Method and device for operating a battery storage device within a renewable energy community
Patent Information
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- SIEMENS AG
- Filing Date
- 2024-06-26
- Publication Date
- 2026-04-15
AI Technical Summary
In renewable energy communities, the storage of gray electricity within battery storage systems reduces the capacity for green electricity, limiting flexibility and economic viability, as gray electricity cannot be traded within the community and incurs higher feed-in tariffs when discharged into the grid.
A method and control unit that optimize battery storage by dividing its capacity into separate partial capacities for green and gray electricity, with the gray electricity portion being minimized through discharge limits and reserve requirements, ensuring maximum flexibility and efficient use of green energy.
This approach maximizes the share of green electricity in battery storage, enhancing flexibility within the renewable energy community, preventing curtailment of renewable energy, and allowing for sustainable operation by minimizing gray electricity's impact, thus improving local integration and network services.
Smart Images
Figure EP2024067889_16012025_PF_FP_ABST
Abstract
Description
[0001]202312301 1 Description Method and device for operating a battery storage system within a renewable energy community. The invention relates to a method according to the preamble of patent claim 1, a control unit according to the preamble of patent claim 11, and a renewable energy community according to the preamble of patent claim 13. Renewable energy communities (also: renewable energy communities) are a network of several energy systems, for example of private households and / or small to medium-sized enterprises, which exchange renewable energy, in particular renewable electricity, within the network. The energy systems of the renewable energy communities can thus generate energy from renewable sources, consume, store, and / or sell the self-generated energy.The basic idea of a renewable energy community is that its energy systems may only exchange electricity generated from renewable sources (green electricity) with each other. Non-renewable electricity (grey electricity), which, for example, was obtained from a grid higher than the renewable energy community, may only be used by the community itself or fed into the grid. Within a renewable energy community, a distinction must therefore be made between green electricity and grey electricity. A renewable energy community typically comprises several energy systems with energy-related assets, which can be divided into generators, storage facilities, non-controllable loads, and controllable loads. The renewable energy community is designed to control the exchange of electricity between the participating energy systems using a central control unit for the energy systems.In other words, the controllable systems of the renewable energy community are centrally controlled by the control unit. Battery storage systems are of particular importance for the operation of a renewable energy community. Since only green electricity may be exchanged within the renewable energy community, it is necessary to label the origin of the electrical energy stored in battery storage systems. In other words, a distinction must also be made between green electricity and gray electricity for the stored electrical energy. The gray electricity component within a battery storage system cannot be used by the renewable energy community. Furthermore, reduced grid tariffs and statutory exemptions from energy-related taxes typically only apply to locally generated green electricity.Furthermore, it is typically not economical to discharge the gray power from the battery storage system into the power grid, as the feed-in tariff is usually significantly lower than the procurement costs – consisting of the energy price, grid fee, and taxes. Thus, the gray power portion of the battery storage system can typically only be used to cover the individual participant's own needs, i.e., for their own use. The disadvantage here is that stored gray power blocks a certain portion of the battery storage system's total capacity for green power. In principle, it is advantageous for the renewable energy community if the green power portion within the battery storage system is as high as possible, as this provides flexibility within the renewable energy community.In particular, an amount of gray power could accumulate in the battery storage units over a longer period of time, thus continuously blocking an ever-increasing portion of the aforementioned flexibility. At the same time, however, a certain amount of gray power, for example, reserved to cover the individual user's own needs, can be advantageous, for example, as a reserve for periods in which lower renewable generation is available. The present invention is based on the object of resolving the above-mentioned technical conflict between the storage of green power and the storage of gray power within the framework of a renewable energy community.The object is achieved by a method having the features of independent patent claim 1, by a control unit having the features of independent patent claim 11, and by a renewable energy community having the features of independent patent claim 14. Advantageous embodiments and further developments of the invention are specified in the dependent patent claims.The method according to the invention for operating a battery storage system within a renewable energy community, wherein the renewable energy community comprises a plurality of energy systems which are designed to exchange green electricity with one another and to use grey electricity themselves