EP4062509A1 - Plate-forme de commande permettant des échanges d'énergie entre une pluralité de systèmes d'énergie et système d'échange d'énergie - Google Patents

Plate-forme de commande permettant des échanges d'énergie entre une pluralité de systèmes d'énergie et système d'échange d'énergie

Info

Publication number
EP4062509A1
EP4062509A1 EP20815728.9A EP20815728A EP4062509A1 EP 4062509 A1 EP4062509 A1 EP 4062509A1 EP 20815728 A EP20815728 A EP 20815728A EP 4062509 A1 EP4062509 A1 EP 4062509A1
Authority
EP
European Patent Office
Prior art keywords
energy
control platform
exchanges
systems
solution
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.)
Pending
Application number
EP20815728.9A
Other languages
German (de)
English (en)
Inventor
Oliver DÖLLE
Stefan Niessen
Sebastian Schreck
Sebastian THIEM
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 EP4062509A1 publication Critical patent/EP4062509A1/fr
Pending legal-status Critical Current

Links

Classifications

    • 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
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • 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
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas 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
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • 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
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2639—Energy management, use maximum of cheap power, keep peak load low
    • 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
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS 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
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS 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
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

Definitions

  • Control platform for energy exchange between several energy systems as well as an energy exchange system
  • the invention relates to a method for operating a control platform according to the preamble of claim 1, a control platform according to the preamble of claim 9, a method for operating an energy exchange system according to the preamble of claim 10 and an energy exchange system according to the preamble of claim 10 Patent claim 11.
  • a local energy market enables energy systems to exchange and trade locally generated energy, in particular electrical energy (electricity). With its decentralized technical design, the local energy market enables the locally generated energy to be efficiently coordinated with the local energy consumption.
  • a local energy market is therefore particularly advantageous with regard to renewable energies, which are typically obtained locally.
  • the energy systems can be categorized into energy consumers (consumers), energy converters and prosumers, who both consume energy and provide or obtain it.
  • energy converters can colloquially be referred to as energy generators (generators), the term generation referring to the form of energy provided, for example electricity from electricity generators.
  • a local energy market is realized by a control platform, which can also be referred to as an energy market platform.
  • the control platform coordinates or controls the energy exchange between the energy systems based on offers that the energy systems transmit to the control platform in advance.
  • Such a control platform or local energy market is known, for example, from document EP 3518369 A1.
  • control platform For smaller energy systems, for example residential buildings, there are several challenges with regard to their integration into a local energy market.
  • the control platform must know in advance of an actual energy exchange what amount of energy an energy system is likely to consume and / or provide within a specified time range. In other words, a prediction of the energy exchange to be expected for the respective energy system is required.
  • the transmission of the envisaged energy exchange to the control platform typically takes place within the framework of offers.
  • Smaller energy systems typically have greater inaccuracies in their predictions.
  • a standard load and / or standard generation profile can be used, which typically represents a sufficiently good approximation.
  • these standard profiles are a significantly poorer approximation due to stochastic processes, for example switching on a vacuum cleaner. In other words, stochastic processes dominate the demand profile or load profile of smaller energy systems.
  • reserve energy which is provided, for example, by a power grid that is external to the local energy market.
  • the efficiency of the local energy market decreases, since either reserve energy is always provided
  • the energy that must and / or locally obtained energy is not consumed and therefore has to be temporarily stored and / or fed into the higher-level power grid.
  • the present invention is based on the object of providing a method for operating a control platform and a control platform that improves the efficiency of the associated local energy market with regard to uncertainties in the energy exchanges.
