CN114844063A - New energy community non-owned energy storage capacity determination and use strategy optimization method - Google Patents
New energy community non-owned energy storage capacity determination and use strategy optimization method Download PDFInfo
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- 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
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- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
- H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
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Abstract
The invention relates to a new energy community non-owned energy storage capacity determining and use strategy optimizing method, belongs to the field of new energy, and aims to establish a new energy community non-owned energy storage use model for solving the capacity cost of settlement before the day and the use cost of settlement within the day by considering the excessive use of energy storage, combine the reported capacity of frequency modulation auxiliary service before the day to obtain capacity income, receive and issue mileage income within the day, establish a new energy community non-owned energy storage participation frequency modulation auxiliary service optimizing model, and solve the optimal non-owned energy storage capacity determining and use strategy and power under the scene of basic excitation signals by using the optimizing model. And solving the total income from the excitation signal change feedback to the adoption of different strategies under different excitation signal scenes by using a feedback driving method. And determining the optimal non-self energy storage capacity and using strategy under different excitation signal scenes according to the maximum total profit principle, and finishing the optimal decision that the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service.
Description
Technical Field
The invention relates to the field of new energy, in particular to a method for determining non-self energy storage capacity and optimizing a use strategy of a new energy community.
Background
In the face of increasingly severe climate change and carbon emission problems, new energy development has become an important issue. Because the centralized large-scale new energy power generation is limited by higher requirements of natural environment and space, a small-scale new energy community consisting of distributed new energy and users becomes a faster and more common way for developing new energy in future urban areas. However, the available power generation amount of the new energy community at the present stage is small, and most of the new energy communities sell the power generation amount to the power grid in a contractual agreement mode, so that the profit is extremely low. Therefore, how to explore a new profit mode suitable for a new energy community and increase the economy of the community becomes an important problem for the development of new energy in town areas. The energy storage is a flexible resource, and has the characteristic of rapid and large-scale charge and discharge, so that the energy storage becomes a high-quality resource in power auxiliary service, particularly frequency modulation auxiliary service. However, the construction cost of energy storage is high, and it is very difficult to directly invest in small-scale new energy communities to construct energy storage. For the new energy community, the non-self energy storage participating frequency modulation auxiliary service is beneficial to improving the total profit and promoting the popularization and development of new energy in urban areas. However, the current phase of research into optimizing the use of non-owned energy storage to participate in fm assisted services is largely focused on how to design the costs involved with non-owned energy storage and how to properly price from the perspective of the energy storage investor. For a new energy community, the new energy community participates in the frequency modulation auxiliary service through non-self energy storage, and the new energy community faces the problems of how to associate an energy storage non-self usage model with a frequency modulation auxiliary service model and adjust a non-self capacity determination and usage strategy under different conditions of a non-self usage model and an excitation signal of the frequency modulation auxiliary service. Therefore, how to design a non-self-use mechanism suitable for the new energy community to participate in the frequency modulation auxiliary service by using the non-self-stored energy and put forward an optimal decision that the new energy community uses the non-self-stored energy to participate in the frequency modulation auxiliary service under different excitation signals becomes an important problem of improving the economy of the new energy community by using the non-self-stored energy and promoting the new energy development to be popularized in cities and towns in the form of the new energy community.
Disclosure of Invention
The invention aims to provide a new energy community non-owned energy storage capacity determining and using strategy optimizing method, so as to realize the optimal decision that the new energy community uses the non-owned energy storage to participate in frequency modulation auxiliary service under different excitation signal scenes.
In order to achieve the purpose, the invention provides the following scheme:
a new energy community non-owned energy storage capacity determining and using strategy optimizing method comprises the following steps:
establishing a new energy community non-self energy storage use model containing the settlement capacity cost in the day and the settlement use cost in the day;
according to the new energy community non-self energy storage use model, establishing a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service;
acquiring a plurality of historical excitation signals of a non-self energy storage use mode and frequency modulation auxiliary service of new energy community energy storage to form a basic excitation signal;
solving the new energy community usage non-self energy storage optimization model according to the basic excitation signal, and obtaining a non-self energy storage capacity determination and use strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, wherein the non-self energy storage capacity determination and use strategy is used as an optimal non-self energy storage capacity determination and use strategy under the scene of the basic excitation signal;
on the basis of the basic excitation signals, at least one excitation signal in the basic excitation signals is changed randomly to form a plurality of different set excitation signal scenes;
determining an optimal non-self energy storage capacity determination and use strategy under each set excitation signal scene by adopting a feedback driving mode based on the maximum total profit of the new energy community under the basic excitation signal scene;
and the optimal non-owned energy storage capacity determining and using strategy in the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy in each set excitation signal scene form an optimal decision for the new energy community to use the non-owned energy storage to participate in the frequency modulation auxiliary service.