and / or to provide it for energy systems external to the renewable energy community, wherein a control unit is used to control the battery storage system, which control unit is designed to calculate target values for charging power and / or discharging power of the battery storage system based on a computer-aided optimization method, wherein the battery storage system is controlled by the control unit in accordance with the calculated target values, is characterized in that in the optimization method the total capacity ^^ of the battery storage system is divided into a first and a second partial capacity ^^. ^,௧ , ^^ ଶ,௧ is divided, with the first partial capacity ^^^,௧ for green electricity and the second partial capacity ^^ ଶ,௧ is intended for grey electricity, and the second partial capacity ^^ ଶ,௧ at 202312301 4 optimization procedures by a threshold value ^^ ଶ,୪୧୫୧^,் limited by discharging within a time range ^^ taking into account a specified discharge power limit ^^ ୫ୟ^ and a specified minimum second partial capacity ^^ ଶ,^ The method according to the invention and / or one or more functions, features and / or steps of the method according to the invention and / or one of its embodiments can be computer-aided. According to the invention, capacities and charge states are considered equivalent. For example, within the optimization method, instead of the first and second partial capacities ^^ ^,௧ , ^^ ଶ,௧ the respective charge level SoC ^,௧ ൌ ^^ ^,௧ / ^^, SoC ଶ,௧ ൌ ^^ ଶ,௧ / ^^ can be used, where ^^ denotes the total capacity of the battery storage system. In particular, it is therefore not necessary for the sum of the first and second partial capacities to be equal to the total capacity. It is initially only necessary to ensure, for example via a secondary condition, that the sum of the partial capacities is less than or equal to the total capacity. This means equivalently that the sum of the states of charge is less than or equal to the overall state of charge. A renewable energy community typically comprises several energy systems, for example households, office buildings, industrial plants and / or public institutions, for example schools and / or universities, which are only permitted to exchange electricity generated internally from renewable sources (green electricity) with each other with regard to the renewable energy community.Renewable energy communities can thus jointly use self-generated renewable energy, i.e., generate, consume, store, and / or sell it. From a structural perspective, the IPCC Fifth Assessment Report, in particular, defines an energy system as: "All components related to the production, conversion, delivery, and use of energy" (Annex I, page 1261). Energy systems typically comprise several components, particularly energy-related systems, such as energy conversion systems, consumption systems, and / or storage systems. Energy systems can, in principle, generate and / or provide multiple forms of energy.The energy systems may include one or more of the following components: power generators, combined heat and power plants, in particular combined heat and power plants, gas boilers, diesel generators, heat pumps, charging stations for electric vehicles, compression chillers, absorption chillers, pumps, district heating networks, energy transfer lines, wind turbines or wind power plants, photovoltaic systems, battery storage systems, biomass plants, biogas plants, waste incineration plants, industrial plants, conventional power plants, and / or the like. Within the Renewable Energy Community, green electricity is electricity generated from renewable sources, for example, by photovoltaic systems. Green electricity is used by the generating energy system itself or provided for other energy systems within the Renewable Energy Community. In other words, green electricity is exchanged within the Renewable Energy Community.In particular, green electricity is not provided by a producer external to the renewable energy community, but by the energy systems (participants) of the renewable energy community itself, whose primary task is not energy generation. Grey electricity is electricity generated from non-renewable sources or from a mix of renewable and non-renewable sources, the share of which from renewable and non-renewable sources is typically unknown, and which is primarily sourced from producers outside the renewable energy community. 202312301 6 Grey electricity is typically provided by conventional power plants and transported to consumers via a public electricity grid.To control the energy exchanges or electricity exchanges within the renewable energy community, a central control of the energy exchanges with respect to the renewable energy community is required, which is implemented by the control unit provided according to the invention. The control unit is at least designed to control the battery storage system using setpoint values for charging power or discharging power. In this case, indirect or direct control can be provided. For example, the battery storage system has a local control unit that directly controls or regulates the battery storage system. The central control unit then transmits the calculated setpoint values to the local control unit, which implements or adjusts them accordingly. This creates indirect control of the battery storage system by the central control unit.Furthermore, the control unit can form a central aggregation unit for the renewable energy community. A computer-aided optimization method within the meaning of the present invention is a method for minimizing or maximizing an objective function. The minimization or maximization of the objective function is typically extremely complex and can therefore only be carried out