  • the object is achieved by a method with the features of independent patent claim 1, by a control platform with the features of independent patent claim 9, by a method for operating an energy exchange system with the features of independent patent claim 10 and by an energy exchange system with the features of independent claim 11.
  • the control platform receives at least one piece of information about an intended energy exchange from the energy systems for at least one time period Objective function optimal energy exchange between the energy systems calculated as a solution to an optimization process.
  • control platform receives information about several possible energy exchanges from at least one of the energy systems, each of these energy exchanges s being assigned a probability value ⁇ s, which is also received by the control platform; - An optimization process is carried out for each of the possible energy exchanges s received and an associated partial solution Z ( ⁇ s ) is thus calculated;
  • the energy exchange between the energy systems is controlled by the control platform based on the overall solution determined.
  • the method for operating a control platform according to the present invention and / or one of its configurations or one or more functions, features and / or steps of the method or its configurations can be computer-aided.
  • the concept of controlling includes regulating.
  • Energy can be provided by generating energy, for example by means of an energy converter, and / or by means of an energy store.
  • energy consumption encompasses any type of consumption of provided energy, in particular likewise energy storage.
  • a possible energy exchange is an amount of energy which is probable in the time domain and which has a certain probability, that is to say to which a probability value is assigned.
  • a possible energy exchange is characterized by a probability density function.
  • the probability value or the probability density function indicates how probable an energy exchange with a certain associated amount of energy is.
  • the probability value or the probability density function can be determined by means of statistical processes / methods and / or by means of historical data from historical or past energy exchanges.
  • An optimization method or an optimization within the meaning of the present invention is a method for minimizing or maximizing a target function.
  • the objective function is typically minimized or maximized numerically due to its complexity.
  • the objective function here characterizes one or more properties or variables of the system, for example the carbon dioxide emissions, the total amount of energy exchanged (volume) and / or the operating costs of one or more energy systems.
  • the objective function has parameters, in particular technical parameters of the energy systems, and variables.
  • the result of the optimization are the values of the variables that correspond to the amount of energy or power to be exchanged.
  • the solution to the optimization method thus at least identifies which amounts of energy are consumed and / or provided by which energy system within the time range.
  • the energy exchanges between the energy systems are the solution of the optimization process.
  • Power exchanges or services are used as equivalent to energy exchanges, since they represent the corresponding amount of energy in an integrated manner over a time range.
  • energy and power are equivalent and interchangeable with one another, since an associated energy or amount of energy always corresponds to a power in a time range.
  • the control platform receives the information about the envisaged exchange of energy from several energy systems for the time domain, for example for a coming day, for a coming hour or for the coming 15 minutes.
  • the energy systems (not necessarily each of the energy systems) communicate to the control platform what amount of energy it is likely to consume, in particular to store, and / or provide, in particular to save, within the time range. winnt. For example, this is done by means of a respective tuple, which identifies the maximum amount of energy that can be consumed, in particular storable, and / or provided, in particular recoverable, by the respective energy system and includes an associated fee.
  • a minimum fee is transmitted for provision, for example in the unit of euros per kilowatt hour, and a maximum fee for consumption, for example in the unit of euros per kilowatt hour.
  • each energy system - provided it participates in the energy exchange within the time range - transmits an offer for a maximum amount of energy for a minimum price when it is provided or for a maximum price when it is consumed.
  • the offer thus includes the technical information of the respective maximum amount of energy to be exchanged. If continuous or quasi-continuous operation is sought, the information mentioned for each time range / time step is transmitted from the energy systems to the control platform and received by it.
  • the probability value ⁇ s associated with the energy exchange is also transmitted to and received by the control platform.
  • a probability distribution discretrete or continuous as a density function
  • the information is in the form of probability-energy-quantity tuples marked.
  • P t , n , k denotes the power of the energy system k at the network node n at time t or within the associated time range.
