CN110546842B - Energy management device and method, energy management system, and operation planning method for energy management system - Google Patents
Energy management device and method, energy management system, and operation planning method for energy management system Download PDFInfo
- Publication number
- CN110546842B CN110546842B CN201780089900.XA CN201780089900A CN110546842B CN 110546842 B CN110546842 B CN 110546842B CN 201780089900 A CN201780089900 A CN 201780089900A CN 110546842 B CN110546842 B CN 110546842B
- Authority
- CN
- China
- Prior art keywords
- power
- schedule
- demand
- receiving unit
- self
- Prior art date
- Legal status (The legal status 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 status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides an energy management device and method, an energy management system, and an operation planning method for the energy management system, wherein in an enterprise composed of a power receiving unit and a power generating unit, a self-consignment plan is made by considering the uncertainty of a plurality of production schedules of a manufacturing plant, and further, the production schedule is adjusted to change the power demand so as to comply with the plan value and the same amount. An energy management device for an enterprise having a power generation unit and a power reception unit connected to a power system, characterized in that: an EMS is provided in a power generation unit and a power receiving unit, an AEMS is provided in an enterprise, the EMS of the power receiving unit predicts the power transition of each production line of the power receiving unit on a predetermined day, and classifies the operation schedule of the production line of the power receiving unit on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule, the AEMS determines the fixed demand on the predetermined day and the maximum demand in consideration of the undetermined schedule from the operation schedule and the power transition after the classification of the predetermined day reported from the EMS of the power receiving unit, determines the minimum self-consignment amount obtained as the difference between the maximum demand and the contract power of the power receiving unit, and outputs the minimum self-consignment amount to the power receiving unit within the range of the fixed demand, and the EMS of the power generation unit generates power according to the self-consignment plan output determined by the AEMS.
Description
Technical Field
The present invention relates to an energy management device and method, an energy management system, and an operation planning method for an energy management system for supplying power in an enterprise including a plurality of power generation units and a plurality of power receiving units, and more particularly, to an energy management device and method, an energy management system, and an operation planning method for an energy management system, which are capable of adjusting power in an enterprise in cooperation with a system for managing scheduling of a process of consuming power in a power receiving unit.
Background
In recent years, energy cost reduction and CO reduction have been achieved 2 For the purpose of emissions, demand for mutually regulating electric power in regions is increasing by combining distributed energy sources such as renewable energy, cogeneration, and storage batteries.
Specifically, for example, in a company having a plurality of units, when there is surplus power generated in a unit (power generation unit) having its own power generation facility and power is insufficient in a unit (power reception unit) purchasing external power, power is distributed from the power generation unit to the power reception unit. In this case, although the company must pay the consignment fee when the electric power is distributed via the electric power system, the company is provided with a cost advantage when the unit price of the generated electricity including the consignment fee is cheaper than the unit price of the external electric power. In this regard, in the country, a power self-consignment system was started as a part of the improvement of the power system in 2014, and low consignment costs were applied in the case of power regulation in the same enterprise. Therefore, it is expected that the present invention will be widely used in enterprises having a plurality of facilities, particularly enterprises having a plurality of manufacturing plants.
However, when self-consignment is performed via the power system, for example, there is an obligation that the planned value is proposed on the previous day and power is supplied on the current day so as to comply with the planned value, and if a discrepancy (imbalance) occurs, it is necessary to pay an imbalance fee. In planning, it is important to predict the power demand of the power receiving unit with high accuracy.
As a conventional technique related to power regulation, patent document 1 proposes a method of predicting the amount of power of a power receiving unit (a consumer) based on actual result data, and determining the self-consignment amount of power in consideration of the fuel consumption characteristics, the transmission loss rate, and consignment fees of a generator of a power generation unit.
Documents of the prior art
Patent document
Patent document 1: japanese patent laid-open No. 2005-261056
Disclosure of Invention
Problems to be solved by the invention
However, when the power receiving unit is a manufacturing plant, there are many production processes in which scheduling is not specified, and therefore, an error in power demand prediction increases, and the self-consignment plan is not reliable, and as a result, imbalance may occur. In addition, there is a problem that there is also a risk that the power purchased from the outside exceeds the contract power in the power receiving unit.
The present invention has been made in view of the above problems, and an object thereof is to: provided are an energy management device and method, an energy management system, and an operation planning method for an energy management system, which, in an enterprise comprising a plurality of power receiving units and a plurality of power generating units including a manufacturing plant, make a self-consignment plan in consideration of the uncertainty of a plurality of production schedules of the manufacturing plant, and further change the power demand by adjusting the production schedules to comply with the plan value while keeping the same amount.