Optionally, the new energy community non-owned energy storage usage model is as follows:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t
wherein, Pay rent,t Represents the total cost of using the non-self energy storage in the t period, Pay rent-ca,t Represents the cost of using the non-self energy storage capacity, Pay, in the t period us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the excessive use cost of using the non-self stored energy in the period t, Pay life-used,t Representing the service cost of the non-self energy storage life in the t period;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil The maximum allowable mileage is represented by the number of lines,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity mileage ratio of the energy storage frequency modulation reported by the non-owned energy storage party in the t period; lambda [ alpha ] rent-ca,t Indicating the use of a non-self-stored energy capacity excitation signal, λ, during the period t over-use,t Representing that a non-self energy storage mileage excitation signal is used in a time period t; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
Optionally, the new energy community uses a non-owned energy storage optimization model including: an objective function and a constraint;
the objective function is:
wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
representing the contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a variable 0-1 that determines whether to overuse stored energy;
indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the constraint of using the non-self energy storage power is as follows:
wherein the content of the first and second substances,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
maximum limit for single use non-self energy storage capacity;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively charge and discharge efficiency by using non-self energy storage;
respectively representing the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
respectively represents the energy storage of t and t +1 time periodsThe SoC value.
Optionally, the basic excitation signal includes a non-self energy storage capacity excitation signal, a non-self energy storage mileage excitation signal, a new energy community contract transaction excitation signal, a time-sharing excitation signal, a frequency modulation capacity excitation signal, and a frequency modulation mileage excitation signal;
the optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time interval when the total profit of the new energy community is maximum, the charging power of the non-owned energy storage is used in each time interval, the discharging power of the non-owned energy storage is used in each time interval, and the historical capacity-mileage ratio of the energy storage frequency modulation reported by an energy storage owner in each time interval.
Optionally, based on the maximum total profit of the new energy community in the basic excitation signal scene, an optimization function used for determining the optimal non-owned energy storage capacity and using the strategy in each set excitation signal scene is determined in a feedback driving manner as follows:
Δpro si ＝f(Δλ i )
pro si ＝obj+Δpro si
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is a set of all non-owned energy storage capacity determination and use strategies;
the optimal profit is obtained when the ith excitation signal changes; p j For the purpose of the optimization of the power of the jth,
the optimum power for the i-th excitation signal variation.
A new energy community non-owned energy storage capacity determination and use strategy optimization system comprises:
the energy storage non-self energy storage use model establishing module is used for establishing a new energy community energy storage non-self energy storage use model containing daily settlement capacity cost and daily settlement use cost;
the non-self energy storage optimization model building module is used for building a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service according to the new energy community energy storage non-self energy storage use model;
the basic excitation signal acquisition module is used for acquiring a plurality of historical excitation signals of a non-self energy storage use model and frequency modulation auxiliary service of new energy community energy storage to form a basic excitation signal;
the basic optimal non-owned energy storage capacity determining and using strategy obtaining module is used for solving a new energy community using non-owned energy storage optimization model according to the basic excitation signal, obtaining a non-owned energy storage capacity determining and using strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, and using the non-owned energy storage capacity determining and using strategy as the optimal non-owned energy storage capacity determining and using strategy under the scene of the basic excitation signal;
the scene setting module is used for randomly changing at least one excitation signal in the basic excitation signals on the basis of the basic excitation signals to form a plurality of different setting excitation signal scenes;
the optimal non-owned energy storage capacity determining and using strategy determining module is set and used for determining the optimal non-owned energy storage capacity determining and using strategy in each set excitation signal scene in a feedback driving mode based on the maximum total profit of the new energy community in the basic excitation signal scene;
and the optimal decision forming module is used for forming an optimal decision of the new energy community using the non-owned energy storage to participate in the frequency modulation auxiliary service together with the optimal non-owned energy storage capacity determining and using strategy under the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy under each set excitation signal scene.
Optionally, the new energy community non-owned energy storage usage model is as follows:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t
wherein, Pay rent,t Represents the total cost of non-self energy storage use in the period t, Pay rent-ca,t Represents the cost of the non-self energy storage capacity in the t period, Pay us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the non-self energy storage overuse cost in the t period, Pay life-used,t Indicating non-self energy storage life usage in t time periodA cost;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil The maximum allowable mileage is represented by the number of lines,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity-mileage ratio of the energy storage frequency modulation reported by the energy storage owner in the t period; lambda [ alpha ] rent-ca,t Representing a non-self energy-storage capacity excitation signal, λ, during a period t over-use,t Representing a non-self energy storage mileage excitation signal in a time period t; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
Optionally, the new energy community uses a non-owned energy storage optimization model including: an objective function and a constraint;
the objective function is:
wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
representing the contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a 0-1 variable for determining whether to overuse stored energy；
Indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda [ alpha ] st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the use of non-self stored energy power constraints is:
wherein the content of the first and second substances,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
maximum limit for single use non-self energy storage capacity;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively charge and discharge efficiency by using non-self energy storage;
respectively representing the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
and respectively representing the SoC values stored in the t and t +1 periods.
