1)での使用予定の電力量を加算する。再計算制御部113は、生産の実施・実績及び生産計画(K1)の立案に応じて、111,112,12等の再計算を制御する。目標制御部114は、目標値とエネルギー需要とを比較して所定の制御を行う。これらは詳しくは図3で説明する。 The energy demand prediction unit 111 predicts the energy demand by using the estimated equipment load by 14 and the predicted power generation by 16. The adding unit 112 adds the amount of power scheduled to be used in the production plan (K1) before adjustment to the energy demand predicted amount by 111. The recalculation control unit 113 controls the recalculation of 111, 112, 12 and the like according to the execution / actual result of production and the production plan (K1). The target control unit 114 performs predetermined control by comparing the target value with the energy demand. These will be described in detail with reference to FIG.
 PMS2は、サーバやDB等で構成され、CPU及びメモリ等を用いてプログラム処理を実行することによりPMS2の機能を実現する。PMS2は、主な機能・処理部として、生産計画立案部201を有する。またPMS2では、管理者(U2)等の端末からサーバにアクセスして画面で各種情報の設定・閲覧などが可能となっている。 PMS2 is composed of a server, a DB, and the like, and implements the functions of PMS2 by executing program processing using a CPU, memory, and the like. The PMS 2 includes a production planning unit 201 as a main function / processing unit. In PMS2, the server can be accessed from a terminal such as an administrator (U2) and various information can be set and viewed on the screen.
 PMS2は、DBに、生産工程に係わる制約条件d21、作業案件d22、原単位情報d23などを記憶・管理する。またPMS2は、立案・調整した生産計画(K1,K2)情報や、工場20の生産ライン21から収集した生産実績情報などをDBに格納する。 The PMS 2 stores and manages the constraint condition d21, work item d22, basic unit information d23 and the like related to the production process in the DB. Further, the PMS 2 stores production plan (K1, K2) information that has been planned and adjusted, production result information collected from the production line 21 of the factory 20, and the like in the DB.
 制約条件d21は、製品単位ごと及び生産ラインごとの使用電力・人員・要期などの制約条件を示す。原単位情報d23は、製品単位ごと及び生産ラインごとの使用電力・人員・要期などの原単位を示す。作業案件d22は生産計画に対応した作業案件の情報である。なお原単位情報(d23)等をPMS2ではなくFEMS1等で管理してもよい。 Constraint condition d21 indicates a constraint condition such as power consumption, personnel, and time required for each product unit and each production line. The basic unit information d23 indicates basic units such as electric power used, personnel, and time required for each product unit and each production line. The work item d22 is information on a work item corresponding to the production plan. The basic unit information (d23) or the like may be managed not by PMS2 but by FEMS1 or the like.
 生産計画立案部201は、DBの情報(d21~d23等)に基づき、生産計画(K1)を作成・立案する。作成した生産計画K1の情報は、FEMS1に入力される。なおこの際、FEMS1からPMS2へアクセスして情報を取得する形としてもよいし、PMS2からFEMS1へアクセスして情報を送信する形などとしてもよい。 The production plan drafting unit 201 creates and drafts a production plan (K1) based on DB information (d21 to d23, etc.). Information on the created production plan K1 is input to FEMS1. At this time, the information may be acquired by accessing the PMS 2 from the FEMS 1 or may be transmitted by accessing the FEMS 1 from the PMS 2.
 FEMS1及びPMS2ではそれぞれ管理者(U1,U2)等のユーザによりGUI画面で情報を閲覧可能であり、例えば後述する図4~図11のようなグラフ・表などを画面に表示して確認・操作が可能である。GUI画面に表示する情報として、少なくとも、調整前後の生産計画(K1,K2)の情報、及び工場20の負荷(実績値)の見える化の情報がある。 In FEMS1 and PMS2, information such as managers (U1, U2) can be browsed on the GUI screen. For example, graphs and tables as shown in FIGS. Is possible. Information displayed on the GUI screen includes at least information on production plans (K1, K2) before and after adjustment and information on visualization of the load (actual value) of the factory 20.
 [生産計画と連携したエネルギー管理]
 図3は、本システム10で、FEMS1とPMS2の連携において、FEMS1に対してPMS2の生産計画情報を入力して調整し、生産計画と連携したエネルギー管理をサイクルで実施する概念などを示す。s1等は処理ステップ、d1等はデータ情報を示す。
[Energy management linked to production planning]
FIG. 3 shows a concept of the system 10 in which the production plan information of the PMS 2 is input to the FEMS 1 for adjustment in the cooperation between the FEMS 1 and the PMS 2 and energy management linked with the production plan is performed in a cycle. s1 etc. indicate processing steps, d1 etc. indicate data information.
 PMS2は、201により立案した生産計画(K1)の情報を、通信ネットワークを介してFEMS1に送信する(s1)。この調整前の生産計画(K1)の情報ないしそれに伴い送信される情報には、生産する製品ごと、及び生産ライン21毎の使用電力量や、当該生産計画に係わる制約条件の情報(例えば生産ライン毎の上限の電力量・人員・納期など)などを含んでいる。言い換えるとFEMS1は生産計画(K1)をPMS2から取得する。 The PMS 2 transmits the information of the production plan (K1) planned by 201 to the FEMS 1 via the communication network (s1). The information of the production plan (K1) before adjustment or the information transmitted along with this information includes the amount of power used for each product to be produced and for each production line 21 and information on constraint conditions related to the production plan (for example, production line Including the maximum amount of electricity, personnel, and delivery date). In other words, the FEMS 1 acquires the production plan (K1) from the PMS2.
 FEMS1は、定期的、例えば毎朝のタイミングで、実績情報や気象情報などに基づき、14による設備負荷予測や、16による発電予測を実行する(s2)。実績情報をもとに照明・空調などの設備の負荷量を予測し、また気象情報などに基づき太陽光発電量を予測する。そしてE需要予測部111は、それら予測量をもとにエネルギー需要を予測する。d1はエネルギー需要予測量のグラフデータ一例を示し、これはs2の設備負荷予測量から発電予測量を減算したデータである。 FEMS1 performs equipment load prediction by 14 and power generation prediction by 16 on a regular basis, for example, every morning, based on performance information and weather information (s2). Predict the load of equipment such as lighting and air conditioning based on the results information, and also predict the amount of photovoltaic power generation based on weather information. Then, the E demand prediction unit 111 predicts the energy demand based on the predicted amounts. d1 shows an example of graph data of the predicted amount of energy demand, which is data obtained by subtracting the predicted power generation amount from the estimated equipment load amount of s2.