numerically, i.e., with computer support. The objective function characterizes a property or a technical variable of the renewable energy community, for example, carbon dioxide emissions or total costs. Typically, no exact minimum or maximum of the objective function is achieved; rather, it is sufficient to approximate it, for example, by setting a threshold value (termination condition). The optimization method calculates the target values required for control.The target values form the variables of the objective function, which are determined by minimizing or maximizing their numerical values. Thus, for the method according to the invention, any possible objective function can be used that includes the charging and / or discharging powers of the battery storage system as variables. Furthermore, optimization is typically performed taking several constraints into account. Constraints, boundary conditions, or constraints—referred to collectively as constraints—are typically technical and / or physical conditions, properties, and / or relations that parameters and / or variables of the optimization process must fulfill. These can be given as an equation and / or inequality, and / or explicitly describe a set of permissible values of parameters and / or permissible values of variables.According to the present invention, the total capacity of the battery storage system is divided into a first and a second partial capacity within the optimization method. The division into the two partial capacities is virtual, meaning that the optimization method comprises two variables with regard to the partial capacities: one for green power and one for gray power. The first partial capacity is intended for green power and the second partial capacity for gray power. In other words, the first partial capacity indicates the green power component and the second partial capacity indicates the gray power component within the battery storage system. 202312301 8 Fundamentally, there is a physically compelling dependency between the changes in the partial capacities and the corresponding charging and / or discharging power of the battery storage system, with green power and gray power each having their own charging and discharging power.In other words, the charging and discharging powers are linked to the partial capacities, so that the constraints imposed by the method on the second partial capacity have a direct impact on the charging and discharging powers, respectively, which are calculated as target values. According to the invention, at least one constraint for the second partial capacity is provided within the optimization method, namely that the second partial capacity is limited during the optimization method by a threshold value that can be maximally achieved by discharging within a time range, taking into account a specified discharge power limit and a specified minimum second partial capacity. This constraint or constraint has a direct impact on the calculated target values of the charging and discharging powers.The secondary condition provided by the invention ensures that the gray power component within the battery storage is as small as possible, but that a certain minimum portion of the gray power, characterized by the specified minimum second partial capacity, remains stored within the battery storage, for example, as a reserve. This requires that, within the time range, for example, at the end of each day, the gray power is removed from the battery and the corresponding electrical energy is fed into the electrical grid if the gray power itself cannot be used. Furthermore, the condition according to the invention technically ensures that the gray power component is as small as possible, i.e., minimized as far as technically possible. This 202312301 9 technical limit is characterized by the specified discharge power limit.In other words, the battery storage system can only be discharged at maximum power within the specified time range, and thus only a minimum gray power share, which can in principle also be zero, can be achieved. If the technically achievable gray power share in the aforementioned sense is above the specified minimum second partial capacity, the second partial capacity is determined by this. If the technically achievable gray power share is below the specified minimum second partial capacity, a smaller gray power share can in principle be achieved, but this is not sensible in terms of a reserve, so that in this case the second partial capacity is limited by the value of the minimum second partial capacity. In principle, however, such a gray power reserve can be dispensed with and the minimum second partial capacity can be set to zero.In summary, the condition required by the invention for the second partial capacity technically ensures that the proportion of gray electricity within the battery storage system is minimized as far as technically possible and technically sensible. This ensures that the proportion of green electricity is blocked as little as possible by gray electricity, so that more flexibility can be provided and used within the renewable energy community. Thus, an origin-based partitioning of the battery storage system takes place in synergistic use of another secondary condition (storage boundary condition) within the optimization process or the optimization model, in which a maximum storage fill level of the two partial capacities is defined within the time range, in particular within 202312301 10 regular time intervals.The invention has the following particular advantages: - Greater flexibility for renewable energy in the renewable energy community is enabled, since the existing flexibility of battery storage systems is not blocked by stored gray electricity