Means for solving the problems
As described above, the present invention provides an energy management device in an enterprise including a power generation unit and a power reception unit connected to a power system, the energy management device including:
an EMS (Energy Management System) is installed in the power generating unit and the power receiving unit, an AEMS (Area Energy Management System) is installed in the enterprise,
the EMS of the power receiving unit predicts the power transition of each production line of the power receiving unit on a predetermined day, classifies the operation schedule of the production line of the power receiving unit on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
the AEMS specifies a specified demand for a specified day and a maximum demand in consideration of the unspecified schedule from the operation schedule after classification of a predetermined day reported from the EMS of the power receiving unit and the power transition, specifies a minimum self-consignment amount obtained as a difference between the maximum demand and the contract power of the entire power receiving unit, and outputs the minimum self-consignment amount to the power receiving unit within the range of the specified demand,
the EMS of the electricity generating unit generates electricity according to the self consignment plan output determined by the AEMS.
Further, the present invention provides an energy management method in an enterprise including a power generation unit and a power reception unit connected to a power system, the method comprising:
predicting the power transition of each production line of the power receiving unit on a predetermined day, classifying the operation schedule of the production line of the power receiving unit on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
determining a specified demand for a specified day and a maximum demand in consideration of the unspecified schedule on the basis of the operation schedule after classification on the specified day and the power transition, determining a minimum self-consignment amount obtained as a difference between the maximum demand and the contract power of the whole power receiving units, and outputting a self-consignment plan to the power receiving units within the range of the specified demand,
the power generation unit generates power in accordance with the self-consignment plan output.
Further, the present invention provides an energy management system in an enterprise including a power generation unit and a power reception unit connected to a power system, the energy management system including:
a demand fluctuation factor specifying means for specifying a demand fluctuation factor in the energy demand prediction of the entire power receiving unit on a predetermined day; a generation unit configured to evaluate a demand variation amount of a predetermined day based on the demand variation factor, and generate an energy production/purchase/transaction plan of the entire power receiving unit; and a presentation unit that presents the plurality of plans related to the energy production/purchase/transaction plan created by the creation unit.
Further, the present invention provides an operation planning method for energy management in an enterprise including a power generation unit and a power reception unit connected to a power grid, the method comprising:
in the prediction of the energy demand of the entire power receiving unit on a predetermined day, the schedules generated by the energy demand are classified into the fixed schedule, the undetermined schedule, and the adjustable schedule is changed to meet the planned value when the energy production/purchase/transaction plan is made based on the maximum error of the undetermined schedule evaluation demand.
Effects of the invention
According to the present invention, the energy costs of the entire enterprise can be reduced by maximizing the self-consignment amount while maintaining the same amount in compliance with the planned value.
Drawings
Fig. 1 is a diagram showing an example of the structure of an enterprise according to an embodiment of the present invention.
Fig. 2 is a diagram showing an example of a system configuration in an enterprise according to the embodiment of the present invention.
Fig. 3 is a diagram showing an example of a functional configuration of a production schedule management function according to an embodiment of the present invention.
Fig. 4 is a diagram showing an example of a self-consignment plan creation flow according to the embodiment of the present invention.
Fig. 5 is a diagram showing an example of scheduling of a production line and power demand in a power receiving unit according to an embodiment of the present invention.
Fig. 6 is a diagram showing an example of a self-consignment plan created in the AEMS according to the embodiment of the present invention.
Fig. 7 is a diagram showing an example of the self-consignment plan of the day created in the AEMS according to the embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described below with reference to the drawings.
Fig. 1 shows an example of the structure of an enterprise according to an embodiment of the present invention. The enterprise 3 is configured by a plurality of power generation units 4 (4 a to 4 n) and a plurality of power reception units 5 (5A to 5M) connected to the power system 1.
Here, the power generation unit 4 is configured by a power generation facility 9, a load 10, and an energy management system (hereinafter, referred to as EMS) 6, and can supply electric power to the load 10 of the power generation unit and other power receiving units 5 in the enterprise 3. In addition, when the power is insufficient, external power of a power company or the like is purchased.
On the other hand, the power receiving unit 5 is not provided with the power generation facility 9, and is configured by the load 10 and the EMS22, and power is supplied from external power of another power generating unit 5, the power company 2, and the like to the load 10 of the power receiving unit. When the power receiving unit 5 is a manufacturing plant, a manufacturing execution system (hereinafter referred to as MES) 8 that manages the production processes in the power receiving unit 5 is provided. MES8 will be described later.
