EP3682387A1 - Commande de micro-réseaux - Google Patents

Commande de micro-réseaux

Info

Publication number
EP3682387A1
EP3682387A1 EP17816464.6A EP17816464A EP3682387A1 EP 3682387 A1 EP3682387 A1 EP 3682387A1 EP 17816464 A EP17816464 A EP 17816464A EP 3682387 A1 EP3682387 A1 EP 3682387A1
Authority
EP
European Patent Office
Prior art keywords
time interval
optimization
control
control method
withdrawal
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.)
Withdrawn
Application number
EP17816464.6A
Other languages
German (de)
English (en)
Inventor
Martin SEYDENSCHWANZ
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Siemens AG
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 Siemens AG filed Critical Siemens AG
Publication of EP3682387A1 publication Critical patent/EP3682387A1/fr
Withdrawn legal-status Critical Current

Links

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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/021—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a variable is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G06Q30/0202—Market predictions or forecasting for commercial activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • 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
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/10—The dispersed energy generation being of fossil origin, e.g. diesel generators
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • Y—GENERAL 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00—Climate change mitigation technologies for sector-wide applications
    • Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
    • Y02P80/14—District level solutions, i.e. local energy networks

Definitions

  • the present invention relates to the control of electrical network arrangements rule or microgrids.
  • a control method, a controller, and a network arrangement will be described.
  • microgrids can provide local electrical power, and are also operable without connection to the power grid or main grid.
  • a microgrid typically includes components such as one or more power generators and one or more power storage devices controlled by a common controller.
  • Microgrid control techniques based on MILP are described, for example, in "Optimization of On-site Renewable Energy Generation for Industrial Sites"; S. Ruangpattana, D. Klabjan, J. Arinez, and S. Biller's IEEE Power Systems Conference and Exposure, 2011. An optimization approach is provided that anticipates the components of the microgrid in a relatively short time span.
  • the network arrangement comprises one or more electrical power generators and one or more power storage, and is controllably connected to the power supply to a main network or connectable.
  • Fer ner is defined a current withdrawal quota, which is provided for removal by the network assembly from the main network in a withdrawal time interval.
  • the control method comprises determining, based on the current consumption contingently, one or more optimization conditions for a control time interval that is less than the extraction time interval.
  • the method also includes performing optimization of an optimization quantity based on the one or more optimization conditions for the control time interval based on magazines having a step size smaller than the control time interval, and driving the network arrangement based on the results of the optimization ,
  • the long-term removal from the main grid is already taken into account in the short-term planning, whereby inefficiencies and costs can be avoided or reduced.
  • the terms network arrangement and microgrid are used synonymously.
  • a time interval may also be referred to as a period or section or a duration.
  • the optimization can be a predictive optimization over the control time interval, such as using a MILP procedure.
  • the optimization can be calculated efficiently and time scales of typical changes, for example with regard to the load and / or the power generation, can be taken into account.
  • the optimization can be performed rolling and / or repeated Runaway leads.
  • the optimization may be repetitively repeated at certain intervals, such as daily or every 12 hours, and / or rolling such that after every N processed or expired magazines a new optimization is performed with a N time-shifted control time interval, where N in particular 1 can be.
  • the control time interval can be kept constant bezüg Lich its width, or the width can be geän changed. In this way, it is possible to react to short-term changes in operating conditions, such as a change in the weather, suddenly increased power demand, or failure of a component.
  • the one or more optimization conditions may be based on a demand acceptance for the control time interval and / or the extraction time interval.
  • the acceptance of presumptions can be used as the basis for a proactive optimization.
  • An acceptance of requirements can, in particular, depict a time course of an anticipated removal in the control time interval and / or in the withdrawal time interval, for example as cumulative amount of electricity taken or energy withdrawn, or as absolute withdrawal, for example per journal.
  • the current withdrawal quota may be within an acceptance interval.
  • the optimization can be designed to keep the current consumption over the sampling time interval in this acceptance interval, or at least to minimize or minimize the interval or to optimize it, possibly taking into account other conditions of opting, inefficiency or costs.
  • the acceptance interval may indicate a lower and upper limit of a current amount that may be taken. Is the menu ge of electricity, which is taken within the withdrawal period within the acceptance interval, the condition that the current contingent can be found, considered to be satisfied who the. In particular, further costs or inefficiencies can then be avoided, for example according to contractual arrangements.
  • a demand acceptance may be provided and / or determined based on the acceptance interval in an acceptance strip, which may be related to a control time interval. There may be multi-level acceptance intervals and / or acceptance strips, for example when costs are multi-level.
  • the optimization can be a cost optimization.
  • Costs can be financial or economic costs or be parameterized as such.
  • costs may be, for example, or related to energy, power, power, power dissipation, energy loss, current loss, time loss or delay, or the like.
  • the withdrawal time interval may be at least 2 weeks, or 3 or 4 weeks, or at least or exactly 14 days, or at least or exactly 20 days, or at least or exactly 30 or 31 days, or one month.
  • Such an interval allows long-term planning for both a main network operator and the operator of the microgrid, which in particular ensures long-term stable operation of the main network.