 FEMS1(加算部112)は、上記s2のエネルギー需要予測量(d1)に対して、PMS2から受信した生産計画(K1)における生産ライン21ごとの使用電力量を加算する(s3)。d2はその加算後のエネルギー需要予測量のグラフデータ一例である。 The FEMS 1 (adding unit 112) adds the amount of power used for each production line 21 in the production plan (K1) received from the PMS 2 to the energy demand predicted amount (d1) of s2 (s3). d2 is an example of graph data of the predicted energy demand after the addition.
 FEMS1(生産計画調整・最適化部12)は、上記s3のデータd2に対し、ピークカット・ピークシフトを含む負荷平準化の処理を行う(s4)。この際、ピークカット・ピークシフトの処理として、全体において、負荷がピークとなる時間帯の生産計画(生産ラインの生産工程)を前後の時間帯にシフトしてピーク値を下げるように、生産計画(スケジュール)を調整・最適化する。またこの際、充放電計画部121により、蓄電池システム5の蓄電池の充放電計画を立てる。またこの際、目標値設定部122により、負荷平準化後のデータd3に示すように、目標電力となる目標値Xを設定する。負荷のピーク値がなるべく目標値X以下になるように計画を調整する。例えば目標値Xを超えてしまう分の電力を、蓄電池から放電供給するように上記の充放電計画を調整する。 The FEMS 1 (production plan adjustment / optimization unit 12) performs load leveling processing including peak cut and peak shift on the data d2 of s3 (s4). At this time, as a peak cut / peak shift process, the production plan in the time zone where the load is at a peak (production process of the production line) is shifted to the previous and next time zones to lower the peak value. Adjust and optimize (schedule). At this time, the charge / discharge planning unit 121 sets a charge / discharge plan for the storage battery of the storage battery system 5. At this time, the target value setting unit 122 sets a target value X to be the target power as shown in the data d3 after the load leveling. The plan is adjusted so that the peak value of the load is as small as possible below the target value X. For example, the above charge / discharge plan is adjusted so that power that exceeds the target value X is supplied from the storage battery.
 上記の目標値Xは、管理者などの人が初期値を設定してもよいし、FEMS1(目標値設定部122)が適宜自動計算して設定してもよい。デマンドに応じて目標値Xを可変に設定・制御してもよい。 The above target value X may be set as an initial value by a person such as an administrator, or may be set automatically by FEMS1 (target value setting unit 122) as appropriate. The target value X may be set and controlled variably according to demand.
 PMS2は、上記s3の調整後の生産計画(K2)のデータd3に従い、工場20の生産ライン21での生産を実施・制御し(s5)、生産実績情報などを記録する。 The PMS 2 executes and controls the production in the production line 21 of the factory 20 in accordance with the data d3 of the production plan (K2) after the adjustment of s3 (s5), and records production result information and the like.
 上記調整後の生産計画(K2)に従う生産の実施(s5)の結果、メータ3によって計測された実績値などに基づき、FEMS1(再計算制御部113)は、所定のタイミング、例えば1時間毎に、予測・計画の修正に基づく再計算の処理を起動する(s6)。言い換えると新たな生産計画(K1)の入力(s1)に応じて、調整・最適化のサイクル(s2~s5)を同様に実行する。 As a result of the implementation (s5) of production according to the adjusted production plan (K2), based on the actual value measured by the meter 3, the FEMS 1 (recalculation control unit 113) performs predetermined timing, for example, every hour. Then, a recalculation process based on the correction of the prediction / plan is started (s6). In other words, according to the input (s1) of the new production plan (K1), the adjustment / optimization cycle (s2 to s5) is similarly executed.
 またFEMS1は、上記の際(s6)、目標制御部114を用いて、実際のデマンド値がd3の目標値Xを超過したかどうか判定し(s7)、超過(デマンド値>X)を検出した場合、例えばPMS2あるいは工場20に対して当該生産ライン21の強制的な停止の要求などを発行・送信する(s8)。あるいは、停止させる以外にも、所定のメッセージ等を管理者などに対して出力して報せるようにしてもよい。 Further, in the above case (s6), the FEMS 1 uses the target control unit 114 to determine whether the actual demand value exceeds the target value X of d3 (s7), and detects the excess (demand value> X). In this case, for example, a request to forcibly stop the production line 21 is issued / transmitted to the PMS 2 or the factory 20 (s8). Alternatively, in addition to stopping, a predetermined message or the like may be output and reported to an administrator or the like.
 [負荷平準化(ピークカット・ピークシフト)]
 図4,図5に、PMS2とFEMS1の連携による負荷平準化(ピークカット・ピークシフト)の概念を示す。図4の(a),(b)は、PMS2の生産管理・生産計画の例におけるピークカット(PCと略す)・ピークシフト(PSと略す)による負荷平準化の前後を示す。対応して、図5の(a),(b)は、FEMS1(前記111)のエネルギー需要予測(シミュレート)におけるPC・PSによる負荷平準化の前後のグラフを示す。
[Load leveling (peak cut, peak shift)]
4 and 5 show the concept of load leveling (peak cut / peak shift) by cooperation between PMS2 and FEMS1. 4A and 4B show before and after load leveling by peak cut (abbreviated as PC) and peak shift (abbreviated as PS) in an example of production management / production plan of PMS2. Correspondingly, FIGS. 5A and 5B show graphs before and after load leveling by PC / PS in the energy demand prediction (simulation) of FEMS1 (111).
 図4(a)で、工場20の生産ライン21の例として、並列稼動可能な複数のライン#1~#5がある。ライン上の作業(工程)は例えば図示するように、段取り・準備の単位と、製造の単位と、清掃の単位とを有する。例えばライン#3上のある作業(401)は、13時~13時30分が段取り・準備、13時30分~15時30分が製造、15時30分~16時が清掃である。製造の単位(時間)では、所定の電力を使用するものとする。同様にライン#5の作業402(11時30分~16時の製造)などを有する。図4(a)の調整前の生産計画(K1)に対応した状態では、13時~15時付近のように特定の時間帯で複数のラインの生産が重なっており、エネルギー負荷が高く集中している。 4A, as an example of the production line 21 of the factory 20, there are a plurality of lines # 1 to # 5 that can be operated in parallel. The operations (processes) on the line include, for example, a setup / preparation unit, a manufacturing unit, and a cleaning unit, as shown in the figure. For example, one work (401) on line # 3 is setup / preparation from 13:00 to 13:30, manufacturing from 13:30 to 15:30, and cleaning from 15:30 to 16:00. In the unit of production (time), predetermined power is used. Similarly, line 402 has work 402 (manufacturing from 11:30 to 16:00). In the state corresponding to the production plan (K1) before adjustment in FIG. 4A, the production of multiple lines overlaps in a specific time zone, such as around 13:00 to 15:00, and the energy load is high and concentrated. ing.