Optionally, the basic excitation signal includes a non-self energy storage capacity excitation signal, a non-self energy storage mileage excitation signal, a new energy community contract transaction excitation signal, a time-sharing excitation signal, a frequency modulation capacity excitation signal, and a frequency modulation mileage excitation signal;
the optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time interval when the total profit of the new energy community is maximum, the charging power of the non-owned energy storage is used in each time interval, the discharging power of the non-owned energy storage is used in each time interval, and the historical capacity-mileage ratio of the energy storage frequency modulation reported by an energy storage owner in each time interval.
Optionally, the optimization function used by the optimal non-owned energy storage capacity determination and use strategy determination module is set as follows:
Δpro si ＝f(Δλ i )
pro si ＝obj+Δpro si
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is a set of all non-owned energy storage capacity determination and use strategies;
the optimal profit is obtained when the ith excitation signal changes; p j In order to optimize the power for the jth,
the optimum power for the i-th excitation signal variation.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention discloses a new energy community non-owned energy storage capacity determining and use strategy optimizing method which comprises the steps of firstly considering the overuse of stored energy, establishing a new energy community non-owned energy storage use model for settling the capacity cost and settling the use cost in a day, then combining the reported capacity of frequency modulation auxiliary service in the day to obtain the capacity profit, receiving and issuing mileage in the day to obtain the mileage profit, establishing a new energy community non-owned energy storage participation frequency modulation auxiliary service optimizing model for using the new energy community, and obtaining the optimal non-owned energy storage capacity determining and use strategy and power in a basic excitation signal scene by utilizing the optimizing model. And finally, solving the total income from the excitation signal change feedback to the adoption of different strategies under different excitation signal scenes by using a feedback driving method. And determining the optimal non-self energy storage capacity and using strategy and power under different excitation signal scenes according to the maximum total profit principle, and finishing the optimal decision that the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a new energy community non-owned energy storage capacity determination and usage policy optimization method according to an embodiment of the present invention;
fig. 2 is a block diagram of a new energy community non-owned energy storage capacity determination and usage policy optimization method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a new energy community non-owned energy storage capacity determination and usage policy optimization method according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a new energy community non-owned energy storage capacity determining and using strategy optimizing method, so as to realize the optimal decision that the new energy community uses the non-owned energy storage to participate in frequency modulation auxiliary service under different excitation signal scenes.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The embodiment of the invention provides a new energy community non-owned energy storage capacity determination and use strategy optimization method, as shown in fig. 1-3, comprising the following steps:
and step S1, establishing a new energy community non-owned energy storage use model containing the settlement capacity cost before the day and the settlement use cost in the day.
The non-self energy storage usage patterns of energy storage typically include capacity costs and usage costs. The service cost is usually a specific service cost and a life service cost. And for the new energy community, non-self energy storage is used for participating in the frequency modulation auxiliary service, the capacity of the new energy community is mainly used for reporting the reserved frequency modulation capacity in the day ahead, and the capacity of the new energy community is used for completing the issued frequency modulation mileage in the day. Therefore, for the new energy community non-owned energy storage use model, the specific use cost is the mileage use cost. Considering that a capacity-mileage ratio exists between the energy storage mileage and the energy storage capacity, the mileage usage cost can be divided into an allowable mileage usage cost and an allowable mileage usage cost in consideration of the possibility that the new energy community is allowed to overuse the non-owned energy storage. Therefore, the non-owned energy storage usage model of the new energy community can be specifically expressed as:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t (1)
wherein the formula (3) shows that if the actual mileage is within the maximum allowable range, the energy storage service cost is only the life service cost; and if the maximum allowable range is exceeded, the energy storage service cost, the service life and the excessive service cost. The formula (4) shows that only the mileage outside the allowable range is charged with the overuse fee. The formula (5) shows that the life cost of the stored energy is shared by investors and stored energy owners according to a certain proportionality coefficient.