  • Bilateral energy contracts that provide a contingent of electricity therefore usually concern a corresponding withdrawal time interval.
  • the control interval may be 48 hours or less, or 24 hours or less, or 12 hours or less. Such an interval may, for example, be adapted to a battery charging cycle, and / or to a consumption cycle, and / or a generator cycle. It may be provided that the step size is 1/12 or less of the control interval, about 1/20 or less, or 1/24 or less. In some cases, the step size may be 15min or more, 30min or more, 45min or more, 60min or more,
  • control device for an electrical network arrangement, wherein the control device is designed to perform a control method as described herein be and / or control.
  • a control device may generally be formed as an integrated circuit, and / or comprise an integrated circuit.
  • An integrated circuit may be designed as a processing circuit or processor circuit, and / or one or more processors and / or controllers and / or processor cores and / or ASICs (Application Specific Integrated
  • Memory or storage medium may include volatile or non-volatile memory, such as random access memory (RAM) and / or read-only memory (ROM) and / or flash memory and / or optical memory and / or magnetic memory, etc.
  • RAM random access memory
  • ROM read-only memory
  • flash memory / or optical memory and / or magnetic memory, etc.
  • a controller can be used as a computer or computer arrangement or
  • Controller assembly may be formed, which may have one or more re integrated circuits.
  • the controller may include one or more interfaces for controlling the microgrid and / or components of the microgrid, and / or for receiving information regarding, for example, operating conditions and / or conditions of the components.
  • the controller may be centralized or distributed, for example, to multiple computers of a computer system.
  • electrical network arrangement which comprises a control device described herein.
  • the invention can be implemented as a computer program.
  • the program may include instructions that cause a controller on which they are executed to execute and / or control a method described herein.
  • a storage media combination which may include one or more storage and / or carrier media may Save computer program.
  • a storage medium and / or carrier medium may be designed to store and / or transport instructions and / or data.
  • a computer program can be formed as a control tool or control tool.
  • FIG. 1 shows an electrical network arrangement according to the invention
  • FIG. 2 shows a method according to the invention
  • FIG. 3 shows an exemplary removal time interval
  • FIG. 4 shows an exemplary control time interval
  • FIG. 5 shows an exemplary sampling time interval in which a control time interval is embedded.
  • Figure 1 shows an inventive electrical network assembly 10, which is also referred to as microgrid.
  • the network arrangement 10 includes one or more power generators 12, 14. Ein
  • the network assembly 10 further includes one or more memory or memory devices 16.
  • a memory device may be generally configured to receive power, such as in the form of electrical current. increase and store and, if A memory device which gives off electricity or energy can also act as a generator. Examples of storage devices include batteries, fuel cells, Pumpspei cher, heat storage, etc. Different producers may be of different types, analog may be different storage devices of different types.
  • the compo nents of the network system 10 may be generally separately controlled and operable, about independently and be switched on and off.
  • the network assembly 10 may further include one or more consumers 18, and / or be connected to this or be connected, such as the power supply.
  • a controller 20 may be connected to the individual compo th to control this.
  • the controller 20 may be configured to drive the components 12, 14, 16 and other components based on a common control method.
  • the electric network arrangement 10 can be regarded as an independently operable power network which can be connected or connectable to a main power network or main network 100, for example in accordance with the control device 20.
  • the network arrangement 10 can be used to store power and / or to remove power be connected to the main network 100 or connectable.
  • the main network can be, for example, the public power grid, and / or a network with a considerably larger capacity than the network arrangement 10, for example at least 10 times or at least 100 times or at least 1000 times greater capacity. Capacitance can be represented as in peak power or continuous power or maximum storage capacity or peak current.
  • electrical arrangements may be provided, such as Transforma gates and / or converters and / or capacitors and / or
  • Main network 100 and network arrangement 10 may have different operators.
  • a power contingent El can be defined, which is the exception for the network arrangement 10 from the main network 100 via a withdrawal time interval TI may be provided, such as one month, for example, on the basis of a bilateral contract between
  • Controller 20 may be configured to perform the control methods described herein.
  • FIG. 2 shows schematically a flow chart of a control method according to the invention, which can be designed as an algorithm.
  • the method may comprise determining a current allocation El and / or withdrawal time interval TI and / or acceptance interval and / or a demand assumption, for example based on an input.
  • the method includes an act S10 of determining one or more optimization conditions based on the
  • the method further comprises the act S12 of performing optimization of an optimization quantity based on the one or more optimization conditions for the control time interval T2 based on magazines having a step size T3.
  • T3 is smaller than T2.
  • the optimization method may in particular comprise a MILP method, which may preferably be carried out iteratively, rolling or preferably iteratively, repeatedly or rolling.
  • the method includes driving the network arrangement based on the optimization as action S14, such as for times according to the magazines.
  • the actions may be performed by associated modules, such as program modules, which may be part of a computer program.
  • the driving may occur at times that are determined based on the magazines. For example, for each step, the associated step size may be added to a sum of step sizes of the previous steps and an initial value or output time, and the driving may be performed at the specific time.