 図4(a)の作業401,402は、前記生産計画調整・最適化の処理(12,s6)におけるPC・PSにより、図4(b)の作業411,412のように前後の時間帯へシフトされる。特に、ライン#3、#5の計画作業(401,402)を、負荷が集中した時間帯よりも前の、比較的負荷が低い時間帯(11時~12時付近)へシフトした場合である。これにより時間及び生産ライン21全体において負荷が緩和・平準化されている。 The operations 401 and 402 in FIG. 4A are moved to the preceding and following time zones like the operations 411 and 412 in FIG. 4B by the PC / PS in the production plan adjustment / optimization process (12, s6). Shifted. In particular, this is a case where the planned work (401, 402) of lines # 3 and # 5 is shifted to a time zone (11:00 to 12:00) where the load is relatively low before the time zone when the load is concentrated. . As a result, the load is alleviated and leveled over time and the entire production line 21.
 上記に対応して、図5(a)で、横軸は時間[h]、縦軸は各ライン#1~#5ごとの電力量[kWh]を示す。501の線はエネルギー需要量予測を示す。同様に図5(b)はPC・PS後を示す。エネルギー需要量予測は、(a)の501では凹凸が大きいが、(b)の502では平らになっており、ピーク値が500程度から350程度へと低くなっている。 Corresponding to the above, in FIG. 5A, the horizontal axis indicates time [h], and the vertical axis indicates the electric energy [kWh] for each of the lines # 1 to # 5. A line 501 indicates an energy demand prediction. Similarly, FIG. 5B shows the state after PC · PS. In the energy demand prediction, the unevenness is large at 501 of (a), but is flat at 502 of (b), and the peak value is lowered from about 500 to about 350.
 [生産計画立案]
 図6は、PMS2(前記201)による生産計画の立案の適用例における、データ情報例を示す。工場20の生産ライン21における生産する製品の例としてUPS(無停電電源装置)に適用した場合であり、生産工程の例として試験ラインに適用した場合を示す。A1は、PMS2で管理されている原単位情報(d23)の一種であり、製品別試験原単位を示す。A2は、作業案件の情報(d22)である。A3は、制約条件(d21)の一種である試験工程制約条件である。
[Production planning]
FIG. 6 shows an example of data information in an application example of planning a production plan by the PMS 2 (201 described above). An example of a product produced in the production line 21 of the factory 20 is applied to a UPS (uninterruptible power supply), and a case of application to a test line is shown as an example of a production process. A1 is a kind of basic unit information (d23) managed by the PMS2, and indicates a test basic unit for each product. A2 is work item information (d22). A3 is a test process constraint condition which is a kind of the constraint condition (d21).
 図6で、製品別試験原単位A1は、製品1台毎にその試験に必要な試験エリア(各生産ラインに対応する)の面積、試験時間、人員、最大消費電力を示す。本例では、A1は、管理項目として、(a1)UPS容量、(a2)試験エリア、(a3)試験時間、(a4)試験人数、(a5)最大電力を有する。 Referring to FIG. 6, product-specific test basic unit A1 indicates the area, test time, personnel, and maximum power consumption of the test area (corresponding to each production line) required for each product. In this example, A1 has (a1) UPS capacity, (a2) test area, (a3) test time, (a4) number of testers, and (a5) maximum power as management items.
 作業案件A2は、製品の案件ごとに、試験台数、及び試験要期(試験を完了させなければならない期限)を示す。本例では、A2は、管理項目として、(a6)案件、(a7)台数、(a8)試験要期を有する。a6の案件の情報は、各社・仕様(UPS容量)などの情報がある。 Work item A2 indicates the number of tests and the test period (time limit for completing the test) for each product item. In this example, A2 has (a6) project, (a7) number of units, and (a8) test period as management items. The information on the item a6 includes information such as each company and specification (UPS capacity).
 試験工程制約条件A3は、許容試験エリア、試験人員、最大電力上限値などを定義した制約条件である。本例では、A3は、管理項目として、(a9)制約条件と、その値である(a10)制約値とを有する。各レコードで各制約条件が定義される。例えば許容試験エリアは770mまで、試験人数は5人まで、電力上限は2000kVAである。 The test process constraint condition A3 is a constraint condition that defines an allowable test area, test personnel, a maximum power upper limit value, and the like. In this example, A3 has (a9) constraint conditions and (a10) constraint values, which are the values, as management items. Each constraint is defined in each record. For example, the allowable test area is up to 770 m 2 , the number of testers is up to 5, and the power upper limit is 2000 kVA.
 図7のA4は、図6のA1~A3に基づき作成される生産計画(K1)の情報例を示す。生産計画A4は、製品別試験原単位A1及び作業案件A2に対して試験工程制約条件A3を考慮することにより立案される。本例では、A4は、管理項目として、例えば(a11)試験日、(a12)試験エリア~(a16)試験エリア、(a17)最大電力を有する。a12~a16の5つの試験エリアは、前述の5つの生産ライン#1~#5に対応している。図7から図4のような表に変換可能である。上記A1~A4から工場20のエネルギー負荷量を計算可能であり、図5のようにエネルギー需要量をシミュレーション計算により予測可能である。 7A4 shows an example of information on the production plan (K1) created based on A1 to A3 in FIG. The production plan A4 is made by considering the test process restriction condition A3 for the test unit A1 for each product and the work item A2. In this example, A4 has, for example, (a11) test date, (a12) test area to (a16) test area, and (a17) maximum power as management items. The five test areas a12 to a16 correspond to the five production lines # 1 to # 5 described above. 7 to 4 can be converted into a table as shown in FIG. The energy load amount of the factory 20 can be calculated from the above A1 to A4, and the energy demand amount can be predicted by simulation calculation as shown in FIG.
 [エネルギー需要・負荷予測]
 図8は、FEMS1でのエネルギー需要・負荷の予測の例について示す。FEMS1(E需要予測部111)により工場20内の設備(照明・空調など)の単位時間当たりの負荷予測(前記14)、及び太陽光発電量予測(前記16)を行い、設備負荷予測量から発電予測量を減算することにより実質的なエネルギー負荷・需要を算出する例を示す。
[Energy demand / load forecast]