In the formula, Pay rent,t Represents the total cost of non-self energy storage use in the period t, Pay rent-ca,t Represents the cost of the non-self energy storage capacity in the t period, Pay us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the non-self energy storage overuse cost in the t period, Pay life-used,t Representing the non-self energy storage life service cost in the t period;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil The maximum allowable mileage is represented by the number of lines,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity-mileage ratio of the energy storage frequency modulation reported by the energy storage owner in the t period; lambda [ alpha ] rent-ca,t Representing a non-self energy-storage capacity excitation signal, λ, during a period t over-use,t Representing a non-self energy storage mileage excitation signal in a time period t; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
And step S2, according to the new energy community non-self energy storage use model, establishing a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service.
Referring to fig. 2 and fig. 3, firstly, a new energy community usage non-owned energy storage regulation and control model is established by combining the day-ahead frequency modulation capacity gain and the day-inside frequency modulation mileage gain of the frequency modulation auxiliary service and considering the capacity and the usage cost of the non-owned energy storage. And secondly, considering contract transaction income of the new energy community and operating cost of using non-self stored energy, and establishing an objective function with the maximum total profit of the new energy community as an objective. And finally, considering energy storage power and SoC constraint, establishing a new energy community using a non-self energy storage optimization model which can be specifically expressed as follows:
equations (11) - (12) illustrate the use of non-self-contained energy storage to provide fm assisted services to gain capacity and mileage benefits. The respective costs in the formula (13) can be obtained from the formulae (2) to (7). Equation (14) illustrates that the operating cost of using non-self stored energy is primarily the charging cost, calculated as a time-shared excitation signal.
Wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
to representthe contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a variable 0-1 that determines whether to overuse stored energy;
indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda [ alpha ] st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the use of non-self stored energy power constraints is:
wherein, the first and the second end of the pipe are connected with each other,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
maximum limit for single use non-self energy storage capacity;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively adopts a non-self energy storage charger,Discharge efficiency;
respectively representing the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
and respectively representing the SoC values stored in the t and t +1 periods.
And step S3, acquiring a plurality of historical excitation signals of the non-self energy storage use model and the frequency modulation auxiliary service of the new energy community energy storage to form a basic excitation signal.
The basic excitation signals comprise non-self energy storage capacity excitation signals, non-self energy storage mileage excitation signals, new energy community contract transaction excitation signals, time-sharing excitation signals, frequency modulation capacity excitation signals and frequency modulation mileage excitation signals.
And step S4, solving the new energy community usage non-self energy storage optimization model according to the basic excitation signal, and obtaining a non-self energy storage capacity determination and use strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, wherein the non-self energy storage capacity determination and use strategy is used as the optimal non-self energy storage capacity determination and use strategy under the scene of the basic excitation signal.
And (5) solving according to the optimization model in the step S3 to obtain the optimal power and the optimal strategy for the new energy community to use the non-self energy storage capacity, charge and discharge and the like in the scene of the basic excitation signal.
The strategy is specifically to rent or not rent the stored energy, and the strategy decides whether to use the stored energy within the range of mileage or prepare for overuse, and then decides whether to charge or discharge the non-owned stored energy by the corresponding auxiliary frequency modulation service after the strategy.
The optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time period when the total profit of the new energy community is maximum (in the formula (6))
) Using charging power other than self-stored energy (in equation (6)) for each period
) Using a discharge power not having self-stored energy (in equation (6)) for each period
) And the historical capacity-mileage ratio (in formula (7)) of the energy storage frequency modulation reported by the energy storage owner in each time period
)。
If the capacity of the non-self stored energy used in each time interval and the historical capacity-mileage ratio of the stored energy frequency modulation reported by the stored energy owner in each time interval are known, the frequency modulation mileage in each time interval can be known, so that whether the stored energy use cost is the life use cost or the overuse cost is determined by using the formula (3), namely, whether the stored energy is used in the mileage range or is prepared for overuse is determined.
Step S5 is to arbitrarily change at least one of the basic excitation signals based on the basic excitation signal to form a plurality of different setting excitation signal scenarios.
In order to cope with the practical situation of the frequency modulation auxiliary service, different excitation signals are simulated according to basic data (historical data), and the value of each excitation signal is increased or decreased, specifically, the value is increased or decreased by a certain amount, so that different excitation signal scenes are formed.
And step S6, determining the optimal non-owned energy storage capacity determination and use strategy in each set excitation signal scene by adopting a feedback driving mode based on the maximum total profit of the new energy community in the basic excitation signal scene.
By way of example, what is fed back, such as the change of the non-own energy storage capacity excitation signal of the non-own energy storage usage model, has a feedback effect on the final profit, and the function of the feedback is the optimization function, so that the excitation signal is changed and the optimization result is changed. So that the total profit ultimately obtained using different strategies also differs. Finally, the optimal strategy and power corresponding to different excitation signal changes can be obtained according to the maximum total profit. The change of the excitation signal requires a comparison object, which is the excitation signal in the first basic scene, i.e. the historical data or the basic data.