Further, a regional energy management system (hereinafter referred to as AEMS) 7 is installed in the enterprise 3, and the self-consignment management between the power generation unit 4 and the power reception unit 5 in the enterprise 3 is performed. For the AEMS7, signal transmission is performed between the EMS6 provided in the power generation unit 4 and the EMS22 provided in the power reception unit 5 using a communication line.
Fig. 2 shows an example of a system configuration in the enterprise 3 according to the embodiment of the present invention. In addition, since the enterprise 3 includes a plurality of power generation units 4 (4 a to 4 n) and a plurality of power reception units 5 (5A to 5M), which have basically the same configuration, a specific configuration will be described below with the power generation unit 4a and the power reception unit 5A as a representative example.
The power generation unit 4a is provided with an EMS6a, and the power generation facility 9 is operated based on the self-consignment plan signal 100 from the AEMS 7.
On the other hand, the power receiving unit 5A in the present embodiment is a manufacturing plant. When the power receiving unit 5A is a manufacturing plant, the EMS22A performs energy management in the power receiving unit 5A, and in addition, a manufacturing execution system (hereinafter referred to as MES) 8A that manages production processes, a production schedule management function 11A that manages scheduling of production processes, and a production/self-consignment plan candidate display function 12A that displays candidates of production/self-consignment plans are provided.
The AEMS7 includes a demand prediction function 13 that evaluates the power demand of the entire enterprise 3, a production schedule adjustment function 14 that adjusts the production schedule of each power receiving unit 5, a self-consignment planning function 15 that generates a self-consignment plan of the entire enterprise, and a result output function 16 that outputs the result of the self-consignment.
Hereinafter, a self-consignment plan creation procedure will be described with reference to fig. 4 showing an example of a self-consignment plan creation flow. The self-consignment plan creation step is executed among the plurality of power receiving units 5 (5A to 5M), the plurality of power generating units 4 (4 a to 4 n), and the AEMS7, and is a flow of creating a self-consignment plan on the AEMS7 side based on the power demand prediction information presented on the power receiving units 5 (5A to 5M) and the power generating units 4 (4 a to 4 n) side, and determining whether or not the self-consignment plan can be accepted in the power receiving units 5 (5A to 5M).
First, processing steps S1 to S4 are executed on the power receiving unit 5 (5A to 5M) side, and the power demand prediction information to be presented to the AEMS7 side is specified.
Specifically, first, in processing step S1 in fig. 4, the MES8 of each power receiving unit 5 predicts the power consumption of each line from the existing results or by calculation. In step S2, the production schedule management function 11 classifies the power consumption of each production line into a fixed schedule, an undetermined schedule, and an adjustable schedule as shown in fig. 5 based on the information input in the MES8 in each power receiving unit 5.
Here, fig. 5 schematically shows the time changes of schedules 5AL1S, 5AL2S, … … ALPs and power demands 5AL1P, 5AL2P, … … ALPP of the production lines 5AL1, 5AL2, … … ALP provided in the power receiving unit 5A on the next day (scheduled day).
The line schedule 5AL1S of the line 5AL1 provided in the power receiving unit 5A is a line in which the scheduled operation time for specifying the next day (scheduled day) is 8 to 20 points, preparation for various materials, equipment, personnel, transportation procedures, and the like is completed, and the next day (scheduled day) should be operated as scheduled. The power demand in this case peaks between 10 and 15 points as in 5AL 1P. In this case, the line schedule 5AL1S is defined as a deterministic schedule.
The line schedule 5AL2S for the line 5AL2 of the power receiving unit 5A is in a state where the scheduled operation time on the first day of the day (scheduled day) is 10 to 18 points as shown by the solid line, but the scheduled start time Ts may be earlier than 10 points, and if the day of the day (scheduled day) is less than, the scheduled start time Ts cannot be specified. In the current planning stage today, for example, the time width dTu of 8 to 10 points is an undetermined time width, and in this case, the line schedule 5AL2S is defined as an undetermined schedule. When the schedule is not determined, the start and end times of the power demand variation pattern vary as indicated by the broken line in response to the possibility of job advancement with respect to the power demand 5AL2P on the next day (scheduled day).
The line scheduling 5ALPs for the line 5ALP of the power receiving unit 5A is in a state where the job schedule on the next day (scheduled day) is 9 to 18 points, but the job schedule can be moved to 11 to 20 points for operation because the job schedule is completed within the next day (scheduled day), for example. When the latter time period is selected, the scheduled start time Ts is moved by the adjustable time width dTc and operated. In this case, the line schedule 5ALPS is defined as an adjustable schedule.