that may not be traded within the community. - The flexibility provided can achieve improved local integration of energy from renewable sources and prevent the curtailment of renewable energies. The method according to the invention thus contributes to more sustainable operation of the renewable energy community. - The green electricity partition (first partial capacity) could be characterized as "loss-free" as an additional benefit for the energy community, for example, by using gray electricity for the storage losses.This would allow all locally generated green electricity to be used again within the renewable energy community at a later time. Losses would then be covered by the gray electricity share that would not need to be stored. - Through controlled storage of gray electricity in the expansions and feeding it into the electrical grid, expensive and CO2-intensive generators could be displaced, taking into account carbon footprints and the price of the electricity mix. This addresses the ecological and economic components of sustainable operation of energy systems. - Through greater flexibility, the renewable energy community can provide better and more effective grid services, such as peak shaving. This can reduce the expansion of grid infrastructure and the associated CO2 footprint, and increase sustainability.202312301 11 The control unit according to the invention for operating a battery storage system within a renewable energy community, wherein the renewable energy community comprises a plurality of energy systems which are designed to exchange green electricity with one another and to use grey electricity themselves and / or to provide it for energy systems external to the renewable energy community, is designed to calculate target values for charging power and / or discharging power of the battery storage system based on a computer-aided optimization method and to control the battery storage system in accordance with the calculated target values. The control unit according to the invention is characterized in that it is designed to divide the total capacity of the battery storage system into a first and second partial capacity ^^ during the optimization method. ^,௧ , ^^ ଶ,௧ to be divided, whereby the first partial capacity ^^ ^,௧for green electricity and the second partial capacity ^^ ଶ,௧ is intended for grey electricity, and the second partial capacity ^^ ଶ,௧ in the optimization process by a threshold value ^^ ଶ,୪୧୫୧^,் limited by discharging within a time range ^^ taking into account a specified discharge power limit ^^ ୫ୟ^ and a specified minimum second partial capacity ^^ ଶ,^is maximum achievable. The control unit according to the invention can comprise a correspondingly designed and configured computing unit for carrying out the numerical optimization method or the optimization. This results in similar, equivalent and equivalent advantages and / or embodiments of the control unit according to the invention for the method according to the invention. The renewable energy community according to the invention comprises a plurality of energy systems which are designed to exchange green electricity with one another, as well as to use gray electricity themselves and / or to provide it for energy systems external to the renewable energy community, and is 202312301 12 characterized in that the renewable energy community comprises a control unit according to the present invention and / or one of its embodiments.The method according to the invention and the control unit according to the invention result in similar, equivalent, and equivalent advantages and / or configurations of the renewable energy community according to the invention. According to an advantageous configuration of the invention, the constraint ^^ is taken into account in the optimization method. ଶ,௧^ ^ ^^ ଶ,୪୧୫୧^,் with ^^ ଶ,୪୧୫୧^,் ൌ max ^ ^^ ଶ,୫୧୬,௧^ , ^^ ଶ,^ ^ used, where ൌ ^^ ଶ,௧^ െ ^^ ∙ ^^ ୫ୟ^ and ^^ ൌ ^ ^^ ^ , ^^ ^ ^ In other words, the optimization procedure uses the constraint ^^ ଶ,௧^ ^max ^ ^^ ଶ,୫୧୬,௧^ , ^^ ଶ,^ ^ used, where ൌ ^^ ଶ,௧^ െ ^^ ∙ ^^ ୫ୟ^ is and ^^ ଶ,௧^ the second partial capacity at the start of discharge and ^^ ଶ,௧^the second partial capacity at the end of the discharge. Equivalently, the constraint SoCଶ,௧^ ^ SoCଶ,୪୧୫୧^,் withSoCଶ,୪୧୫୧^,் ൌ max ^SoCଶ,୫୧୬,௧^ , SoCଶ,^^ is used, where SoCଶ,୫୧୬,௧^ ൌ SoCଶ,௧^ െ^^ ∙ ^^ ୫ୟ^ / ^^ is and SoC ଶ,௧^ the second state of charge at the start of discharging the battery storage and SoC ଶ,௧^ the second state of charge at the end of the battery storage discharge. In other words, the condition required for the second partial capacity according to the invention will be considered a constraint in the optimization process. Here, the constraint ^^ ଶ,௧^ ^max ensure that the technical conditions (maximum discharge power ^^ ୫ୟ^ and minimal gray current share ^^ ଶ,^) are taken into account and no technically impossible or unfavorable gray power component (second partial capacity) is calculated. If the technically maximum achievable minimum second state of charge ^^ଶ,୫୧୬,௧^ is smaller than the specified minimum state of charge SoCଶ,^ for the gray power, then during optimization SoCଶ,௧^ ^ 202312301 13 SoC ଶ,^ required. If the technically maximum achievable minimum second state of charge is greater than the specified minimum state of charge SoC ଶ,^ for the gray current, the optimization SoC ଶ,௧^ ^ ^^ ଶ,୫୧୬,௧^ required. In an advantageous development of the invention, the discharge power limit ^^ ୫ୟ^by a system-specific maximum power of the battery storage system or by a maximum power of a grid connection point of the renewable energy community. In other words, the discharge power limit, i.e., the maximum discharge power that can be used to discharge the battery storage system, in particular the gray power, can be limited by the battery storage system or by the grid connection point of the renewable energy community. In this case, the power at the grid connection point, which is typically also virtual, refers to the power aggregated across the renewable energy community.For example, if discharging the battery storage system at its maximum permissible discharge power would result in a violation of the operating limits of the renewable energy community, such as the power aggregated at the grid connection, the battery storage system will not be discharged at its maximum discharge power, but rather at the still permissible power that does not result in a violation of the operating limits at the grid connection point of the renewable energy community. If, however, the operating limits at the grid connection point are not violated, discharging can occur at the maximum permissible discharge power for the battery storage system. In principle, the maximum discharge power for discharging the battery storage system can differ from the maximum permissible charging power of the battery storage system.202312301 14 According to an advantageous embodiment of the invention, the specified time range ^^ comprises one or more time steps of the optimization method. Typically, discrete time steps are used for the temporal dependencies. In other words, the time range covered by the optimization method is divided into discrete time steps for the numerical solution of the optimization problem. For example, a day is divided into hourly or 15-minute time steps. Thus, the specified time range provided for discharging the gray current comprises one or more of the aforementioned time steps. Thus, for example, ^^ ൌ ^^. ^ െ ^^ ^ an integer multiple of ∆ ^^, where ∆ ^^ denotes the time steps or the time step size. In an advantageous development of the invention, the discharge power limit ^^ ୫ୟ^by an average power of maximum discharge powers dependent on the time step. In other words, ൌ ∑ ௧∈் ^^ ୫ୟ^,௧ / ^^, where ^^ denotes the number of time-dependent discharge powers or the number of time steps considered. Thus, in particular This additionally ensures a grid-friendly and controlled withdrawal of the gray power without violating the operating limits of the Renewable Energy Community. According to an advantageous embodiment of the invention, the specified time range covers only the last time step of the optimization process. As a result, the gray power is advantageously discharged only in the last time step of the time range considered in the optimization process. For example, the gray power is discharged in the last simulation step of each day, typically in the evening or at night. Advantageously, however, the minimum limit ^^ provided by the invention ଶ,^A minimal residual amount of gray power is always stored within the battery storage system, which can be used as a reserve, especially in the evening hours. Nevertheless, the invention still provides sufficient flexibility. In an advantageous development of the invention, losses during the storage of green power are compensated for by the gray power stored using the second partial capacity. In other words, loss-free storage or intermediate storage of green power within the renewable energy community is made possible, with the losses that always occur when storing a quantity of electricity being covered by the stored gray power. For this reason, too, it is advantageous to always have a fixed minimum proportion of gray power stored.In other words, when the green electricity is withdrawn from storage, an amount of energy corresponding to the withdrawal losses is withdrawn from the gray electricity partition, so that in the end, the entire original amount of green electricity can be made available to one or more users (energy systems) within the renewable energy community. Furthermore, control by the control unit could enable the conversion of green electricity to gray electricity. This is advantageous, for example, if surplus electricity from one or more photovoltaic systems cannot be used by the participant (energy system) itself or in the renewable energy community. This shifts energy in the already fully charged battery from the virtual gray electricity partition to the green electricity partition to the same extent, provided that gray electricity is stored in the battery at that time.In other words, in this case, green power is temporarily stored in the battery and gray power is fed back into the grid. 202312301 16 If at this point in time there is less energy in the virtual gray power partition than was converted from the green power category to gray power, all of the energy in the gray power partition is shifted to the green power partition, and the remaining green power can then be fed back into the grid as green power. This advantageous method prevents simultaneous, lossy storage of green power and withdrawal of gray power. According to an advantageous embodiment of the invention, the battery storage system is modeled during the optimization method such that the respective efficiencies ^^ are used to calculate the target values for the charging power and / or discharging power. ୡ୦ , ^^ ^ୡ୦In other words, battery storage systems typically have different efficiencies for their charging and discharging. Advantageously, these different efficiencies are then also taken into account in the optimization process. In an advantageous development of the invention, the constraints ൌ ^^ ୡ୦ used, where ^^ ୡ୦ ^ / ଶ,௧ the target values of the charging power for the first and second partial capacity and ^^ ^ୡ୦ ^ / ଶ,௧ denotes the target values of the discharge power for the first and second partial capacity. Advantageously, this also takes into