Therefore, a feedback driving mode is adopted, and the total profit determined and used by different non-owned energy storage capacity and using strategies when different excitation signals such as non-owned energy storage capacity, overuse, frequency modulation capacity, frequency modulation mileage and the like change is analyzed according to the basic excitation signals. According to the maximum total profit, whether the new energy community uses the non-owned energy storage or not and whether the energy storage is excessively used or not in the scene is selected, so that the optimal non-owned energy storage capacity determination, the use strategy and the optimal power of the new energy community using the non-owned energy storage to participate in the frequency modulation auxiliary service in different excitation signal scenes of the new energy are obtained, and therefore the optimal decision of the new energy community using the non-owned energy storage to participate in the frequency modulation auxiliary service is completed, and the following expression is shown:
Δpro si ＝f(Δλ i ) (21)
pro si ＝obj+Δpro si (22)
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is all non-self energy storage capacityDetermining and using a set of policies;
the optimal profit is obtained when the ith excitation signal changes; p j For the purpose of the optimization of the power of the jth,
the optimum power for the i-th excitation signal variation.
And step S7, the optimal non-owned energy storage capacity determining and using strategy in the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy in each set excitation signal scene form an optimal decision that the new energy community uses the non-owned energy storage to participate in the frequency modulation auxiliary service.
The invention aims to protect an optimal non-self energy storage decision method of a new energy community based on frequency modulation auxiliary service feedback driving. The method is characterized in that according to the characteristic that the non-self energy storage mode has the daily settlement of the non-self energy storage capacity cost and the daily settlement of the use cost, the corresponding frequency modulation capacity and the frequency modulation mileage in the frequency modulation auxiliary service are combined, whether the non-self energy storage mileage is used excessively or not is considered, and a non-self energy storage use model for the new energy community to use the non-self energy storage to participate in the frequency modulation auxiliary service is established. Considering the mechanism characteristic that the capacity is reported by a frequency modulation auxiliary service link day ahead and the mileage is issued within the day, taking the non-owned energy storage used by the new energy community as an excitation signal receiver of the frequency modulation auxiliary service, and establishing an optimization model that the new energy community uses the non-owned energy storage to participate in the frequency modulation auxiliary service according to the non-owned energy storage using mechanism. Considering the power and SoC constraint of using the non-self energy storage, the running cost of the new energy community using the non-self energy storage to participate in the frequency modulation auxiliary service and the income of an energy link for trading incentive signal settlement according to contracts are calculated, and the optimal non-self energy storage power of the new energy community participating in the frequency modulation auxiliary service link under the scene of basic incentive signals is obtained by taking the maximum income of the new energy community as a target. Based on the changes of different excitation signals such as the excitation signal with the non-owned energy storage capacity, the overuse excitation signal, the frequency modulation capacity excitation signal, the frequency modulation mileage excitation signal and the like, the economic analysis is carried out on the determination and use strategies of the different non-owned energy storage capacities in a feedback driving mode, and the optimal determination and use strategies of the non-owned energy storage capacities and the non-owned energy storage capacities corresponding to the conditions of the different excitation signals are obtained.
The invention has the technical effects that:
(1) the invention considers the relation between the capacity cost and the use cost of the non-self energy storage and the frequency modulation capacity and the frequency modulation mileage of the frequency modulation auxiliary service, so that the mechanism of using the non-self energy storage by the new energy community is more specific to the frequency modulation auxiliary service. The invention also considers the characteristics of the frequency modulation mileage, establishes a new energy community non-self energy storage use model containing the settlement of the non-self energy storage capacity cost before the day, the settlement of the service life cost in the day and the over-use cost of the mileage, and ensures that the mechanism that the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service is more reasonable.
(2) The method fully considers the influence of different excitation signal conditions such as non-self energy storage capacity, overuse, frequency modulation capacity, frequency modulation mileage and the like on the use of the non-self energy storage strategy in the new energy community, and determines the different non-self energy storage capacities under different excitation signals and uses the strategy to obtain the total profit by using a feedback driving mode, so that the optimal energy storage capacity determination, use strategy and optimal power of energy storage under different excitation signal conditions can be obtained. The method and the system have the advantage that the decision of the new energy community using the non-self energy storage to participate in the frequency modulation auxiliary service is more comprehensive by considering the excitation signals under different conditions. And the decision of using the non-self energy storage to participate in the frequency modulation auxiliary service can be obtained under the condition of only acquiring historical data or basic data, and a corresponding decision can be made when the historical data or the basic data change, so that the optimal non-self energy storage capacity determination, the use strategy and the optimal power can be obtained under the condition of different excitation signals, and the decision of using the non-self energy storage to participate in the frequency modulation auxiliary service of the new energy community is more scientific.