In this way, in the processing step S2, the power consumption of each production line is defined and classified into any one of the fixed schedule, the undetermined schedule, and the adjustable schedule by the production schedule management function 11 based on the information input in the MES8.
Further, in the processing step S3, the production schedule management function 11 predicts an undetermined time width dTu for the undetermined schedule. For example, in the above description, the production line schedule 5AL2S which is an undetermined schedule advances the schedule of 10 points to 8 points, but a time other than 8 points is assumed as the scheduled start time Ts. Here, the production schedule management function 11 has an operator input function 17 or a machine learning function 18, as shown in fig. 3. The operator input function 17 outputs the result of estimating and inputting the undetermined time width dTu by the operator with reference to the supply chain information of the manufacturing plant and the database 19 relating to the past undetermined schedule to the EMS22. Alternatively, the machine learning function 18 refers to the database 19, calculates the undetermined time width dTu by machine learning, and inputs the result to the EMS22.
In step S4 of the process in fig. 4, the EMS22 of each power receiving unit 5 predicts the power demand including an error in each power receiving unit using the undetermined time width dTu as a parameter. If this is shown in the example of the power receiving unit 5A in fig. 5, the total power demand at each time is obtained for each of the power demands 5AL1P, 5AL2P, … … ALPP determined for the schedules 5AL1S, 5AL2S, … … 5ALPS of the production line. In this case, since the specified power and the unspecified power are present at each time, the total of the specified power and the total of the unspecified power are grasped in a divided manner. Since the undetermined time width dTu is used as a parameter, power demand prediction in a plurality of modes is performed. The portion corresponding to the sum of undetermined powers is an error in the power receiving unit.
In processing step S5 of fig. 4, AEMS7 calculates the power demand of the entire power receiving unit based on the power demand prediction information of the power receiving unit 5 reported from each power receiving unit 5 (5A to 5M).
Fig. 6 shows an example of a self-consignment plan created on the day before the scheduled day in the AEMS 7. The concept of the present invention will be described with reference to fig. 6. The self-consignment plan indicates the electric power (electric power transition) at each time of 24 hours on the next day (scheduled day), but P1 in the electric power characteristics shown here is a specific demand part of the electric power demand of the entire power receiving units calculated from the electric power demand prediction information reported from each power receiving unit 5 (5A to 5M). In all power receiving units (5A-5M), determination demand is evaluated from power at the time of scheduling in which a job is first scheduled in a scheduled schedule, and power at the time of scheduling in which a job is first scheduled in an adjustable schedule, and the determination demand portion P1 is calculated as a determination demand by summing up all the power receiving units. In addition, the power demand of the power generation unit is not included at this stage. In fig. 5, the total of the background-colored portions at each time corresponds to the determination demand P1.
The maximum demand P2 in consideration of the undetermined schedule of fig. 6 is obtained by adding the fluctuation amount of the undetermined demand to the determined demand P1 at each time. The maximum demand in consideration of the undetermined schedule is the result of power demand prediction for all cases including all cases where the undetermined time width dTu is a parameter and changed in all power receiving units.
However, in the case where the enterprise 3 in fig. 1 needs to satisfy the maximum demand P2 in consideration of the undetermined scheduling by the amount of power generation from the power generation units 4 (4 a to 4 n) and the external power of the power company 2 or the like, the external power of the power company 2 or the like is limited by the contract power P3 (the total of the contract powers of the power receiving units), and the power of the contract power P3 or more cannot be obtained from the power company 2. In fig. 6, the minimum self-consignment amount P4 is described in consideration of the difference between the undetermined scheduled maximum demand P2 (undetermined demand maximum value) and the contract power P3. Since power generation includes consumption of power demand by a power generation unit, the amount of power generation to satisfy the demand by a power reception unit is herein classified as "self-consignment amount".
The minimum self-consignment amount P4 shown in fig. 6 represents the minimum self-consignment amount in the idea that the power receiving unit 5 receives the same amount of external power as the contract power P3 of the power receiving unit and self-generates power to self-consignment shortage. In the present invention, a self-consignment plan is prepared and the self-consignment plan value from the power generation unit 4 is determined so as to be within the range of the determined demand P1 and the minimum self-consignment amount P4 at each time period. In this case, the generator operation plan of the power generation unit in step S7 is processed to optimize the operation plan so as to reduce the power generation cost by including the power demand of the entire power generation unit in the power demand of the entire power reception unit in fig. 6. In the optimization, the ratio of the amount of electricity purchased to the amount of self-generated electricity is determined in consideration of the cost of electricity generation and the like.