  • the respective data field identifies the probability ⁇ s that the power exchanged within the time range is less than or equal to P s max . that is, the amount of energy exchanged within the time range T is less than or equal to P s max. T is.
  • an optimization method is carried out for each of the possible energy exchanges s received, and an associated partial solution Z ( ⁇ s ) is thus calculated.
  • the calculation of the several partial solutions can take place in parallel or in series.
  • the partial solutions are assigned to the respective probability value ⁇ s , so that the partial solutions are dependent on this.
  • Each partial solution Z ( ⁇ s ) characterizes the most optimal possible energy exchange between the energy systems, if one of the energy systems had only transmitted the possible energy exchange s as the envisaged energy exchange.
  • an overall solution is determined or calculated from the several partial solutions. The calculation is made depending on the probability values ⁇ s .
  • Z * is determined by a marked change in the function curve Z ( ⁇ s ) or Z ( ⁇ ).
  • the actual energy exchanges between the energy systems are determined by the overall solution.
  • the control platform according to the invention now controls the energy exchange between the energy systems based on or in accordance with the determined overall solution.
  • the concept of control is to be interpreted broadly.
  • every measure of the control platform which in principle has at least one direct or indirect partial effect on the actual energy exchange, should be understood as control by the control platform.
  • the energy exchanges are carried out by a data signal that includes control data and by the control platform to the respective energy systems is transmitted, controlled.
  • the data signal is used, for example, to switch on, switch on, switch off and / or change the operation of technical energy systems in the energy systems, whereby the actual direct operational control of the systems can be left to the energy system and / or an energy management system of the energy system.
  • the signal from the control platform only forms the trigger for the operational processes mentioned, which then ultimately lead to the exchange of energy, that is to say to the provision of energy and / or to energy consumption.
  • the signal from the control platform is a price signal, that is to say a data signal which characterizes a cost-effective provision and / or a cost-effective consumption. For example, provision is cost-effective if more energy is to be consumed locally than is provided locally.
  • a local block-type thermal power station is switched on by the price signal.
  • Local consumption is particularly cost-effective when more energy is provided locally than is consumed locally. For example, if there is increased photovoltaic power generation in the afternoon.
  • the energy efficiency of the local energy market is also improved by the price signal, since the local provision of energy and its local consumption can be better matched and thus less reserve energy has to be provided and / or used.
  • the uncertainties for an envisaged energy exchange that is to say for an energy supply and / or an energy consumption, are thus taken into account during the optimization by the control platform.
  • the technically best possible and objective overall solution with regard to the uncertainties can be determined.
  • the uncertainties or the associated probabilities are viewed as a whole, so that they can be symbolically leveraged against each other.
  • This holistic view reduces the uncertainty reduced within the entire local energy market. This means that less reserve power has to be made available to compensate, so that energy supply and energy consumption can be more efficiently matched. In other words, differences that occur in the energy balance between the energy systems are recognized a priori by the control platform and can thus be reduced. Furthermore, the optimization and thus the solution can be designed so robustly that even in the worst case, sufficient reserve energy / reserve power is provided. Reserve capacities can be better estimated and used more efficiently.
  • Another advantage of the present invention is that the expansion of renewable energies, in particular their local expansion, is promoted.
  • the expansion of energy stores, in particular electrochemical energy stores, for example battery stores, can also be promoted here. These provide flexibility and stabilize the local energy market, which typically largely comprises volatile energy sources. This relieves the load on the higher-level power grid, since the local provision of energy and its local consumption can be better coordinated.
  • the control platform according to the invention for controlling energy exchanges between several energy systems, whereby at least one piece of information about an intended energy exchange can be received from the energy systems for at least one time range through the control platform, and through the control platform optimal energy exchanges between the energy systems with regard to a target function Energy systems are calculable as a solution to an optimization process, is characterized in that
  • each of these energy exchange s is assigned a probability value ⁇ s which can also be received by the control platform;
  • an optimization process can be carried out by the control platform for each of the possible energy exchanges s received, and an associated partial solution Z ( ⁇ s ) can thus be calculated;
  • the overall solution from the several partial solutions Z ( s ) can be calculated by the control platform as a function of their probability values ⁇ s;
  • the energy exchange between the energy systems can be controlled by the control platform based on the overall solution determined.
  • the control platform is designed to carry out the features mentioned, such as receiving the data and / or calculating the partial solutions and the overall solution by means of the optimization method.
  • the method according to the invention for operating an energy exchange system which comprises several energy systems and a control platform, the energy systems each transmitting information about at least one envisaged energy exchange to the control platform for at least one time range, and in which the The control platform calculates optimal energy exchanges between the energy systems as a solution to an optimization method with regard to a target function, is characterized in that
  • At least one of the energy systems transmits information about several possible energy exchanges s to the control platform, each of these energy exchanges s being assigned a probability value ⁇ s, which is also transmitted to the control platform; - an optimization process is carried out for each of the transmitted possible energy exchanges s and an associated partial solution Z ( ⁇ s ) is thus determined;
  • the energy exchange between the energy systems is controlled by the control platform based on the overall solution determined.
  • the method for operating an energy exchange system according to the present invention and / or one of its configurations or one or more functions, features and / or steps of the method and / or its configurations can be computer-aided.
  • the energy exchange system comprising several energy systems and a control platform, the energy systems and the control platform being designed in such a way that information about at least one intended energy exchange can be transmitted to the control platform by the energy systems for at least one time range, and by means of the control platform -
  • optimal energy exchanges between the energy systems can be calculated as a solution to an optimization method, is characterized in that
  • At least one of the energy systems can transmit information about several possible energy exchanges s to the control platform, each of these energy exchanges s being assigned a probability value ⁇ s , which can also be transmitted to the control platform;
  • the overall solution from the several partial solutions Z ( s ) can be calculated by the control platform as a function of their probability values ⁇ s;
  • the energy exchange between the energy systems can be controlled by the control platform based on the overall solution determined.
  • the energy exchange system according to the invention is designed to carry out the features mentioned, such as, for example, receiving the data and / or calculating the partial solutions and the overall solution by means of the optimization method.
  • the energy exchange system according to the invention forms a local energy market according to the invention.
  • the energy exchanges are controlled by means of the control platform by transmitting respective control data to the respective energy system.
  • control data By transmitting the control data, the respective energy technology systems within the energy systems can advantageously be controlled, in particular started up, switched on and / or switched off.
  • the control of several systems of an energy system is provided.
  • the term “control” and “control data” is to be interpreted broadly. Every data record that, after it has been received by the respective energy system, has a direct or indirect partial effect on the operation of the respective energy system, in particular its energy-related systems, is encompassed by the concept of control data.
  • the energy systems are advantageously designed to receive and process the control data from the control platform.
  • the energy systems particularly preferably include a respective energy management system.
  • the control data can preferably include a price signal, in particular encode.
  • information about a maximum amount of energy to be consumed is received from the energy system by the control platform for an envisaged energy consumption of one of the energy systems.
  • the at least one energy system transmits information about the maximum amount of energy to be consumed by the energy system to the control platform.
  • the amount of energy transmitted is intended for consumption.
  • the energy systems which in particular do not transmit any possible energy exchanges and want to consume a certain amount of energy within the time range, transmit at least a maximum amount of energy to be consumed. If this maximum amount of energy to be consumed is combined with information about a maximum fee, a purchase offer for the maximum amount of energy to be consumed is transmitted to the control platform.
  • a basic buy offer (English: buy order) is through the information or fixed, where the maxi- male remuneration at time t, at node n, of the energy system.
  • the energy system (s) that transmit possible energy exchanges to the control platform transmit the information for all s, N tnk.
  • information about a maximum amount of information to be provided is used for an envisaged supply of energy from one of the energy systems Amount of energy received from the energy system by the control platform.
  • the at least one energy system transmits information about the maximum amount of energy to be provided by the energy system to the control platform.
  • the amount of energy transmitted is intended for provision.
  • the energy systems which in particular do not transmit any possible energy exchanges and want to provide a certain amount of energy within the time range, transmit at least a maximum amount of energy that can be provided. If this maximum amount of energy to be provided is combined with information about a minimum fee, a sales offer for the maximum amount of energy to be provided is transmitted to the control platform.
  • a basic sale offer (English: rope order) is through the values / information respectively determined, with the minimum wage at time t, on Identifies node n, of the energy system. That or the energy systems that transmit possible energy exchanges to the control platform transmit the information
  • the control platform therefore preferably has the information received, where the index B an energy consumption and the index S indicates an energy supply.
  • control platform Further information, in particular technical information / parameters specific to the energy system, can be received by the control platform from the energy systems.
  • the overall solution from the several partial solutions Z ( s ) becomes neighboring due to the maximum with respect to the probability values ⁇ s Gradients of the partial solutions Z ( ⁇ s ) of the possible energy exchanges s calculated.
  • the probability values are arranged in ascending order, that is, for ⁇ s , ⁇ s-1 and ⁇ s + 1 are adjacent. the Edge points ⁇ 1 and ⁇ N only have an adjacent probability value or are excluded from the stated determination.
  • a particularly advantageous individual objective function z ( ⁇ s ), which is associated with a possible energy exchange s, is through set. This provides s objective functions z, or if ⁇ R is continuous, a function z (z) is provided. For every value ⁇ s and thus for every possible energy exchange s, the present objective function z ( ⁇ s ) is maximized, that is, the values of the variables are determined in such a way that z ( ⁇ s ) has a maximum Has objective function value Z ( ⁇ s ). In other words, each partial solution is Z ( ⁇ s ) by its associated objective function value
  • secondary conditions are typically taken into account.
  • the respective objective function is preferably maximized under the secondary conditions and whereby and, as mentioned above, by the respective Energy system transmitted to the control platform and received by it.
  • T ⁇ T t .
  • a possible energy exchange s can also be referred to as a scenario, so that the above optimization problem is solved for all scenarios.
  • a total solution is then determined from the calculated partial solutions.
  • the overall solution is an advantageous compromise / balance between the total amount of energy exchanged between the energy systems (trading volume) and the risk or the probability of the scenario (scenario probability ⁇ s ).
  • the overall solution is preferred for each objective function value or each partial solution Z ( ⁇ s ) of an associated scenario s or possible energy exchange s determined, it being possible for an additional weighting factor k to be provided in addition.
  • k 1.
  • the objective function value or the scenario probability that is to say the probability value of a possible energy exchange, can be weighted more strongly by means of the weighting factor k. For example, an overall solution that is as robust as possible with a smaller target function value can be determined in this way. This is particularly advantageous if the energy exchange system or the local energy market is to be operated with the lowest possible risk, that is to say with the smallest possible uncertainty with regard to the energy exchange.
  • the overall solution is calculated by calculating the difference in absolute value between neighboring partial solutions
  • the partial solutions are sampled, for example according to their function curve Z ( ⁇ s ).
  • Z ( ⁇ s ) Typically there is a transition area within which further Z ( ⁇ s ) become significantly worse than a previous value.
  • the gradient has
  • the threshold value typically has the dimension of trading volume per probability value / scenario probability.
  • the trading volume can have the unit kilowatt hours or euros.
  • the probability values are dimensionless and have a numerical value between 0 and 1 or between 0 percent and 100 percent.
  • the threshold value or the gradient mentioned above can be easily interpreted.
  • the threshold value can be set manually as a function of an existing risk assessment, for example based on later empirical values, existing conditions for the higher-level network, etc., and a willingness to take risks.
  • the threshold value can change as a function of time, that is to say a new threshold value can be defined dynamically. In particular, this is dependent on a consistency of previous predicted and / or used probability values.
  • the optimization problem could be designed using two objective functions.
  • a first objective function could model the total amount of energy exchanged and the second objective function the scenario probability, that is to say the respective probability values. It is intended to maximize both objective functions.
  • Known numerical solvers in particular Gurobi TM, can be used to solve the optimization problem, that is to say to calculate the partial solutions.
  • control platform determines the reserve capacities required for the energy exchanges based on the overall solution.
  • an improved estimate of the required reserve energy or the required reserve capacities can be made.
  • This advantageously improves the energy efficiency of a local energy market that includes the control platform.
  • differences in the energy balance that lead to corresponding reserve capacities are recognized in advance of the actual energy exchanges and can thus be reduced to the lowest possible level in a technically controllable manner.
  • network bottlenecks are anticipated and reduced.
  • FIG. 1 shows a probabilistic forecast for a photovoltaic system
  • FIG. 2 is a graphic representation of a calculation of an overall solution.
  • FIG. 1 shows an exemplary probabilistic prediction for a photovoltaic system, according to which possible energy exchanges and associated probability values can be determined and / or provided. After their determination and / or provision, they can be transmitted by the associated energy system, which in the present case includes the photovoltaic system, to a control platform in accordance with the present and / or one of its configurations.
  • the hours of one day, for example the next day (day-ahead trading), are plotted on the abscissa 200.
  • the power provided by the photovoltaic system is plotted in watts on ordinate 201.
  • a probabilistic forecast is calculated for every hour of the day.
  • the probability values can be continuous, so that a probability density function of the possible energy exchanges is transmitted to the control platform and received by it for every hour of the day.
  • the time range can be less than an hour, in particular 15 minutes.
  • the actual course of the power provided by the photovoltaic system over the course of the day is identified by the reference symbol 202. It can be seen here that there are significant deviations from the expected course or with regard to the probability distribution, particularly in the areas of sunrise and sunset.
  • An optimal overall solution is then calculated or determined from this function. This is clearly illustrated by FIG.
  • FIG. 2 shows a graphic representation of a calculation or a determination of an overall solution 142 from the partial solutions, which in their entirety form a function 140 as a function of the probability or as a function of the probability values.
  • the probability of a possible energy exchange is plotted on the abscissa 100.
  • the value of the respective partial solution associated with the probability value is plotted on the ordinate 101 in any dimension and unit.
  • the totality of the partial solutions forms a function depending on the probability, the course of which with the Reference numeral 140 is identified.
  • the probability or the probability value for a possible energy exchange can also be referred to as the scenario probability, since possible energy exchanges represent a respective scenario.
  • the scenario probability is thus plotted in percent on the abscissa 100.
  • curve 140 shows that a high-risk overall solution 144 can be determined which, although it has an advantageous, comparatively high objective function value (value of the associated partial solution), but a comparatively high risk. This is the case because the probability of the energy exchange occurring is essentially 0%.
  • a robust or low-risk overall solution 146 can be determined which, although it has a high probability, of almost 100% in the present case, has a non-advantageous and comparatively low target function value. It should be noted here that, with regard to optimization, the maximum possible target function value is advantageous, since this characterizes the exchanged energy volume, for example.
  • the target function can be supplemented by a weighted combination of total carbon dioxide emissions, primary energy use and / or the operating costs, which are typically to be minimized.
  • a minimization can always be converted into a maximization by changing the sign of the objective function.
  • the greatest possible target function value is advantageous.
  • the compromise solution 142 that is to say the optimal overall solution 142, has an associated probability value of 42%.
  • a marked increase can be be characterized by a significant change in adjacent gradients of function 140.
  • the overall solution 142 determined or calculated according to the present invention is thus the best possible compromise or balance between the high-risk overall solution 144 and the low-risk overall solution 146 operated with a low risk of failure or operational risk.

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Abstract

L'invention concerne un procédé de fonctionnement d'une plate-forme de commande qui permet des échanges d'énergie entre une pluralité de systèmes d'énergie, des informations concernant un échange d'énergie souhaité étant reçues par la plate-forme de commande en provenance des systèmes d'énergie dans chaque cas pour au moins un intervalle de temps, et la plate-forme de commande calculant des échanges d'énergie entre les systèmes d'énergie qui sont optimaux en ce qui concerne une fonction cible en tant que solution à un procédé d'optimisation, la plate-forme de commande recevant des informations en provenance d'au moins un système de la pluralité de systèmes d'énergie concernant une pluralité d'échanges d'énergie possibles s, une valeur de probabilité ζ s , qui est également reçue par la plate-forme de commande, étant attribuée à chacun de ces échanges d'énergie s ; pour chacun des échanges d'énergie possibles reçus s, un procédé d'optimisation est mis en œuvre et une solution partielle associée Ζ(ζ s ) est ainsi calculée ; la solution totale (142) est calculée à partir de la pluralité de solutions partielles Ζ(ζ s ) en fonction des valeurs de probabilité ζ s correspondantes ; les échanges d'énergie entre les systèmes d'énergie sont commandés par la plate-forme de commande sur la base de la solution totale déterminée (142). De plus, l'invention concerne une plate-forme de commande, un système d'échange d'énergie et un procédé de fonctionnement d'un tel système d'échange d'énergie.
EP20815728.9A 2020-03-05 2020-11-06 Plate-forme de commande permettant des échanges d'énergie entre une pluralité de systèmes d'énergie et système d'échange d'énergie Pending EP4062509A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP20161156.3A EP3876376A1 (fr) 2020-03-05 2020-03-05 Plateforme de commande pour l'échange d'énergie entre plusieurs systèmes d'énergie ainsi que système d'échange d'énergie
PCT/EP2020/081334 WO2021175463A1 (fr) 2020-03-05 2020-11-06 Plate-forme de commande permettant des échanges d'énergie entre une pluralité de systèmes d'énergie et système d'échange d'énergie

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EP4062509A1 true EP4062509A1 (fr) 2022-09-28

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EP20161156.3A Withdrawn EP3876376A1 (fr) 2020-03-05 2020-03-05 Plateforme de commande pour l'échange d'énergie entre plusieurs systèmes d'énergie ainsi que système d'échange d'énergie
EP20815728.9A Pending EP4062509A1 (fr) 2020-03-05 2020-11-06 Plate-forme de commande permettant des échanges d'énergie entre une pluralité de systèmes d'énergie et système d'échange d'énergie

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EP20161156.3A Withdrawn EP3876376A1 (fr) 2020-03-05 2020-03-05 Plateforme de commande pour l'échange d'énergie entre plusieurs systèmes d'énergie ainsi que système d'échange d'énergie

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US (1) US20230093272A1 (fr)
EP (2) EP3876376A1 (fr)
KR (1) KR20220146636A (fr)
CN (1) CN115244813A (fr)
AU (1) AU2020433707B2 (fr)
WO (1) WO2021175463A1 (fr)

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1263108A1 (fr) * 2001-06-01 2002-12-04 Roke Manor Research Limited Système de gestion d'énergie pour une communauté
US20070124026A1 (en) * 2005-11-30 2007-05-31 Alternative Energy Systems Consulting, Inc. Agent Based Auction System and Method for Allocating Distributed Energy Resources
US9148019B2 (en) * 2010-12-06 2015-09-29 Sandia Corporation Computing architecture for autonomous microgrids
DE102013214996A1 (de) * 2013-07-31 2014-07-31 Siemens Aktiengesellschaft Vorrichtung zur Lastverschiebung in intelligenten Stromverteilungsnetzen und ein entsprechendes System
US10211638B2 (en) * 2013-09-30 2019-02-19 Board Of Regents, The University Of Texas System Power quality of service optimization for microgrids
TW201820246A (zh) * 2016-11-23 2018-06-01 財團法人資訊工業策進會 取得用電戶之負載運作機率之方法及取得用電戶群組之負載運作機率之方法
EP3518369A1 (fr) 2018-01-30 2019-07-31 Siemens Aktiengesellschaft Méthode et dispositif pour contrôler le transfert de puissance électrique et réseau électrique
CN110648006A (zh) * 2018-06-26 2020-01-03 南京理工大学 一种考虑风光相关性的日前优化调度方法
WO2020014006A1 (fr) * 2018-07-13 2020-01-16 Siemens Aktiengesellschaft Réduction photovoltaïque dynamique pour distribution d'énergie électrique

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KR20220146636A (ko) 2022-11-01
US20230093272A1 (en) 2023-03-23
EP3876376A1 (fr) 2021-09-08
AU2020433707B2 (en) 2023-10-12
CN115244813A (zh) 2022-10-25
WO2021175463A1 (fr) 2021-09-10
AU2020433707A1 (en) 2022-09-01

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