account the possibly different efficiencies for charging and discharging the battery storage system. Here, ^^ ^^ ^ / ଶ,௧ / ^^ ^^ the temporal change of the respective partial capacity, which is caused by a charge ( ^^ ୡ୦ ∙ ^^ ୡ୦ ^ / ଶ,௧ ) or unload ( ^^^ୡ୦ ^ / ଶ,௧ / ^^ ^ୡ୦ ) of the battery storage. Constraint represents the physical coupling between the target values for the 202312301 17 charging powers ( ) and discharge capacities ( ) is safe. If discrete time steps are used for the numerical solution of the optimization problem, then the constraint or ^^ ∙ ^SoC all ^^ of the considered optimization period are used.In the case that the discrete constraint ^^ ∙ ^SoC^ / ଶ,௧ െ is used, the discrete condition SoC ଶ,௧^ ^ max ^SoC ଶ,୫୧୬,௧^ , SoC ଶ,^ ^ used, where According to an advantageous embodiment of the invention, the time range is defined such that the second partial capacity is discharged when the electricity mix underlying the Renewable Energy Community has a CO2 footprint above an emissions threshold. In other words, taking into account the current CO2 footprint of the electricity mix, withdrawal is postponed to a time with high CO2 emissions, thus displacing CO2-intensive producers. Withdrawal at a time with low CO2 emissions, on the other hand, could disadvantageously result in electricity from renewable sources having to be curtailed. For this purpose, for example, information about the CO2 intensity of the electricity mix can be converted into an internal price, which flows into the objective function of the optimization problem.Furthermore, taking into account the current electricity price, storage can be postponed to a time with high prices, thus displacing producers with high electricity generation costs. This can also contribute to balancing electricity price peaks. For this purpose, information about the current electricity price can be converted into an internal price, which flows into the objective function of the optimization problem. 202312301 18 In an advantageous development of the invention, the control unit is designed to control further energy-related systems within the renewable energy community. In other words, the control unit advantageously forms a central control unit with respect to the renewable energy community.In this case, it controls not only the battery storage system, but also other energy-related systems of the renewable energy community, in particular generators, for example photovoltaic systems, and / or controllable loads, for example heat pumps. According to an advantageous embodiment of the invention, the control unit is designed to control the electricity exchanges between the energy systems of the renewable energy community. As a result, the control unit advantageously forms a central control unit or control device for all electricity exchanges between the energy systems of the renewable energy community. In an advantageous development of the invention, the control unit is further designed to control the electricity exchanges between the energy systems in such a way that only green electricity is exchanged between the energy systems.This advantageously ensures that only green electricity, i.e., no gray electricity, is exchanged among the energy systems of the renewable energy community. Further advantages, features, and details of the invention emerge from the exemplary embodiments described below and from the drawing. The figure schematically shows a model (participant model) of a renewable energy community with at least one battery storage system. Similar, equivalent, or equivalently effective elements can be provided with the same reference numerals in the figure. The figure shows a so-called participant model of a renewable energy community 1, which illustrates the fundamental dependencies regarding electricity exchanges. Possible electricity exchanges or energy exchanges are marked with arrows in the figure.A control unit that controls the aforementioned power exchanges, as well as the individual energy systems (participants), are not shown in the figure for reasons of clarity. Based on numerical, i.e., computer-aided optimization, the control unit controls the energy exchanges between the energy systems of the renewable energy community and a power grid 3 that is higher-level with respect to the energy community. The renewable energy community 1 comprises several energy systems that can exchange green power 4 with each other. Furthermore, the green power can be stored or temporarily stored using at least one battery storage unit 2 of the renewable energy community 1. For the operation of a renewable energy community 1, a distinction is made between green power 4 and gray power 5. Green power 4 is electricity generated from renewable sources within the renewable energy community 1.Grey electricity 5, on the other hand, is not generated renewably by the Renewable Energy Community 1, but is typically procured externally with respect to the Renewable Energy Community 1. 202312301 20 In other words, green electricity 4 is exchanged via the Energy Community 1. Grey electricity 4 can be procured via the electrical grid 3 or fed into it. A surplus of green electricity 4 that is not used by the Energy Community 1 itself or in the Energy Community 1 can be converted internally into grey electricity 5 (arrow 45) and fed into the grid. The Renewable Energy Community 1 or the energy systems of the Renewable Energy Community 1 have additional energy systems that can be divided into generators 11, for example photovoltaic systems, non-controllable loads 12, for example electrical base loads, and controllable loads 13.The battery storage system 2 enables the storage or intermediate storage of green electricity 4 and / or gray electricity 5. To determine the origin of the electricity (green electricity 4 or gray electricity 5), the battery storage system is virtually divided into two partial capacities 21, 22 by the control unit for optimization, i.e. for controlling its charging power and / or discharging power. The first partial capacity 21 is intended for green electricity and the second partial capacity 22 for gray electricity. The partial capacities 21, 22 are not rigid, but dynamic, which is symbolized in the figure by the movable boundary 23 between the partial capacities 21, 22. For control or optimization, the balance equation of the battery storage system 2 is thus divided into the so-called commodities ^^ ∈ ^^, in this case gray electricity 4 and green electricity 5. This ensures that the sum of gray electricity 4 (SoC. ^,௧ ) and Green Power 5 (SoC ଶ,௧) remains within the general memory limits. In other words, the optimization uses the constraint SoC୫୧୬ ^ ∑^ୀ^,ଶ SoC^,௧ ^SoC୫ୟ^ for all considered times ^^, where 202312301 21 SoC ୫୧୬ and SoC ୫ୟ^ the general technical storage limits. Furthermore, it is ensured that the sum of the commodity-specific loading capacities ( and unloading capacities remains within the general performance limits. This is determined by the constraints ^^ ୫୧୬ ^ as well as ^^ ୫୧୬ ^ ∑ ^ୀ^,ଶ ^^ ^, ୡ ^ ୦ ^ ^^ ௧ ∙ ^^ ୫ୟ^ for all considered points in time ^^. The coupling of the respective charge states 21, 22 or partial capacities 21, 22 is then determined during optimization by the constraint ୡ୦ ൌ ^^ ୡ୦ ∙ ^^ ^ / ଶ,௧ െ ^^ ^ୡ୦ ^ / ଶ,௧ / ^^ ^ୡ୦for all considered times ^^, where discrete time steps ∆ ^^ are used and ^^ denotes the total capacity of the battery storage 2. For the second partial capacity 22, an additional constraint is used in the optimization, which ensures that the stored gray current 5 is discharged as far as technically possible and technically reasonable. The technically possible limit is defined by a threshold value SoC ଶ,୫୧୬,௧^ while the technically reasonable limit is defined by a minimum gray current share SoC ଶ,^ is marked. It is technically possible to discharge battery storage 2 within a time range ^^ with a maximum discharge power limit ^^୫ୟ^. Thus, technically, the maximum SoCଶ,୫୧୬,௧^ ൌSoCଶ,௧^ െ ^ ^^^ െ ^^^^ ∙ ^^୫ୟ^ / ^^ and ^^ ൌ ^ ^^^ , ^^^^ at the end of the discharge (time ^^ ^) is achievable. However, since this is technically sensible, for example as a reserve, a minimum gray current 5 should remain in the battery storage 2. The two technical conditions mentioned can thus be summarized as SoCଶ,௧^ ^max ^SoCଶ,୫୧୬,௧^ , SoCଶ,^^. The second state of charge for exactly the time ^^ ^ is thus determined by the maximum of the smallest SoC value that can be achieved while adhering to the discharge power limits and the generally defined threshold for the minimum gray current share. Thus, optimization is ensured at regular intervals, in this case in the last simulation step of each day. ^that the commodity-specific SoC of a storage partition, in this case the gray power 5, does not exceed a defined threshold so that sufficient flexibility can be maintained in the further partition 21 of the battery storage system 2. The withdrawal of the gray power 5 advantageously provides more flexibility for the renewable energy community 1, since more green power 4 can be stored or temporarily stored and used by the renewable energy community 1. However, a minimal proportion of the gray power 5 always remains in the battery storage system 5, which can be used as a reserve. Overall, greater flexibility for renewable energy in the energy community 1 is thus achieved, since the existing flexibility of battery storage systems 2 is not blocked by stored gray power 5, which may not be exchanged within the energy community 1.Although the invention has been illustrated and described in detail by the preferred embodiments, the invention is not limited by the disclosed examples, and other variations can be derived therefrom by a person skilled in the art without departing from the scope of the invention. 202312301 23 List of reference numerals 1 Renewable energy community 2 Battery storage 3 Grid feed-in / grid feed-in 4 Green power 5 Gray power 11 Generator 12 Non-controllable loads 12 Controllable loads 21 First partial capacity 22 Second partial capacity 23 Adjustable limit 45 Conversion from green power to gray power.
Claims
202312301 24 claims 1. Method for operating a battery storage system (2) within a renewable energy community (1), wherein the renewable energy community (1) comprises a plurality of energy systems which are designed to exchange green electricity (4) with one another, as well as to use gray electricity (5) itself and / or to provide it for energy systems external to the renewable energy community (1), wherein a control unit is used to control the battery storage system (2), which control unit is designed to calculate target values for charging powers and / or discharging powers of the battery storage system (2) based on a computer-aided optimization method, wherein the battery storage system (2) is controlled by the control unit in accordance with the calculated target values, characterized in that in the optimization method, the total capacity ^^ of the battery storage system (2) is divided into a first and second partial capacity ^^ ^,௧ , ^^ ଶ,௧(21, 22), where the first partial capacity ^^ ^,௧ (21) for green electricity (4) and the second partial capacity ^^ ଶ,௧ for grey electricity (5), and the second partial capacity ^^ ଶ,௧ (22) in the optimization procedure by a threshold value ^^ ଶ,୪୧୫୧^,் limited by discharging within a time range ^^ taking into account a specified discharge power limit ^^ ୫ୟ^ and a specified minimum second partial capacity ^^ ଶ,^ (22) is maximally achievable.