In step S14 of fig. 4, the total power demand of the entire company is determined by adding the total power demand of the power receiving unit determined in step S5 to the total power demand prediction result of the power generating unit evaluated in the EMS6 of the power generating unit 4.
In step S6 of fig. 4, the production schedule adjustment function 14 of the AEMS7 corrects the power demand section of the entire power receiving unit based on the adjustable time dTc of the adjustable schedule from each power receiving unit. As a result of changing the adjustable time dTc of the adjustable schedule, the relationship between the powers shown in fig. 6 is changed.
In processing step S7 of fig. 4, the self-consignment planning function 15 of the AEMS7 creates a plurality of operation plans for the power generation facilities in the entire power generation unit for the power demand of the entire enterprise obtained by summing the corrected power demand of the entire power receiving unit and the power demand of the entire power generation unit.
In the operation plan of the power generation facility in the processing step S8 in fig. 4, a plurality of operation plans are created under the constraint condition that the power purchased from the outside by each power generation unit and power reception unit is equal to or less than the contract power. If the restriction condition is not satisfied, readjustment of the adjustable schedule shown in processing step S6 is performed.
In step S9 of the process of fig. 4, a plurality of self-consignment plans are output from the AEMS7 to the EMS22 of each power receiving unit 5.
In processing step S10 of fig. 4, EMS22 and MES8 of each power receiving unit 5 present a plurality of self-consignment plans and a plurality of production scheduling plans to the operator for the self-consignment plan received from AEMS 7.
In processing step S11 in fig. 4, the operator of each power receiving unit 5 selects one plan from a plurality of plans. If the condition is not satisfied, the process returns to the processing step S6 of the AEMS7, and readjustment of the adjustable schedule is performed again to correct the power demand of the entire power receiving unit.
In processing step S12 of fig. 4, after the operators of all the power receiving units confirm the self-consignment plan and the production schedule plan, the MES8 outputs the production schedule.
Further, in step S13 of fig. 4, the AEMS7 outputs the power generation plan to all the power generation units.
Fig. 7 shows an example of the self-consignment plan and the actual results for all the power receiving units on the same day created in the AEMS 7. The operation plan for the self-consignment on the day is repeatedly performed at intervals of, for example, 30 minutes according to the procedure shown in fig. 4. Basically, the self-consignment amount from the power generation unit 4 to the power reception unit 5 is equal to or less than the demand amount of the power reception unit, and the difference is satisfied by purchasing external power. However, the demand may be lower than the self-consignment plan value due to an urgent change in the production plan of the power receiving unit 5. In this case, since unbalance occurs, if the unbalance cost is high, the operation cost may increase. Therefore, in the present embodiment, the demand on the current day and the self-consignment plan value are compared at each plan time (for example, 30 minutes), and if there is a possibility of imbalance, the operation plan is made so as to avoid imbalance using the adjustable time width dTc of the adjustable schedule shown in fig. 5 as a parameter.
In the above description of the embodiment, the representative adjustable demand side equipment classified as the adjustable schedule is the air conditioner, but even in this case, it is desirable to use the remaining capacity of the air conditioner on the premise that the comfort of the occupants is ensured to the minimum without classifying the entire capacity of the air conditioner as the adjustable schedule.
As described above, according to the method of the present invention, it is possible to provide an operation planning apparatus and method for making a self-consignment plan in consideration of uncertainty of a plurality of production schedules of a manufacturing plant in an enterprise including a plurality of power receiving units and a plurality of power generating units including the manufacturing plant, and further changing power demand by adjusting the production schedules, thereby maximizing the self-consignment amount while keeping the same amount while complying with the plan values, thereby reducing energy costs.
As described above, in the present invention, in the self-consignment plan on the day before the predetermined day, the respective production schedules of the power receiving unit are classified into the fixed schedule, the undetermined schedule, and the adjustable schedule on the basis of the variation information of the production schedule evaluated by the machine learning function of the operator or the actual performance information based on the supply chain, or the Manufacturing Execution System (MES) that monitors and manages the work of the production line and the worker, and the self-consignment plan is created on the basis of the undetermined schedule so as not to exceed the contract power in consideration of the maximum error of the power demand. A regional Energy Management System (AEMS) is provided, which compares the self-consignment plan value with the actual performance of the power demand when performing the self-consignment on the same day, changes the adjustable schedule so as not to generate imbalance, and presents a plurality of candidates for the production schedule and the self-consignment plan to the operator in each planning period.