FIG. 8 shows an example of prediction of energy demand / load in FEMS1. FEMS1 (E demand prediction unit 111) performs load prediction per unit time (14) and photovoltaic power generation amount prediction (16) of equipment (lighting, air conditioning, etc.) in the factory 20 from the equipment load prediction amount. An example of calculating a substantial energy load / demand by subtracting the power generation prediction amount will be shown.
 図8のB1は、予測に用いる予測入力情報を示し、DBに格納される。B1は例えば、過去実績情報(例えば3または4から取得可能)、気象情報(例えば外部の気象情報提供者から取得可能)、就業カレンダー(例えば工場20またはPMS2から取得可能)などを用いることができる。B2は、B1に基づく設備負荷予測量のグラフである。横軸は時間、縦軸は負荷量(電力量)を示す。FEMS1(前記111,14)は、予測入力情報B1に基づき、単位時間当たりのエネルギー負荷(主として照明・空調などの設備の負荷)を予測し、その結果であるB2をDBに格納する。 B1 in FIG. 8 indicates prediction input information used for prediction, and is stored in the DB. For example, B1 can use past performance information (eg, obtainable from 3 or 4), weather information (eg, obtainable from an external weather information provider), work calendar (eg, obtainable from the factory 20 or PMS2), and the like. . B2 is a graph of the estimated equipment load based on B1. The horizontal axis represents time, and the vertical axis represents the load amount (power amount). The FEMS 1 (111, 14) predicts an energy load per unit time (mainly a load of facilities such as lighting and air conditioning) based on the predicted input information B1, and stores the result B2 in the DB.
 B3は、予測に用いる太陽光発電予測情報を示し、DBに格納される。B3は例えば、気温予測や日射量予測(例えば外部の気象情報提供者から取得可能)、過去実績などを用いることができる。気温予測や日射量予測は、単位時間当たりの気温・日射量などの予測情報であり、過去実績はそれらの過去の実績情報である。 B3 indicates photovoltaic power generation prediction information used for prediction, and is stored in the DB. For B3, for example, temperature prediction, solar radiation amount prediction (for example, obtainable from an external weather information provider), past results, and the like can be used. The temperature prediction and the solar radiation amount prediction are prediction information such as the temperature and the solar radiation amount per unit time, and the past performance is the past performance information.
 B4は、B3に基づく太陽光発電予測量のグラフである。横軸は時間、縦軸は発電量を示す。FEMS1(前記111,16)は、太陽光発電予測情報B3に基づき、単位時間当たりの太陽光発電量を予測し、その結果のB4をDBに格納する。 B4 is a graph of the predicted amount of photovoltaic power generation based on B3. The horizontal axis represents time, and the vertical axis represents the amount of power generation. The FEMS 1 (111, 16) predicts the amount of photovoltaic power generation per unit time based on the photovoltaic power generation prediction information B3, and stores the resulting B4 in the DB.
 図9のB5は、図8のB2からB4を減算して得られる、エネルギー需要予測量のグラフであり、単位時間当たりの設備負荷予測量(即ち需要予測量)であり、図3のデータd1に対応する。横軸は時間、縦軸は需要量を示す。下側の901はB2からB4を減算した部分、上側の902はB4部分に相当する。FEMS1(前記111)は上記B2からB4を減算してB5を作成し、DBに格納する。 B5 in FIG. 9 is a graph of the predicted energy demand obtained by subtracting B4 from B2 in FIG. 8, and is a predicted equipment load per unit time (that is, a predicted demand), and data d1 in FIG. Corresponding to The horizontal axis shows time, and the vertical axis shows demand. The lower part 901 corresponds to the part obtained by subtracting B4 from B2, and the upper part 902 corresponds to the part B4. FEMS1 (111) subtracts B4 from B2 to create B5 and stores it in DB.
 次に、図10は、FEMS1で、エネルギー需要予測量(C1)に生産計画(K1)の電力量(C2≒A4)を加算して工場全体負荷量(C3)を得る例を示す。C1は、前記図9等のFEMS1が予測計算したエネルギー需要量(B5,d1)に相当する。1001部分は図9の901部分と同じである。C1は、工場20全体での設備(照明・空調など)の負荷予測量に対応する。C2は、前記図7等でPMS2が立案した生産計画(K1)のデータ情報(A4)に相当し、横軸は時間、縦軸は生産ライン21ごとの使用電力量を示す。前記加算部112はこれら(C1,C2)を加算する。 Next, FIG. 10 shows an example of obtaining the factory total load amount (C3) by adding the power amount (C2≈A4) of the production plan (K1) to the energy demand prediction amount (C1) in FEMS1. C1 corresponds to the energy demand (B5, d1) predicted and calculated by the FEMS 1 in FIG. The portion 1001 is the same as the portion 901 in FIG. C1 corresponds to the predicted load amount of equipment (lighting, air conditioning, etc.) in the entire factory 20. C2 corresponds to the data information (A4) of the production plan (K1) planned by the PMS 2 in FIG. 7 and the like, the horizontal axis indicates time, and the vertical axis indicates the power consumption for each production line 21. The adder 112 adds these (C1, C2).
 図11は、FEMS1で、上記加算後の工場全体負荷量(C3)における負荷平準化(PC・PS)の前後の例を示す。図11のC3は、ピークシフト前であり、図11のC4は、ピークシフト後である。1001の部分は同じ量である。ピーク値は、6000越えから6000未満へ減少している。上記のように、負荷が最も高くなるピーク時間帯を中心に、生産ライン21毎に生産計画を前後の時間帯にシフトすることにより負荷を平準化する。 FIG. 11 shows an example before and after load leveling (PC / PS) in the factory total load amount (C3) after the addition in FEMS1. C3 in FIG. 11 is before the peak shift, and C4 in FIG. 11 is after the peak shift. The portion of 1001 is the same amount. The peak value decreases from over 6000 to less than 6000. As described above, the load is leveled by shifting the production plan to the preceding and following time zones for each production line 21 around the peak time zone where the load is highest.
 図12は、FEMS1で、前記図11の負荷平準化後の工場全体負荷量(C4)に対して、蓄電池情報(D2)に基づく充放電計画情報(D3)を立案・反映し、かつ目標エネルギー負荷を設定した例を示す。D4は調整後の生産計画(K2)における工場全体負荷量に相当する。 FIG. 12 is a plan for reflecting and charging / discharging plan information (D3) based on the storage battery information (D2) with respect to the entire factory load (C4) after the load leveling in FIG. An example in which a load is set is shown. D4 corresponds to the entire factory load in the adjusted production plan (K2).