2. Method according to claim 1, characterized in that in the optimization method the constraint ^^ ଶ,௧^ ^ ^^ ଶ,୪୧୫୧^,் with ^^ ଶ,୪୧୫୧^,் is used, where ^^ ଶ,୫୧୬,௧^ ൌ ^^ ଶ,௧^ െ ^^ ∙ ^^ ୫ୟ^ and ^^ ൌ ^ ^^ ^ , ^^ ^ ^ 3. Method according to claim 1 or 2, characterized in that the discharge power limit ^^ ୫ୟ^by a system-specific maximum power of the battery storage system (2) or by a maximum power of a grid connection point of the Renewable Energy Community (1). 202312301 25 4. Method according to one of the preceding claims, characterized in that the specified time range ^^ comprises one or more time steps of the optimization method.
5. Method according to claim 4, characterized in that the discharge power limit ^^ ୫ୟ^by an average power of maximum discharge powers dependent on the time step.
6. Method according to claim 4 or 5, characterized in that the specified time range only includes the last time step of the optimization process.
7. Method according to one of the preceding claims, characterized in that losses during the storage of the green power (4) are compensated by the gray power (5) stored by means of the second partial capacity (22).
8. Method according to one of the preceding claims, characterized in that in the optimization process, the battery storage (2) is modeled such that for calculating the target values of the charging powers and / or discharging powers, the respective efficiencies , ^^ ^ୡ୦ 9. Method according to claim 8, characterized in that in the optimization process the constraints ൌ ^^ ୡ୦ ^^ ୡ୦ / ଶ,௧ െ ^ୡ୦ ୡ୦ ^ ^^ ^ / ଶ,௧ / ^^ ^ୡ୦ be used, where ^^ ^ / ଶ,௧ the target values of the charging power for the first and second partial capacity (21, 22) and ^^ ^ୡ୦ ^ / ଶ,௧ denote the target values of the discharge power for the first and second partial capacity (21, 22).
10. Method according to one of the preceding claims, characterized in that the time range is set such that a discharge of the second partial capacity (22) takes place when the target value of the discharge power for the first and second partial capacity (21, 22) is 202312301 26 regulated electricity mix has a CO2 footprint above an emission threshold.
11. A control unit for operating a battery storage system (2) within a renewable energy community (1), wherein the renewable energy community (1) comprises a plurality of energy systems configured to exchange green electricity (4) with one another, as well as to use gray electricity (5) themselves and / or to provide it to energy systems external to the renewable energy community (1), wherein the control unit is configured to calculate target values for charging powers and / or discharging powers of the battery storage system (2) based on a computer-aided optimization method, and to control the battery storage system (2) according to the calculated target values, characterized in that the control unit is configured to divide the total capacity of the battery storage system (2) into a first and second partial capacity during the optimization method.^,௧ , ^^ ଶ,௧ (21, 22), where the first partial capacity ^^ ^,௧ (21) for green electricity (4) and the second partial capacity ^^ ଶ,௧ (22) is intended for grey current (5), and the second partial capacity (22) ^^ ଶ,௧ in the optimization process by a threshold value ^^ ଶ,୪୧୫୧^,் limited by discharging within a time range ^^ taking into account a specified discharge power limit ^^ ୫ୟ^ and a specified minimum second partial capacity ^^ ଶ,^ (22) is maximally achievable.
12. Control unit according to claim 11, characterized in that it is designed to control further energy-technical systems (11, 12, 13) within the renewable energy community (1).
13. Control unit according to claim 11 or 12, characterized in that it is designed to control the power exchanges between the energy systems of the renewable energy community (1). 202312301 27 14. Renewable energy community (1), comprising a plurality of energy systems which are designed to exchange green electricity (4) with one another, as well as to use grey electricity (5) themselves and / or to provide it for energy systems external to the renewable energy community (1), characterized in that the renewable energy community (1) comprises a control unit according to one of claims 11 to 13.
15. Renewable energy community (1) according to claim 14, characterized in that the control unit is designed to control the electricity exchanges between the energy systems in such a way that only green electricity (4) is exchanged between the energy systems.