Industrial applicability
The present invention can be applied to regional energy management of an enterprise constituted by a plurality of units constituted in a building, a factory, a university, or the like.
Description of the reference numerals
1: an electric power system; 2: an electric power company; 3: an enterprise; 4: a power generation unit; 5: a power receiving unit; 6: an Energy Management System (EMS) of the power generation unit; 7: a regional energy management system (AEMS); 8: a Manufacturing Execution System (MES); 9: a power generation device; 10: a load; 11: a production scheduling management function; 12: a production/self-consignment plan candidate display function; 13: a demand prediction function; 14: a production scheduling adjustment function; 15: a self-consignment plan function; 16: a result output function; 17: an operator input function; 18: a machine learning function; 19: a database; 22: energy Management System (EMS) of the power receiving unit.
Claims (15)
1. An energy management device in an enterprise having a power generation unit and a power reception unit connected to a power system,
EMS is installed in the power generating unit and the power receiving unit, AEMS is installed in the enterprise,
the EMS of the power receiving unit predicts the power transition of each production line of the power receiving unit on a predetermined day, classifies the operation schedule of the production line of the power receiving unit on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
the AEMS specifies a specified demand for a specified day and a maximum demand in consideration of the unspecified schedule from the operation schedule after classification of a predetermined day reported from the EMS of the power receiving unit and the power transition, specifies a minimum self-consignment amount obtained as a difference between the maximum demand and a contract power of the power receiving unit, and outputs a self-consignment plan to the power receiving unit within the range of the specified demand,
the EMS of the power generation unit generates power according to the self-consignment plan output determined by the AEMS.
2. The energy management device according to claim 1,
the AEMS adjusts the operation timing of the production line classified into the adjustable schedule when the minimum self-consignment sales volume cannot be specified and the self-consignment sales plan output to the power receiving unit within the range of the specified demand is output.
3. The energy management device according to claim 1,
the AEMS uses the undetermined schedule to make a plurality of self-consignment plan outputs,
the EMS of the power receiving unit outputs a confirmed self-consignment plan among the plurality of self-consignment plan outputs presented by the AEMS as a production schedule of the power receiving unit,
the AEMS provides the self-consignment plan output confirmed by the EMS of the power receiving unit to the EMS of the power generating unit as the self-consignment plan output determined by the AEMS.
4. The energy management device according to claim 1,
the AEMS compares the demand of the current day with the self-consignment plan output at regular scheduled intervals on the predetermined day, and if there is a possibility of imbalance, creates an operation plan so as to avoid imbalance using the adjustable time width of the adjustable schedule as a parameter.
5. An energy management method for an enterprise having a power generation unit and a power reception unit connected to a power system,
predicting the power transition of each production line of the power receiving unit on a predetermined day, classifying the operation schedule of the production line of the power receiving unit on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
determining a fixed demand for a predetermined day and a maximum demand in consideration of the non-fixed schedule based on the operation schedule after the classification of the predetermined day and the power transition, determining a minimum self-consignment amount obtained as a difference between the maximum demand and a contract power of the power receiving unit, and outputting the self-consignment plan to the power receiving unit within a range of the fixed demand,
the power generation unit generates power in accordance with the self-consignment plan output.
6. The energy management method according to claim 5,
and adjusting the operation timing of the production line classified into the adjustable schedule when the minimum self-consignment quantity cannot be determined and the self-consignment plan output to the power receiving unit is within the range of the determined demand.
7. The energy management method according to claim 5,
creating a plurality of said self-consignment plan outputs using said undetermined schedule,
the self-consignment plan output selected from the plurality of self-consignment plan outputs is used as the production schedule of the power receiving unit,
and determining the generated power of the generating unit according to the selected self-consignment plan output.
8. The energy management method according to claim 5,
on the predetermined day, the demand on the current day and the self-consignment plan output are compared at regular scheduled intervals, and if there is a possibility of imbalance, an operation plan is made so as to avoid imbalance using the adjustable time width of the adjustable schedule as a parameter.
9. An energy management system in an enterprise including a power generation unit and a power reception unit connected to a power grid, the energy management system comprising:
a demand variation factor specifying unit that specifies a demand variation factor in the energy demand prediction of the enterprise on a predetermined day;
a creating unit that evaluates a demand variation amount of a predetermined day based on the demand variation factor, and creates an energy production/purchase/transaction plan of the enterprise; and
a presentation unit that presents the plurality of plans related to the energy production/purchase/transaction plan created by the creation unit,
when predicting the energy demand of the enterprise, the scheduling generated by the energy demand is classified into determined scheduling, undetermined scheduling and adjustable scheduling, and the maximum error of the demand is evaluated according to the undetermined scheduling.