The embodiment of the invention also provides a new energy community non-owned energy storage capacity determination and use strategy optimization system, which comprises:
the energy storage non-self energy storage use model establishing module is used for establishing a new energy community energy storage non-self energy storage use model containing daily settlement capacity cost and daily settlement use cost;
the non-self energy storage optimization model building module is used for building a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service according to the non-self energy storage use model of the new energy community;
the basic excitation signal acquisition module is used for acquiring a plurality of historical excitation signals of a non-self energy storage use model and frequency modulation auxiliary service of new energy community energy storage to form a basic excitation signal;
the basic optimal non-owned energy storage capacity determining and using strategy obtaining module is used for solving a new energy community using non-owned energy storage optimization model according to the basic excitation signal, obtaining a non-owned energy storage capacity determining and using strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, and using the non-owned energy storage capacity determining and using strategy as the optimal non-owned energy storage capacity determining and using strategy under the scene of the basic excitation signal;
the scene setting module is used for randomly changing at least one excitation signal in the basic excitation signals on the basis of the basic excitation signals to form a plurality of different setting excitation signal scenes;
the optimal non-owned energy storage capacity determining and using strategy determining module is set and used for determining the optimal non-owned energy storage capacity determining and using strategy under each set excitation signal scene in a feedback driving mode based on the maximum total profit of the new energy community under the basic excitation signal scene;
and the optimal decision forming module is used for forming an optimal decision of the new energy community using the non-owned energy storage to participate in the frequency modulation auxiliary service together with the optimal non-owned energy storage capacity determining and using strategy under the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy under each set excitation signal scene.
The new energy community non-owned energy storage use model is as follows:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t
wherein, Pay rent,t Represents the total cost of non-self energy storage use in the period t, Pay rent-ca,t Represents the cost of the non-self energy storage capacity in the t period, Pay us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the non-self energy storage overuse cost in the t period, Pay life-used,t Representing the non-self energy storage life service cost in the t period;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil The maximum allowable mileage is represented by the number of lines,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity-mileage ratio of the energy storage frequency modulation reported by the energy storage owner in the t period; lambda [ alpha ] rent-ca,t Representing a non-self energy-storage capacity excitation signal, λ, during a period t over-use,t Representing a non-self energy storage mileage excitation signal in a t time period; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
The new energy community uses a non-owned energy storage optimization model which comprises the following steps: an objective function and a constraint;
the objective function is:
wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
representing the contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a variable 0-1 that determines whether to overuse stored energy;
indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda [ alpha ] st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the use of non-self stored energy power constraints is:
wherein the content of the first and second substances,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
for single use, non-self energy storage capacityA large limit;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively charge and discharge efficiency by using non-self energy storage;
respectively representing the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
and respectively representing the SoC values stored in the t and t +1 periods.
The basic excitation signals comprise non-self energy storage capacity excitation signals, non-self energy storage mileage excitation signals, new energy community contract transaction excitation signals, time-sharing excitation signals, frequency modulation capacity excitation signals and frequency modulation mileage excitation signals.
The optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time interval when the total profit of the new energy community is maximum, the charging power of the non-owned energy storage is used in each time interval, the discharging power of the non-owned energy storage is used in each time interval, and the historical capacity mileage ratio of the energy storage frequency modulation reported by an energy storage owner in each time interval.
The optimal non-owned energy storage capacity determining and using strategy determining module is set to use the following optimization functions:
Δpro si ＝f(Δλ i )
pro si ＝obj+Δpro si
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is a set of all non-owned energy storage capacity determination and use strategies;
the optimal profit is obtained when the ith excitation signal changes; p j For the purpose of the optimization of the power of the jth,
the optimum power for the i-th excitation signal variation.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. A new energy community non-owned energy storage capacity determining and using strategy optimizing method is characterized by comprising the following steps:
establishing a new energy community non-self energy storage use model containing the settlement capacity cost in the day and the settlement use cost in the day;
according to the new energy community non-self energy storage use model, establishing a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service;
acquiring a plurality of historical excitation signals of a non-self energy storage use model and frequency modulation auxiliary service of new energy community energy storage to form a basic excitation signal;
solving the new energy community usage non-self energy storage optimization model according to the basic excitation signal, and obtaining a non-self energy storage capacity determination and use strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, wherein the non-self energy storage capacity determination and use strategy is used as an optimal non-self energy storage capacity determination and use strategy under the scene of the basic excitation signal;
on the basis of the basic excitation signals, at least one excitation signal in the basic excitation signals is changed randomly to form a plurality of different set excitation signal scenes;
determining an optimal non-self energy storage capacity determination and use strategy under each set excitation signal scene by adopting a feedback driving mode based on the maximum total profit of the new energy community under the basic excitation signal scene;
and the optimal non-owned energy storage capacity determining and using strategy in the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy in each set excitation signal scene form an optimal decision for the new energy community to use the non-owned energy storage to participate in the frequency modulation auxiliary service.
2. The method for determining and optimizing the non-owned energy storage capacity of the new energy community according to claim 1, wherein the non-owned energy storage usage model of the new energy community is as follows:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t
wherein, Pay rent,t Represents the total cost of non-self energy storage use in the period t, Pay rent-ca,t Represents the cost of the non-self energy storage capacity in the t period, Pay us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the non-self energy storage overuse cost in the t period, Pay life-used,t Representing the non-self energy storage life service cost in the t period;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil It is indicated that the maximum allowable mileage is,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity-mileage ratio of the energy storage frequency modulation reported by the energy storage owner in the t period; lambda [ alpha ] rent-ca,t Representing a non-self energy-storage capacity excitation signal, λ, during a period t over-use,t Representing a non-self energy storage mileage excitation signal in a time period t; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
3. The method for determining the non-owned energy storage capacity and optimizing the usage strategy of the new energy community according to claim 2, wherein the method for optimizing the usage of the non-owned energy storage capacity of the new energy community comprises the following steps: an objective function and a constraint;
the objective function is:
wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
representing the contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a variable 0-1 that determines whether to overuse stored energy;
indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the use of non-self stored energy power constraints is:
wherein the content of the first and second substances,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
maximum limit for single use non-self energy storage capacity;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively charge and discharge efficiency by using non-self energy storage;
respectively the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
and respectively representing the SoC values stored in the t and t +1 periods.
4. The new energy community non-owned energy storage capacity determination and usage strategy optimization method according to claim 3,
the basic excitation signals comprise non-self energy storage capacity excitation signals, non-self energy storage mileage excitation signals, new energy community contract transaction excitation signals, time-sharing excitation signals, frequency modulation capacity excitation signals and frequency modulation mileage excitation signals;
the optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time interval when the total profit of the new energy community is maximum, the charging power of the non-owned energy storage is used in each time interval, the discharging power of the non-owned energy storage is used in each time interval, and the historical capacity-mileage ratio of the energy storage frequency modulation reported by an energy storage owner in each time interval.
5. The method for determining the non-owned energy storage capacity of the new energy community and optimizing the usage strategy of the new energy community according to claim 3, wherein the optimal non-owned energy storage capacity determination and usage strategy in each set excitation signal scene is determined by a feedback-driven method based on the maximum total profit of the new energy community in the basic excitation signal scene as follows:
Δpro si ＝f(Δλ i )
pro si ＝obj+Δpro si
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is a set of all non-owned energy storage capacity determination and use strategies;
the optimal profit is obtained when the ith excitation signal changes; p j For the purpose of the optimization of the power of the jth,
the optimum power for the i-th excitation signal variation.
6. A new energy community non-owned energy storage capacity determination and use strategy optimization system is characterized by comprising:
the non-self energy storage use model establishing module is used for establishing a new energy community non-self energy storage use model containing daily settlement capacity cost and daily settlement use cost;
the non-self energy storage optimization model building module is used for building a new energy community use non-self energy storage optimization model which aims at the maximum total profit of the new energy community when the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service according to the non-self energy storage use model of the new energy community;
the basic excitation signal acquisition module is used for acquiring a plurality of historical excitation signals of a non-self energy storage use model and frequency modulation auxiliary service of new energy community energy storage to form a basic excitation signal;
the basic optimal non-owned energy storage capacity determining and using strategy obtaining module is used for solving a new energy community using non-owned energy storage optimization model according to the basic excitation signal, obtaining a non-owned energy storage capacity determining and using strategy when the total profit of the new energy community is maximum under the scene of the basic excitation signal, and using the non-owned energy storage capacity determining and using strategy as the optimal non-owned energy storage capacity determining and using strategy under the scene of the basic excitation signal;
the scene setting module is used for randomly changing at least one excitation signal in the basic excitation signals on the basis of the basic excitation signals to form a plurality of different setting excitation signal scenes;
the optimal non-owned energy storage capacity determining and using strategy determining module is set and used for determining the optimal non-owned energy storage capacity determining and using strategy under each set excitation signal scene in a feedback driving mode based on the maximum total profit of the new energy community under the basic excitation signal scene;
and the optimal decision forming module is used for forming an optimal decision of the new energy community for participating in the frequency modulation auxiliary service by using the non-owned energy storage together with the optimal non-owned energy storage capacity determining and using strategy under the basic excitation signal scene and the optimal non-owned energy storage capacity determining and using strategy under each set excitation signal scene.
7. The system for determining and optimizing the non-owned energy storage capacity of the new energy community according to claim 6, wherein the non-owned energy storage usage model of the new energy community is:
Pay rent,t ＝Pay rent-ca,t +Pay us-fee,t
wherein, Pay rent,t Represents the total cost of the non-self energy storage use in the period t, Pay rent-ca,t Represents the cost of the non-self energy storage capacity in the t period, Pay us-fee,t Represents the non-self energy storage use cost, Pay, of the t period over-used,t Represents the non-self energy storage overuse cost in the t period, Pay life-used,t Representing the non-self energy storage life service cost in the t period;
indicating that the t period uses the capacity of the non-self energy storage,
representing the actual mileage in the period t, P allowed-mil The maximum allowable mileage is represented by the number of lines,
indicating that the total capacity of the non-self stored energy is used,
indicating that the charging power other than the self-stored energy is used in the period t,
indicating that the discharging power of the non-self stored energy is used in the t period;
representing the historical capacity-mileage ratio of the energy storage frequency modulation reported by the energy storage owner in the t period; lambda [ alpha ] rent-ca,t Representing a non-self energy-storage capacity excitation signal, λ, during a period t over-use,t Representing a non-self energy storage mileage excitation signal in a time period t; c represents a life cost sharing proportionality coefficient, C rp Representing the cost of energy storage replacement.
8. The new energy community non-owned energy storage capacity determination and usage strategy optimization system according to claim 7, wherein the new energy community usage non-owned energy storage optimization model comprises: an objective function and a constraint;
the objective function is:
wherein obj represents the maximum total profit for the new energy community,
the new energy community uses the non-self energy storage to participate in the frequency modulation auxiliary service income in the time period t,
representing the contract electricity price earnings for the period t,
representing the non-own cost of energy storage capacity for the period t,
represents the life use cost for the period t,
which represents the operating cost for the period t,
represents the t-period overuse cost; p represents a variable 0-1 to determine whether to overuse stored energy;
indicating the benefit of using non-self energy storage to participate in frequency up-regulation during the period t,
representing the benefit of using non-self energy storage to participate in frequency down-regulation in the t period;
representing the generated power of the new energy community in the time period t,
representing the load power of the new energy community in the t period; lambda [ alpha ] st,t Represents a contract transaction excitation signal, lambda, of the new energy community in the t period tou,t Represents the time-sharing excitation signal of the t period,
represents a frequency modulated capacity excitation signal for a period of t,
representing a frequency-modulated mileage stimulus signal at a time t; n represents the total time period;
the constraint conditions comprise a non-self energy storage power constraint and an energy storage life loss constraint;
the use of non-self stored energy power constraints is:
wherein the content of the first and second substances,
the maximum rates of charge and discharge using non-self stored energy are respectively; mu is a variable 0-1 for limiting the energy storage and not simultaneously charging and discharging;
maximum limit for single use non-self energy storage capacity;
the energy storage life loss constraint is as follows:
wherein the content of the first and second substances,
respectively charge and discharge efficiency by using non-self energy storage;
respectively representing the initial and final SoC values of the stored energy;
respectively the allowed minimum and maximum SoC values of stored energy;
and respectively representing the SoC values stored in the t and t +1 periods.
9. The new energy community non-owned energy storage capacity determination and usage strategy optimization system according to claim 8,
the basic excitation signals comprise non-self energy storage capacity excitation signals, non-self energy storage mileage excitation signals, new energy community contract transaction excitation signals, time-sharing excitation signals, frequency modulation capacity excitation signals and frequency modulation mileage excitation signals;
the optimal non-owned energy storage capacity determining and using strategy refers to that the capacity of the non-owned energy storage is used in each time interval when the total profit of the new energy community is maximum, the charging power of the non-owned energy storage is used in each time interval, the discharging power of the non-owned energy storage is used in each time interval, and the historical capacity-mileage ratio of the energy storage frequency modulation reported by an energy storage owner in each time interval.
10. The system of claim 8, wherein the optimization function used by the optimal non-owned energy storage capacity determination and usage policy determination module is:
Δpro si ＝f(Δλ i )
pro si ＝obj+Δpro si
wherein, Δ λ i Is the variation of the i-th excitation signal, f (Δ λ) i ) For total profit feedback corresponding to variation of the i-th excitation signal, Δ pro si Determining the profit variation corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal is changed; pro si Determining the total profit corresponding to the sih non-owned energy storage capacity and the use strategy when the ith excitation signal changes; s is a set of all non-owned energy storage capacity determination and use strategies;
the optimal profit is obtained when the ith excitation signal changes; p j For the purpose of the optimization of the power of the jth,
the optimum power for the i-th excitation signal variation.
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