  • Optimization conditions may generally be parameters or quantities, and / or conditions on quantities, and / or equations and / or inequalities and / or mathematical expressions considered and / or used in the optimization.
  • An optimizer size may be a size that is to be optimized by the optimization, such as minimized or maximized.
  • An optimization variable can also be referred to as a target variable.
  • An optimization quantity may be represented or defined by an expression and / or a formula or equation or parameters, and / or based on one or more optimization conditions, and / or limited by one or more optimization conditions.
  • a control variable may be a variable that is controlled or regulated by the method, directly or indirectly. Control variables may in particular be the current delivery or absorption or performance of one or more components be, and / or in particular the removal from the main network.
  • power may be considered as electrical or electrical energy.
  • a quantity of current can be parameterized as current time times, or energy or power times time.
  • a contingent may generally represent a quantity of electricity related to a particular time period, such as the withdrawal time interval.
  • the term "long-term” may refer to the sampling time interval, the term “short-term” to the control time interval.
  • a withdrawal time interval can be a contract time horizon or contract period, a control time interval, in particular, a planning period or planning horizon.
  • a quantity of energy Y to be taken corresponding to the quota El, during the contract period Tmax, corresponding to the withdrawal time interval TI, at a fixed price cO per kWh agreed.
  • tolerance levels such as deviations down, that is, less energy is taken off, and up, that is, more energy is lost in which to continue
  • the tolerance levels represent an acceptance interval.
  • the following parameters should describe these tolerance levels q t : Permissible negative deviation (in percent) of the agreed amount of energy in the entire contract period Tmax q u : Permissible positive deviation (in percent) of the agreed amount of energy in the entire contract period Tmax
  • Tmax applies to the actual cumulative energy consumption Z at the end of the contract period
  • optimization for a microgrid may, in some variants, have a prediction time space or preview horizon T, corresponding to the control time interval T2, from a few hours to a day.
  • a tag is a typical cycle length for battery deployment planning. Forecasts for the availability of renewable energy sources and the required power generation by other producers in Microgrid can become more uncertain for longer planning horizons.
  • the running times of the planning programs increase with the length of the planning horizon. For example, MILP-based control tools can be rebuilt on a rolling basis and have limited time to deliver results due to scheduling in operation. correspond In addition, too long a runtime can affect the control at the time step level.
  • Grid connection is the described planning horizon T of the control tool so much smaller. Accordingly ent stands the problem, the energy contract, which refers only to the cumulative energy withdrawal at the end of the contract period, in the rolling control of the microgrid on the shorter time horizon
  • an estimate as a function of the time for the expected cumulative Energyentnah me y (t) in the sampling time interval can be provided, for example for the period [0, Tmax] or [Tstart, Tstart + Tmax], where Tstart may be eit Vietnamese a start Z, about a beginning of the month.
  • Tstart may be eit Vietnamese a start Z, about a beginning of the month.
  • profiles of requirements can be derived accepted from historical data, which can represent et wa factors influencing the energy withdrawal, approximately with respect to the microgrid or one or more compo nents (nits peak load Z, work / holidays, etc.).
  • FIG. 3 shows an exemplary demand assumption with acceptance strips for a sample month with 30 days as long-term planning.
  • days of a month and in the vertical direction a cumulated energy consumption are indicated.
  • An example is an energy demand estimate for a month and the associated
  • a program or method of optimization may be implemented based on these parameters.
  • an iterative MILP-based approach to integrating bi lateral energy contracts (or other long-term power contingents) into programs for predictive, rolling, cost-effective control of microgrids can be used.
  • the step size or duration of the intervals may be the same for all time steps, or vary.
  • N may be 12 or more, 24 or more, 48 or more, 72 or more.
  • t n start of the time interval n, instead of the start of the interval another reference point can also be selected, such as the middle of the interval;
  • Idi IJN indicator variable that indicates whether the tatsumbleli ⁇ che cumulative energy consumption lower than the
  • the energy consumption represents the withdrawal from the main network.
  • the energy consumption represents the total energy or power consumption of the microgrid, taking into account the removal from the main grid.
  • different cost levels for the overrun and / or underrun can be provided, for example, each increase after exceeding an upper or lower limit for the removal.
  • MILP mixed-integer linear program
  • This program is controlled by the power points P ⁇ t n ) of the mains connection.
  • the objective function (1) is
  • FIG. 5 shows how short-term planning relates to the long-term planning of FIG. 3.
  • FIG. 5 in the horizontal direction, for example, days of a month and in the vertical direction a cumulative energy consumption are indicated.
  • Figure 4 areas are marked records in which the acceptance strip in some time overwriting or falls below.
  • a rolling planning with regular re-optimization can be carried out. This is supported by the approach, for example by shifting the planning horizon / control time interval and / or transfer of the current system state, eg the previous accumulated energy consumption zO in the contract horizon.
  • long-term quotas for example from bilateral energy in-depth, short-term control tools for
  • Microgrids are integrated.
  • the short-term, rolling planning with slowly growing / shifted planning horizon is much more accurate than a prior planning of the entire contract horizon.
  • the inventive approach can be easily integrated into existing and future MILP-based programs for controlling microgrids.
  • the invention complements MILP-based programs for the cost-effective control of microgrids and is very well suited for complex, but time-critical applications with planning optimization at runtime.
  • the invention proposes to consider long-term conditions and / or costs by mapping them to short-term planning horizons by short-term cost approximations and corresponding conditions.

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Abstract

L'invention concerne un procédé de commande pour un agencement de réseau électrique (10), qui comprend un ou plusieurs générateurs de courant électrique (12, 14) et un ou plusieurs accumulateurs d'électricité (16). L'agencement de réseau (10) est ou peut être connecté de manière commandée à un réseau principal (100) pour le prélèvement de courant. Un contingent de prélèvement de courant (E1) est défini, lequel est prévu pour le prélèvement du réseau principal (100) par l'agencement de réseau (10) durant un intervalle de temps de prélèvement (T1). Le procédé de commande comprend la détermination d'une ou plusieurs conditions d'optimisation sur la base du contingent de prélèvement de courant (E1) pour un intervalle de temps de commande (T2), lequel est inférieur à l'intervalle de temps de prélèvement (T1) ainsi que la réalisation d'une optimisation d'une grandeur d'optimisation sur la base de l'une ou plusieurs conditions d'optimisation pour l'intervalle de temps de commande (T2) sur la base d'incréments de temps avec une largeur (T3) qui est inférieure à (T2). Le procédé comprend en outre la commande de l'agencement de réseau sur la base de l'optimisation. L'invention concerne également un procédé et des dispositifs correspondants.
EP17816464.6A 2017-11-20 2017-11-20 Commande de micro-réseaux Withdrawn EP3682387A1 (fr)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/EP2017/079780 WO2019096424A1 (fr) 2017-11-20 2017-11-20 Commande de micro-réseaux

Publications (1)

Publication Number Publication Date
EP3682387A1 true EP3682387A1 (fr) 2020-07-22

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EP17816464.6A Withdrawn EP3682387A1 (fr) 2017-11-20 2017-11-20 Commande de micro-réseaux

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US (1) US20210175717A1 (fr)
EP (1) EP3682387A1 (fr)
CN (1) CN111344724A (fr)
WO (1) WO2019096424A1 (fr)

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DE102022118176A1 (de) 2022-07-20 2024-01-25 Rolls-Royce Solutions GmbH Verfahren zum Betreiben eines Leistungsbereitstellungsnetzwerks, Steuervorrichtung zur Durchführung eines solchen Verfahrens und Leistungsbereitstellungsnetzwerk mit einer solchen Steuervorrichtung

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US8812338B2 (en) * 2008-04-29 2014-08-19 Sas Institute Inc. Computer-implemented systems and methods for pack optimization
US8200373B2 (en) * 2009-04-23 2012-06-12 Pentair Water Pool And Spa, Inc. Energy production and consumption matching system
US8178997B2 (en) * 2009-06-15 2012-05-15 Google Inc. Supplying grid ancillary services using controllable loads
CN102810186A (zh) * 2012-08-01 2012-12-05 江苏省电力设计院 多时间尺度微网能量优化管理体系结构及其方法
US9489701B2 (en) * 2012-11-06 2016-11-08 Ali Emadi Adaptive energy management system
US9651929B2 (en) * 2014-09-29 2017-05-16 International Business Machines Corporation HVAC system control integrated with demand response, on-site energy storage system and on-site energy generation system

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WO2019096424A1 (fr) 2019-05-23
CN111344724A (zh) 2020-06-26
US20210175717A1 (en) 2021-06-10

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