10. The energy management system of claim 9,
in the case of making the energy production/purchase/transaction plan, the adjustable schedule is changed to conform to the plan value.
11. The energy management system according to claim 9 or 10,
the on-demand devices and schedules that are adjustable in advance are registered as the adjustable schedule.
12. The energy management system of claim 11,
the demand side equipment capable of being adjusted in advance is air conditioning equipment, and is adjusted within the range of comfort.
13. An operation planning method for an energy management system in an enterprise including a power generation unit and a power reception unit connected to a power grid,
in the energy demand prediction of the enterprise on the scheduled day, the schedules generated due to the energy demand are classified into a fixed schedule, an undetermined schedule, and an adjustable schedule, and the adjustable schedule is changed to conform to a plan value in the case of making an energy production/purchase/transaction plan according to the maximum error of the undetermined schedule evaluation demand.
14. An energy management system in an enterprise including a power generation unit and a power reception unit connected to a power system,
the power receiving unit predicts the power transition of each production line on a predetermined day using information from the production schedule management function, classifies the operation schedule of the production line on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
the enterprise specifies a specified demand for a specified day and a maximum demand in consideration of the unspecified schedule on the basis of the classified operation schedule and the power transition for the specified day reported from the power receiving unit, specifies a minimum self-consignment amount obtained as a difference between the maximum demand and the power contract for the power receiving unit, and outputs a self-consignment plan to the power receiving unit within the specified demand,
the power generation unit generates power in accordance with the self-consignment plan output determined by the enterprise, and,
the production schedule management function has an operator input function of estimating and inputting a result of an undetermined time width as information from the production schedule management function with reference to supply chain information of a manufacturing plant and a database relating to past undetermined schedules, or a machine learning function of calculating an undetermined time width as information from the production schedule management function by machine learning with reference to a database.
15. An operation planning method for an energy management system in an enterprise including a power generation unit and a power reception unit connected to a power grid,
the power receiving unit predicts the power transition of each production line on a predetermined day using information from the production schedule management function, classifies the operation schedule of the production line on the predetermined day into a fixed schedule, an undetermined schedule, and an adjustable schedule,
the enterprise identifies a specified demand for a specified day and a maximum demand in consideration of the unspecified schedule, based on the classified operation schedule and the power transition for the specified day reported from the power receiving unit, identifies a minimum self-consignment amount obtained as a difference between the maximum demand and a contract power for the power receiving unit, and outputs a self-consignment plan to the power receiving unit within the range of the specified demand,
the power generation unit generates power in accordance with the self-consignment plan output determined by the enterprise, and,
the production schedule management function provides an undetermined time width estimated by an operator with reference to supply chain information of the manufacturing plant and a database relating to past undetermined schedules, or provides an undetermined time width calculated with reference to a database relating to past undetermined schedules.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/JP2017/021953 WO2018229895A1 (en) | 2017-06-14 | 2017-06-14 | Energy management device and method, energy management system, and energy management system operation planning method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110546842A CN110546842A (en) | 2019-12-06 |
| CN110546842B true CN110546842B (en) | 2023-01-03 |
Family
ID=64660587
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201780089900.XA Active CN110546842B (en) | 2017-06-14 | 2017-06-14 | Energy management device and method, energy management system, and operation planning method for energy management system |
Country Status (3)
| Country | Link |
|---|---|
| JP (1) | JP6893980B2 (en) |
| CN (1) | CN110546842B (en) |
| WO (1) | WO2018229895A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020256056A1 (en) * | 2019-06-19 | 2020-12-24 | 京セラ株式会社 | Self-consignment system, and self-consignment method |
| JP7229901B2 (en) * | 2019-11-27 | 2023-02-28 | 京セラ株式会社 | Self-consignment system and self-consignment method |