 D2の蓄電池情報は、例えば蓄電池システム5内の制御部(パワーコンディショナー)が持っている情報を取得して利用でき、DBに格納される。D2は、例えば、蓄電池の容量、機器状態、放電可能電力、放電可能時間などの情報がある。D2は、蓄電池システム5自体から取得可能な蓄電池容量や放電可能電力などの情報の他、FEMS1側で計算可能な放電可能時間や、FEMS1側で制約条件として定義する情報から成る。 The storage battery information of D2 can be obtained by using, for example, information held by a control unit (power conditioner) in the storage battery system 5 and stored in the DB. For example, D2 includes information such as the capacity of the storage battery, the device state, the dischargeable power, and the dischargeable time. D2 includes information such as storage battery capacity and dischargeable power that can be acquired from the storage battery system 5 itself, dischargeable time that can be calculated on the FEMS1 side, and information that is defined as a constraint on the FEMS1 side.
 D3の充放電計画情報は、C4,D2に基づく、工場20(生産ライン21)に対する単位時間当たりの蓄電池からの放電(供給)のスケジュールを含む情報である。D3は、例えば、目標電力、蓄電池の容量遷移、単時間充放電容量、停電時照明用充電などの情報がある。D3では、目標電力ないし目標負荷として、D4のYの線に示すように、低減目標値が設定される。これは前記図3の目標値(X)の設定に対応する。当該目標に応じて、単位時間当たりの充放電量が決定される。 The charge / discharge plan information of D3 is information including a schedule of discharge (supply) from the storage battery per unit time for the factory 20 (production line 21) based on C4 and D2. D3 includes information such as target power, storage battery capacity transition, single-time charge / discharge capacity, and charging for power failure. In D3, a target reduction value is set as the target power or target load, as indicated by the Y line in D4. This corresponds to the setting of the target value (X) in FIG. The charge / discharge amount per unit time is determined according to the target.
 D4で、目標Y以下である1201部分と目標Y以上である1202部分とを有する。1202部分については、計画として、蓄電池システム5からの放電によりまかなう。即ち太陽光発電量を考慮した蓄電池の蓄電量の範囲内で当該放電をまかなうように計画を立てる。FEMS1は、上記設定した目標負荷(Y)に基づき、前記設備負荷予測・デマンド制御部14を用いて、照明・空調システム4(設備)に対するデマンド監視を実施する。この際、例えば目標負荷(Y)に対して実測の負荷が急増(超過)した場合、FEMS1は、前述(114)のように生産ライン21に対して生産一時停止などを要求することができる。あるいは、照明・空調システム4に対して電力使用の低減や停止を要求することができる。上記計画・制御により工場20全体の負荷を削減することができる。 D4 has a 1201 portion that is equal to or smaller than the target Y and a 1202 portion that is equal to or larger than the target Y. About 1202 part, it covers by the discharge from the storage battery system 5 as a plan. In other words, a plan is made to cover the discharge within the range of the storage amount of the storage battery considering the amount of photovoltaic power generation. Based on the set target load (Y), the FEMS 1 uses the equipment load prediction / demand control unit 14 to perform demand monitoring for the lighting / air conditioning system 4 (equipment). At this time, for example, when the actually measured load suddenly increases (exceeds) with respect to the target load (Y), the FEMS 1 can request the production line 21 to pause the production as described above (114). Alternatively, the lighting / air conditioning system 4 can be requested to reduce or stop the use of power. The load of the whole factory 20 can be reduced by the said plan and control.
 [効果等]
 以上説明したように、本実施の形態のシステム10では、FEMS1とPMS2との連携により、生産計画情報に即した工場20のエネルギー需要の予測により、従来よりも高精度のエネルギー需要予測を可能とする。そして当該予測に基づき生産計画における生産ライン21の稼働のシフト等によりエネルギー負荷平準化を可能とし、効率的な生産計画・電力使用計画が可能である。また再生可能エネルギー・分散型電源(5,6)を活用した、負荷低減目標を含む充放電計画により、効率的な生産が可能である。また照明・空調などの設備(4)のデマンド制御による負荷低減を含めた、効率的な生産が可能である。これらにより従来よりも工場20全体の効率的なエネルギー管理による省エネなどを実現できる。また生産計画の精度の向上によりリードタイムの短縮などにもつながる。従来のFEMSは生産管理システムと連携していないためエネルギー需要予測精度が高くなかったが、本実施の形態では上記のように連携により予測精度を高め、エネルギー管理の効率化を実現している。
[Effects]
As described above, in the system 10 of the present embodiment, the energy demand can be predicted with higher accuracy than before by predicting the energy demand of the factory 20 in accordance with the production plan information by cooperation between the FEMS 1 and the PMS 2. To do. Based on the prediction, the energy load can be leveled by shifting the operation of the production line 21 in the production plan, and an efficient production plan and power usage plan are possible. Moreover, efficient production is possible by the charge / discharge plan including the load reduction target utilizing the renewable energy / distributed power source (5, 6). Moreover, efficient production is possible, including load reduction by demand control of equipment (4) such as lighting and air conditioning. As a result, it is possible to realize energy saving by more efficient energy management of the entire factory 20 than before. In addition, lead time can be shortened by improving the accuracy of production planning. Since the conventional FEMS is not linked to the production management system, the energy demand prediction accuracy is not high. However, in the present embodiment, the prediction accuracy is increased by cooperation as described above, and the efficiency of energy management is realized.
 以上、本発明者によってなされた発明を実施の形態に基づき具体的に説明したが、本発明は前記実施の形態に限定されるものではなく、その要旨を逸脱しない範囲で種々変更可能であることは言うまでもない。 As mentioned above, the invention made by the present inventor has been specifically described based on the embodiment. However, the present invention is not limited to the embodiment, and various modifications can be made without departing from the scope of the invention. Needless to say.
 1…工場エネルギー管理システム(FEMS)、2…生産管理システム(PMS)、3…電力量計(メータ)、4…照明・空調システム、5…蓄電池システム、6…太陽光発電システム、10…本システム(エネルギー管理システム)、11…サーバ、20…工場、21…生産ライン(生産設備)。 DESCRIPTION OF SYMBOLS 1 ... Factory energy management system (FEMS), 2 ... Production management system (PMS), 3 ... Electricity meter (meter), 4 ... Lighting / air-conditioning system, 5 ... Storage battery system, 6 ... Solar power generation system, 10 ... book System (energy management system), 11 ... server, 20 ... factory, 21 ... production line (production equipment).

Claims (9)

  1.  コンピュータの情報処理を用いて、生産設備を持つ工場を対象としてエネルギー管理を行うエネルギー管理システムであって、
     前記工場を対象としてエネルギー管理を行う工場エネルギー管理システムと、
     前記工場の生産設備における生産計画を管理する生産管理システムと、
     前記工場に対して再生可能エネルギーまたは分散型電源による電力を供給可能な電力供給システムと、を有し、
     前記工場エネルギー管理システムは、
     前記生産管理システムにより立案される生産計画に連携する処理と、
     前記工場のエネルギー負荷ないし需要量を予測する処理と、
     前記電力供給システムによる供給可能な電力を予測する処理と、
     前記生産計画の情報に対して、前記予測による供給可能な電力からの供給量を含めて、前記予測による工場のエネルギー負荷ないし需要量を平準化してより効率的なエネルギー管理となるようにピークカットまたはピークシフトを含む調整を行い、当該調整後の生産計画の情報を前記生産管理システムに対して出力する処理と、を行うこと、を特徴とするエネルギー管理システム。
    An energy management system that performs energy management for factories with production facilities using computer information processing,
    A factory energy management system for managing energy for the factory;
    A production management system for managing a production plan in the production facility of the factory;
    A power supply system capable of supplying renewable energy or power from a distributed power source to the factory,
    The factory energy management system is:
    Processing linked to a production plan planned by the production management system;
    A process for predicting the energy load or demand of the factory;
    A process of predicting power that can be supplied by the power supply system;
    Peak cut so that more efficient energy management is achieved by leveling the energy load or demand of the factory according to the prediction, including the supply amount from the power that can be supplied by the prediction, with respect to the information of the production plan Or an adjustment including a peak shift is performed, and a process of outputting the adjusted production plan information to the production management system is performed.
  2.  請求項1記載のエネルギー管理システムにおいて、
     前記工場エネルギー管理システムは、
     前記生産管理システムから、前記生産計画の情報として、製品ごと及び生産ラインごとの使用電力を含む情報と、当該生産に係わる制約条件の情報と、当該生産に係わる原単位の情報とを取得する処理と、
     前記調整の処理として、前記取得した情報を用いて、前記工場の生産設備を用いた複数の生産ラインにおける負荷の大きい時間帯の作業を、その前後の負荷の小さい時間帯にシフトして全体的に負荷を平準化するように前記ピークカットまたはピークシフトを含む調整を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    The factory energy management system is:
    Processing for acquiring information including power consumption for each product and each production line, information on constraint conditions related to the production, and information on basic units related to the production from the production management system as information on the production plan When,
    As the adjustment process, the acquired information is used to shift work in a time zone with a large load on a plurality of production lines using the production equipment of the factory to a time zone with a low load before and after that, and overall An adjustment including the peak cut or peak shift is performed so as to level the load on the energy management system.
  3.  請求項1記載のエネルギー管理システムにおいて、
     前記生産管理システムは、
     前記生産計画の情報として、製品ごと及び生産ラインごとの日時及び使用電力を含む情報と、当該生産に係わる制約条件の情報と、当該生産に係わる製品単位ごと及び生産ラインごとの使用電力、人員、及び時間を含む原単位の情報とを記憶する処理と、
     前記生産計画を立案する処理と、
     前記エネルギー管理システムとの連携のため、前記エネルギー管理システムとの間で前記生産計画を含むデータ情報を送受信する処理と、
     前記工場エネルギー管理システムで調整された生産計画の情報に従い前記工場の生産設備での生産を実施する処理と、を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    The production management system includes:
    As information of the production plan, information including date and time and power consumption for each product and each production line, information on constraint conditions related to the production, power usage for each product unit and production line for each production, personnel, And processing for storing basic unit information including time, and
    A process for preparing the production plan;
    Processing for transmitting / receiving data information including the production plan to / from the energy management system for cooperation with the energy management system;
    An energy management system comprising: performing production at a production facility of the factory according to information on a production plan adjusted by the factory energy management system.
  4.  請求項1記載のエネルギー管理システムにおいて、
     前記工場及び工場エネルギー管理システムに接続される照明・空調システムを有し、
     前記照明・空調システムは、前記工場の生産設備以外の設備である照明機器及び空調機器を含んで成り、
     前記工場エネルギー管理システムは、前記照明・空調システムからの情報を用いて、前記照明・空調を含む設備のエネルギー負荷を予測する処理と、
     前記照明・空調を含む設備のエネルギー負荷の予測量から、前記電力供給システムによる供給可能な電力の予測量を減算する処理と、
     前記減算した予測量に前記生産計画の使用電力量を加算して前記工場の全体のエネルギー需要予測量を得る処理と、
     前記工場の全体のエネルギー需要予測量に応じて、前記照明・空調を含む設備に対するデマンド制御を行う処理と、を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    The lighting and air conditioning system connected to the factory and factory energy management system,
    The lighting / air conditioning system includes lighting equipment and air conditioning equipment that are equipment other than production facilities of the factory,
    The factory energy management system uses information from the lighting / air conditioning system to predict the energy load of the facility including the lighting / air conditioning, and
    A process of subtracting the predicted amount of power that can be supplied by the power supply system from the predicted amount of energy load of the facility including the lighting and air conditioning;
    A process of adding the amount of power used in the production plan to the subtracted predicted amount to obtain an overall energy demand predicted amount of the factory;
    A process for performing demand control on the equipment including the lighting and air conditioning according to the predicted energy demand of the entire factory.
  5.  請求項1記載のエネルギー管理システムにおいて、
     前記電力供給システムとして、前記工場で発生する電力、あるいは所定の発電システムによる発電力を蓄電し、前記工場に対して放電による電力供給が可能な蓄電池システムを有し、
     前記工場エネルギー管理システムは、前記蓄電池システムと接続され、前記生産計画の調整に併せて、前記工場の全体のエネルギー需要量のうちの一部を、前記蓄電池システムからの放電による電力供給でまかなうように、前記蓄電池システムから前記工場に対する放電の計画を立案する処理を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    The power supply system has a storage battery system capable of storing electric power generated in the factory, or electric power generated by a predetermined power generation system, and capable of supplying electric power by discharging to the factory,
    The factory energy management system is connected to the storage battery system, and in conjunction with the adjustment of the production plan, a part of the total energy demand of the factory is supplied by power supply by discharge from the storage battery system. And an energy management system, characterized in that a process of planning a discharge from the storage battery system to the factory is performed.
  6.  請求項1記載のエネルギー管理システムにおいて、
     前記電力供給システムとして、太陽光発電または他の方式による発電システムを有し、
     前記工場エネルギー管理システムは、前記発電システムと接続され、
     前記発電システムからの情報または外部からの気象情報を含む情報を用いて、前記発電システムによる発電量を予測する処理と、
     前記工場のエネルギー負荷の予測量から、前記発電システムによる発電予測量を減算する処理と、
     前記減算した予測量に前記生産計画の使用電力量を加算して前記工場の全体のエネルギー需要予測量を得る処理と、を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    As the power supply system, having a power generation system by solar power generation or other methods,
    The factory energy management system is connected to the power generation system,
    A process of predicting the amount of power generated by the power generation system using information from the power generation system or information including weather information from outside,
    A process of subtracting the predicted power generation amount by the power generation system from the predicted amount of energy load of the factory;
    An energy management system, comprising: adding the amount of power used in the production plan to the subtracted predicted amount to obtain a predicted energy demand for the entire factory.
  7.  請求項1記載のエネルギー管理システムにおいて、
     前記工場エネルギー管理システムは、前記生産計画の調整において、前記予測による工場のエネルギー需要量に対し、目標値を設定する処理と、当該目標値を超える分を前記電力供給システムによる電力供給でまかなうように、前記電力供給システムから前記工場に対する電力供給の計画を立案する処理と、を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    In the adjustment of the production plan, the factory energy management system may set a target value for the predicted energy demand of the factory, and supply the power exceeding the target value with the power supply by the power supply system. And an energy management system that performs a process of planning a power supply from the power supply system to the factory.
  8.  請求項1記載のエネルギー管理システムにおいて、
     前記工場エネルギー管理システムは、前記生産計画の調整において、前記予測による工場のエネルギー需要量に対し、目標値を設定する処理と、前記調整後の生産計画に従う生産の実施による実績値における負荷量が前記目標値を超過している場合に、前記工場の生産設備または前記生産管理システムに対して、生産の停止を要求する処理と、を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    In the adjustment of the production plan, the factory energy management system includes a process for setting a target value with respect to the energy demand of the factory based on the prediction, and a load amount in the actual value by the execution of the production according to the adjusted production plan. An energy management system, wherein when the target value is exceeded, a process for requesting a production stop to the production facility of the factory or the production management system is performed.
  9.  請求項1記載のエネルギー管理システムにおいて、
     前記生産設備を含む工場の使用電力量を計測するメータと、
     前記工場エネルギー管理システムは、前記メータの情報を収集して前記工場の使用電力量を含む情報を画面で表示する処理を行うこと、を特徴とするエネルギー管理システム。
    The energy management system according to claim 1,
    A meter for measuring the amount of power used in a factory including the production facility;
    The said factory energy management system collects the information of the said meter, and performs the process which displays the information containing the electric energy consumption of the said factory on a screen, The energy management system characterized by the above-mentioned.
PCT/JP2013/077285 2012-10-26 2013-10-08 Energy management system WO2014065111A1 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2012-236204 2012-10-26
JP2012236204A JP6114532B2 (en) 2012-10-26 2012-10-26 Energy management system

Publications (1)

Publication Number Publication Date
WO2014065111A1 true WO2014065111A1 (en) 2014-05-01

Family

ID=50544491

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2013/077285 WO2014065111A1 (en) 2012-10-26 2013-10-08 Energy management system

Country Status (3)

Country Link
JP (1) JP6114532B2 (en)
MY (1) MY178295A (en)
WO (1) WO2014065111A1 (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105006822A (en) * 2015-07-30 2015-10-28 乔治费歇尔汽车产品(昆山)有限公司 Energy optimization control system
JP6059375B1 (en) * 2016-02-09 2017-01-11 ファナック株式会社 Production control system and integrated production control system
JPWO2015178256A1 (en) * 2014-05-19 2017-04-20 Jfeスチール株式会社 Electric power supply / demand guidance apparatus and electric power supply / demand guidance method
CN107392381A (en) * 2017-07-27 2017-11-24 中车青岛四方车辆研究所有限公司 A kind of railway vehicle air conditioner system energy consumption Forecasting Methodology, device and computer equipment
EP4080433A1 (en) * 2021-04-22 2022-10-26 Hitachi, Ltd. Management system and management method

Families Citing this family (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2015012753A (en) * 2013-07-01 2015-01-19 日新電設株式会社 On-demand type power control system, on-demand type power control method, and on-demand type power control program
KR101807975B1 (en) * 2016-12-01 2018-01-19 김영민 The Energy Management System including the product's energy cost calculating module measured by the distribution rate of the instrument data according to the percentage of the facility-specific distribution.
KR101847540B1 (en) * 2017-05-26 2018-05-28 스마트시스템(주) Peak Power Control System by Setting Type Working Environment Temperature
JP6956015B2 (en) * 2018-01-16 2021-10-27 積水化学工業株式会社 Power management system and power management method
JP7176338B2 (en) * 2018-10-04 2022-11-22 株式会社Ihi Operation plan optimization device
JP7140716B2 (en) * 2019-06-17 2022-09-21 トヨタ紡織株式会社 Energy management system and energy management method
CN112628900B (en) * 2021-01-21 2022-02-22 中国建筑西北设计研究院有限公司 Regional cooling system based on partitioned energy source station
JP2022130258A (en) * 2021-02-25 2022-09-06 均 石井 Paper and pulp manufacturing cost reduction method
JP2022130255A (en) * 2021-02-25 2022-09-06 均 石井 Cost reduction method of carbon fiber production
WO2023119393A1 (en) * 2021-12-21 2023-06-29 三菱電機株式会社 Power management assistance device, program, and power management assistance method

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09179604A (en) * 1995-09-13 1997-07-11 Toshiba Corp System and method for controlling operation of plant
JP2004151830A (en) * 2002-10-29 2004-05-27 Daikin Ind Ltd Energy demand optimization system and production schedule creation supporting system
JP2005092827A (en) * 2003-09-22 2005-04-07 Mitsubishi Electric Corp Scheduling system and program for making computer perform scheduling
JP2009282799A (en) * 2008-05-23 2009-12-03 Hitachi Ltd Method and program for plant operation planning
JP2011175463A (en) * 2010-02-24 2011-09-08 Hitachi Ltd Method and apparatus for supporting determination of production plan
JP2011259656A (en) * 2010-06-11 2011-12-22 Mitsubishi Heavy Industries Mechatronics Systems Ltd Energy management apparatus, energy management method, and energy management program
WO2012057307A1 (en) * 2010-10-29 2012-05-03 三洋電機株式会社 Control device for power management
JP2012175849A (en) * 2011-02-23 2012-09-10 Toshiba Mitsubishi-Electric Industrial System Corp Power demand management system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09179604A (en) * 1995-09-13 1997-07-11 Toshiba Corp System and method for controlling operation of plant
JP2004151830A (en) * 2002-10-29 2004-05-27 Daikin Ind Ltd Energy demand optimization system and production schedule creation supporting system
JP2005092827A (en) * 2003-09-22 2005-04-07 Mitsubishi Electric Corp Scheduling system and program for making computer perform scheduling
JP2009282799A (en) * 2008-05-23 2009-12-03 Hitachi Ltd Method and program for plant operation planning
JP2011175463A (en) * 2010-02-24 2011-09-08 Hitachi Ltd Method and apparatus for supporting determination of production plan
JP2011259656A (en) * 2010-06-11 2011-12-22 Mitsubishi Heavy Industries Mechatronics Systems Ltd Energy management apparatus, energy management method, and energy management program
WO2012057307A1 (en) * 2010-10-29 2012-05-03 三洋電機株式会社 Control device for power management
JP2012175849A (en) * 2011-02-23 2012-09-10 Toshiba Mitsubishi-Electric Industrial System Corp Power demand management system

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPWO2015178256A1 (en) * 2014-05-19 2017-04-20 Jfeスチール株式会社 Electric power supply / demand guidance apparatus and electric power supply / demand guidance method
CN105006822A (en) * 2015-07-30 2015-10-28 乔治费歇尔汽车产品(昆山)有限公司 Energy optimization control system
JP6059375B1 (en) * 2016-02-09 2017-01-11 ファナック株式会社 Production control system and integrated production control system
US9958861B2 (en) 2016-02-09 2018-05-01 Fanuc Corporation Production control system and integrated production control system
CN107392381A (en) * 2017-07-27 2017-11-24 中车青岛四方车辆研究所有限公司 A kind of railway vehicle air conditioner system energy consumption Forecasting Methodology, device and computer equipment
EP4080433A1 (en) * 2021-04-22 2022-10-26 Hitachi, Ltd. Management system and management method

Also Published As

Publication number Publication date
JP2014085981A (en) 2014-05-12
MY178295A (en) 2020-10-07
JP6114532B2 (en) 2017-04-12

Similar Documents

Publication Publication Date Title
JP6114532B2 (en) Energy management system
Chen et al. Measures to improve energy demand flexibility in buildings for demand response (DR): A review
Arun et al. Intelligent residential energy management system for dynamic demand response in smart buildings
Xiong et al. Multi-agent based multi objective renewable energy management for diversified community power consumers
US10727784B2 (en) Aggregation system, control method thereof, and control apparatus
Bao et al. A multi time-scale and multi energy-type coordinated microgrid scheduling solution—Part I: Model and methodology
JP5727063B1 (en) Energy management apparatus, energy management system, energy management method and program
Jindal et al. A heuristic-based appliance scheduling scheme for smart homes
JP6341409B2 (en) Power management method, power management system, power management apparatus and program
US9209625B2 (en) Method and system to co-optimize utilization of demand response and energy storage resources
US8676394B2 (en) Integrated demand response for energy utilization
Oldewurtel et al. A framework for and assessment of demand response and energy storage in power systems
US20150378381A1 (en) Systems and methods for energy cost optimization
US20140067142A1 (en) System and method for energy management
KR20130066814A (en) A power control method of electrical devices using control algorithm of maximum demand power
US11663541B2 (en) Building energy system with load-following-block resource allocation
KR20120112155A (en) Systems and methods for forecasting electrical load
Tiwari et al. Automated demand response in smart distribution grid: A review on metering infrastructure, communication technology and optimization models
US20200193345A1 (en) Cost optimization of a central energy facility with load-following-block rate structure
KR101918625B1 (en) System and method for providing power service to a plurality of customers using an energy storage device
JP6903531B2 (en) Distributed power control device, distributed power control system and distributed power control method
JP2015211516A (en) Charge/discharge control system for power storage device
Abrishambaf et al. SCADA office building implementation in the context of an aggregator
JP2013005470A (en) Simultaneous equal amount control system and its purchased electric power plan generation device
CN114365370A (en) Regional energy management device and regional energy management method

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 13848299

Country of ref document: EP

Kind code of ref document: A1

WWE Wipo information: entry into national phase

Ref document number: IDP00201502438

Country of ref document: ID

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 13848299

Country of ref document: EP

Kind code of ref document: A1