| CN112270458A (en) * | 2020-09-15 | 2021-01-26 | 广东韶钢松山股份有限公司 | Energy refined management and control method and device, computer equipment and storage medium |
| CN113346555B (en) * | 2021-05-25 | 2023-06-09 | 西安交通大学 | Daily rolling scheduling method considering electric quantity coordination |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4220007B2 (en) * | 1998-02-06 | 2009-02-04 | 東京電力株式会社 | Production scheduling device |
| JP2002123578A (en) * | 2000-08-10 | 2002-04-26 | Osaka Gas Co Ltd | Electric power retail system |
| JP3631967B2 (en) * | 2001-03-14 | 2005-03-23 | 株式会社エネット | Surplus power management system and control method thereof |
| JP2002345154A (en) * | 2001-05-18 | 2002-11-29 | Hitachi Ltd | Power demand and supply method, and display device |
| JP4050021B2 (en) * | 2001-07-21 | 2008-02-20 | 株式会社東芝 | Power consignment control system and power transaction method |
| JP2005210833A (en) * | 2004-01-22 | 2005-08-04 | Hitachi Ltd | Method for simultaneously and equally controlling consigned power |
| JP2005229657A (en) * | 2004-02-10 | 2005-08-25 | Fuji Electric Systems Co Ltd | Method for determining consignment electric energy |
| JP2005261056A (en) * | 2004-03-10 | 2005-09-22 | Toshiba Corp | Generation power controller of self-consignment system |
| JP2005278335A (en) * | 2004-03-25 | 2005-10-06 | Toshiba Corp | Support system for creating operation program of power consignment and support program for creating operation program of power consignment |
| JP2006081256A (en) * | 2004-09-08 | 2006-03-23 | Hitachi Ltd | Electrical energy sorting system and method |
| CN106463959B (en) * | 2014-05-19 | 2019-12-03 | 杰富意钢铁株式会社 | Power supply and demand guiding device and power supply and demand guidance method |
| JP6322588B2 (en) * | 2015-01-14 | 2018-05-09 | 株式会社日立製作所 | Community management system |
| CN105633949B (en) * | 2015-12-14 | 2018-07-24 | 云南电网有限责任公司电力科学研究院 | A kind of real-time power generation dispatching of economical operation and control method |
| CN105761109A (en) * | 2016-02-19 | 2016-07-13 | 刘隽琦 | Smart management system for energy management and electricity transaction in virtual power plant and method for optimizing operation thereof |
-
2017
- 2017-06-14 CN CN201780089900.XA patent/CN110546842B/en active Active
- 2017-06-14 JP JP2019524622A patent/JP6893980B2/en active Active
- 2017-06-14 WO PCT/JP2017/021953 patent/WO2018229895A1/en active Application Filing
Also Published As
| Publication number | Publication date |
|---|---|
| CN110546842A (en) | 2019-12-06 |
| JP6893980B2 (en) | 2021-06-23 |
| JPWO2018229895A1 (en) | 2019-12-19 |
| WO2018229895A1 (en) | 2018-12-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mohandes et al. | A review of power system flexibility with high penetration of renewables | |
| CN110546842B (en) | Energy management device and method, energy management system, and operation planning method for energy management system | |
| US11095152B2 (en) | Energy storage modeling and control | |
| EP3413421B1 (en) | Building energy optimization system with economic load demand response (eldr) optimization | |
| US7305282B2 (en) | Very short term load prediction in an energy management system | |
| US7454270B2 (en) | Dynamic economic dispatch for the management of a power distribution system | |
| US9335747B2 (en) | System and method for energy management | |
| US7689323B2 (en) | Automatic generation control of a power distribution system | |
| JP3631967B2 (en) | Surplus power management system and control method thereof | |
| Dababneh et al. | Integrated electricity and natural gas demand response for manufacturers in the smart grid | |
| JP2009284723A (en) | Power supply/demand controller and method of controlling power supply/demand | |
| EP3343720A1 (en) | Management server, management method, and management system | |
| US20180366951A1 (en) | Renewable power system and sizing method for controllable plant associated with renewable power system | |
| Schultz et al. | Method for an energy-oriented production control | |
| Rezaei et al. | A new stochastic gain adaptive energy management system for smart microgrids considering frequency responsive loads | |
| JP2021141778A (en) | Planning device, planning method, and computer program | |
| Chamana et al. | Buildings participation in resilience enhancement of community microgrids: Synergy between microgrid and building management systems | |
| Bartolucci et al. | Grid service potential from optimal sizing and scheduling the charging hub of a commercial Electric Vehicle fleet | |
| Roesch et al. | An approach towards a cost-based production control for energy flexibility | |
| US20030036937A1 (en) | Method for control and coordination of independent tasks using benders decomposition | |
| Heimgaertner et al. | A distributed control architecture for a loosely coupled virtual power plant | |
| KR102492456B1 (en) | Distributed resource brokerage trading platform device based on power generation forecasting | |
| EP3386059A1 (en) | Method and system for providing ancillary grid services | |
| JP4617290B2 (en) | Power generation planning system | |
| JP2005135266A (en) | Electric power transaction support system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |