Energy storage dispatching method for participating in frequency modulation auxiliary service market

Abstract

The application relates to the field of power systems, and particularly discloses a shared energy storage frequency modulation auxiliary service market energy storage scheduling method. The shared energy storage is a storage cluster of multiple storages aggregated from at least one side of power sources, power grids and loads, and participates in frequency modulation as an independent market subject. The frequency modulation market subject includes a power dispatch center and a plurality of shared energy storages and thermal power units. The method comprises the following steps: a master-slave game model of shared energy storage day-ahead frequency modulation is constructed with the power dispatch center as the master and the shared energy storages and the thermal power units as the slaves, and the model is solved to obtain the winning amount and the clearing price of each shared energy storage and thermal power unit in each period; an internal cooperation game model of each shared energy storage day-ahead frequency modulation is constructed with the minimum total frequency modulation cost and the maximum total frequency modulation performance of the aggregated storages as the targets; and the internal cooperation game model is solved according to the winning amount and the clearing price of each shared energy storage to obtain the scheduling result. The application can improve the utilization rate of the energy storage and relieve the frequency modulation pressure of the power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power systems, and particularly relates to a shared energy storage participating in frequency modulation auxiliary service market energy storage scheduling method. BACKGROUND

[0002] With the deepening of global energy transformation, the proportion of renewable energy power generation in the power grid is increasing. However, the output of renewable energy such as wind power and photovoltaic power has randomness and volatility, so the increase of the proportion of new energy access in the power grid will have a certain impact on the frequency stability of the power grid. Moreover, with the growth of user electricity demand, the power load changes frequently, and the frequency modulation pressure of the power grid also increases. Based on this, how to effectively use the existing frequency modulation resources has become a key problem to alleviate the frequency modulation pressure of the power system.

[0003] Among them, energy storage has significant advantages in power frequency modulation resources due to its fast response speed, high accuracy and bidirectional regulation capability. However, at present, there is a problem of low actual utilization rate of energy storage in new energy stations, independent energy storage and user-side energy storage, which leads to a great waste of energy storage resources. SUMMARY

[0004] Therefore, the present application provides a shared energy storage participating in frequency modulation auxiliary service market energy storage scheduling method to try to solve or at least alleviate the above problems.

[0005] According to an aspect of the present application, there is provided a method for dispatching energy storage participating in a frequency modulation auxiliary service market, wherein the energy storage is an energy storage cluster aggregated from at least one of power sources, power grids and users, and participates in the frequency modulation auxiliary service market as an independent market subject, the market subjects of the frequency modulation auxiliary service market include a power dispatch center and a plurality of energy storages and thermal power units, the method comprising: obtaining basic parameters, the basic parameters including available capacities, available mileages, capacity bids, mileage bids of each energy storage and thermal power unit, and capacity demand, mileage demand, capacity bid interval and mileage bid interval of the power dispatch center; constructing a master-slave game model of the energy storage for day-ahead frequency modulation, with the power dispatch center as the master and the energy storages and thermal power units as the slaves, and with the minimum day-ahead frequency modulation total scheduling cost of the power dispatch center as the upper target and the maximum day-ahead frequency modulation revenue of each energy storage and thermal power unit as the lower target; inputting the basic parameters into the master-slave game model to obtain the capacity bid amount, mileage bid amount and clearing price of each energy storage and thermal power unit in each period in the day-ahead frequency modulation market; constructing an internal cooperation game model of each energy storage for day-ahead frequency modulation, with the minimum total frequency modulation cost and the maximum total frequency modulation performance of each energy storage as the target; and for each energy storage, solving the internal cooperation game model of the energy storage according to the capacity bid amount, mileage bid amount and clearing price of the energy storage in each period in the day-ahead frequency modulation market to obtain the dispatching result of each energy storage aggregated by the energy storage, the dispatching result including the capacity output and mileage output of each energy storage in each period in the day-ahead frequency modulation market.

[0006] According to another aspect of the present application, there is provided a computing device, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, and the program instructions comprise instructions for executing the method for dispatching energy storage participating in a frequency modulation auxiliary service market according to the present application.

[0007] According to another aspect of the present application, there is provided a readable storage medium storing program instructions, which, when read and executed by a computing device, causes the computing device to execute the method for dispatching energy storage participating in a frequency modulation auxiliary service market according to the present application.

[0008] In summary, the application proposes a shared energy storage frequency modulation operation mode, specifically, the shared energy storage effectively aggregates idle energy storage distributed in different positions of the power supply side, the power grid side and the load side, and participates in the frequency modulation market as an independent energy storage, so that the frequency modulation pressure of the power grid can be relieved, and the utilization efficiency of idle energy storage distributed in different positions of the source, the grid and the load can be improved, and the superior frequency modulation performance of the energy storage is fully utilized. Moreover, the application constructs a bidding clearing master-slave game model of shared energy storage frequency modulation and a cooperation game model of each energy storage in the shared energy storage cluster based on game theory, and by simultaneously applying the cooperation game and the non-cooperation game method in the shared energy storage, the optimal scheduling of each energy storage can be realized, and the timeliness and accuracy of the energy storage frequency modulation scheduling are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0009] To the accomplishment of the foregoing and related ends, certain illustrative aspects are described herein in connection with the following description and the annexed drawings. These aspects are indicative of various ways in which the principles disclosed herein can be practiced and all aspects and equivalents thereof are intended to be within the scope of the claimed subject matter. The above- and other advantages of the present disclosure, as defined solely by the claims, will become more fully apparent from the detailed description given herein below and the accompanying drawings, wherein like elements are referred to by like reference numerals. Described are certain illustrative aspects to provide a full understanding of various aspects of the present disclosure. The aspects can be combined with each other’s various embodiments, however, other aspects can include not all of the aspects or embodiments discussed in combination.

[0010] Figure 1 A structural block diagram of a computing device 100 according to one embodiment of the application is shown;

[0011] Figure 2 A flow chart of an energy storage scheduling method 200 of shared energy storage participating in frequency modulation auxiliary service market according to one embodiment of the application is shown;

[0012] Figure 3 A schematic diagram of an operation mode of shared energy storage according to one embodiment of the application is shown;

[0013] Figure 4 A schematic diagram of a market subject operation mode of shared energy storage frequency modulation according to one embodiment of the application is shown;

[0014] Figure 5 A schematic diagram of a master-slave game model solving framework of shared energy storage day-ahead frequency modulation according to one embodiment of the application is shown;

[0015] Figure 6 A schematic diagram of an internal cooperation game model solving framework of shared energy storage according to one embodiment of the application is shown;

[0016] Figure 7 A schematic diagram of system prediction data and time-of-use electricity price according to one embodiment of the application is shown;

[0017] Figure 8A schematic diagram of the winning capacity and the winning mileage of the energy storage and thermal power unit in the day-ahead frequency modulation market according to one embodiment of the present application is shown;

[0018] Figure 9 A schematic diagram of the capacity output and the mileage output of each energy storage in the shared energy storage according to one embodiment of the present application is shown;

[0019] Figure 10 A schematic diagram of the total capacity output and the total mileage output of each energy storage according to one embodiment of the present application is shown;

[0020] Figure 11 A schematic diagram of a comparative analysis chart of the income of each energy storage before and after improvement according to one embodiment of the present application is shown. DETAILED DESCRIPTION

[0021] Exemplary embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.

[0022] In view of the low utilization rate of the current energy storage, the present application proposes an operation mode of shared energy storage participating in the frequency modulation auxiliary service market, and provides an energy storage scheduling method of shared energy storage participating in the frequency modulation auxiliary service market. Specifically, the idle energy storage dispersed in different positions of source, network, load and the like is aggregated as shared energy storage, participates in the frequency modulation bidding as an independent market subject, and optimizes and schedules the internal energy storage of the cluster by using a scheduling strategy, so that the utilization rate of the energy storage can be improved, and the frequency modulation pressure of the power grid can be relieved.

[0023] The energy storage scheduling method of shared energy storage participating in the frequency modulation auxiliary service market of the present application can be executed in a computing device. Figure 1 A block diagram of the physical components (i.e., hardware) of the computing device 100 is shown. In a basic configuration, the computing device 100 includes at least one processing unit 102 and a system memory 104. According to one aspect, depending on the configuration and type of the computing device, the processing unit 102 can be implemented as a processor. The system memory 104 includes, but is not limited to, volatile (e.g., random access memory (RAM)), non-volatile (e.g., read-only memory (ROM)), flash memory, or any combination thereof. According to one aspect, the system memory 104 includes an operating system 105 and a program module 106, and the program module 106 includes an energy storage scheduling module 120 configured to execute the energy storage scheduling method 200 of shared energy storage participating in the frequency modulation auxiliary service market of the present application.

[0024] According to one aspect, operating system 105 is, for example, suitable for controlling the operation of computing device 100. Furthermore, examples are practiced in conjunction with graphics libraries, other operating systems, or any other applications, and are not limited to any particular application or system. Figure 1 The basic configuration is illustrated by the components within the dashed lines 108. According to one aspect, the computing device 100 has additional features or functions. For example, according to one aspect, the computing device 100 includes additional data storage devices (removable and / or non-removable), such as disks, optical discs, or magnetic tapes. This additional storage... Figure 1 The image is shown by removable storage 109 and non-removable storage 110.

[0025] As stated above, according to one aspect, a program module is stored in system memory 104. According to one aspect, the program module may include one or more applications. The present invention does not limit the type of application; for example, applications may include: email and contact applications, word processing applications, spreadsheet applications, database applications, slideshow applications, drawing or computer-aided applications, web browser applications, etc.

[0026] According to one aspect, examples can be practiced on circuits including discrete electronic components, packaged or integrated electronic chips containing logic gates, circuits utilizing microprocessors, or on a single chip containing electronic components or a microprocessor. For example, it can be practiced via wherein... Figure 1 Each or many of the components shown can be implemented as an example by integrating a System-on-a-Chip (SOC) on a single integrated circuit. According to one aspect, such an SOC device may include one or more processing units, graphics units, communication units, system virtualization units, and various application functions, all integrated (or “burned in”) as a single integrated circuit onto a chip substrate. When operating via the SOC, the functions described herein can be operated via dedicated logic integrated on a single integrated circuit (chip) with other components of the computing device 100. Embodiments of the invention can also be implemented using other techniques capable of performing logical operations (e.g., AND, OR, and NOT), including but not limited to mechanical, optical, fluid, and quantum technologies. Additionally, embodiments of the invention can be implemented within a general-purpose computer or in any other circuit or system.

[0027] According to an aspect, the computing device 100 can also have one or more input device(s) 112 such as a keyboard, mouse, pen, voice input device, touch input device, etc. Output device(s) 114 such as a display, speakers, printer, etc. can also be included. The aforementioned devices are examples and others can be used. The computing device 100 can include one or more communication connections 116 allowing communications with other computing devices 118. Examples of suitable communication connections 116 include, but are not limited to, an RF transmitter, receiver, and / or transceiver circuitry; universal serial bus (USB), parallel, and / or serial ports.

[0028] The term computer readable media as used herein includes computer storage media. Computer storage media can include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, or program modules. The system memory 104, the removable storage 109, and the non-removable storage 110 are all computer storage media examples (i.e., memory storage.) Computer storage media can include Random Access Memory (RAM), Read-Only Memory (ROM), Electronically Erasable Programmable Read-Only Memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store information and which can be accessed by the computing device 100. According to an aspect, any such computer storage media can be part of the computing device 100. Computer storage media does not include a modulated data signal or other propagated data signal.

[0029] According to an aspect, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. According to an aspect, the term "modulated data signal" describes a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

[0030] Figure 2 A flowchart of a method 200 of energy storage dispatching for participation in a frequency regulation ancillary services market is shown, according to one embodiment of the present application. The method 200 is suitable for execution in a computing device (e.g., the computing device 100 shown Figure 1

[0031] ​Here, a few points are first explained. First, the shared energy storage is an energy storage cluster aggregated from at least one side of the power supply, the power grid, and the load, and in some embodiments, the shared energy storage can be an energy storage cluster aggregated from idle energy storages distributed on the power supply side, the power grid side, and the load side (or user side). Further, the energy storages on the power supply side, the power grid side, and the load side can be pumped storage, compressed air energy storage, flywheel energy storage, flow battery, lithium ion battery, sodium-sulfur battery, and lead-acid battery. That is, the shared energy storage can be composed of one or more of pumped storage, compressed air energy storage, flywheel energy storage, flow battery, lithium ion battery, sodium-sulfur battery, and lead-acid battery.

[0032] Specifically, the shared energy storage refers to a large energy storage power station invested and constructed by a third party. These power stations not only meet their own energy storage needs, but also provide the required energy storage services to other new energy stations. The shared energy storage uses advanced intelligent control technology to centrally control idle energy storages (such as pumped storage, compressed air energy storage, flywheel energy storage, flow battery, lithium ion battery, sodium-sulfur battery, and lead-acid battery) distributed at different locations of the source, the grid, and the load, with the grid as the link. This breaks the original 1-to-1 relationship between energy storage and new energy stations and turns to a 1-to-N relationship, so as to realize the optimal allocation of the whole grid energy storage resources, meet the requirements of new energy stations for mandatory energy storage, create new profit channels for energy storage, and improve the utilization rate of energy storage.

[0033] Second, after the centralized management of multiple dispersed energy storage devices, the shared energy storage participates in the frequency modulation auxiliary service market as an independent market subject (i.e., a whole). Specifically, in some embodiments, each energy storage owner connects their energy storage device to the shared energy storage, which can be uniformly dispatched by the shared energy storage operator. Figure 3 which shows the operation mode of the shared energy storage according to an embodiment of the present application. The grid effectively aggregates idle energy storage resources distributed on the power supply side, the power grid side, and the user side, as well as independent energy storages to realize unified dispatching. The shared energy storage operator can use bilateral negotiation, bidding, or unilateral calling to conduct power trading, or can obtain rental fees by renting energy storage devices to new energy stations, users, and conventional units. At the same time, the shared energy storage can also participate in the power market as an independent market subject to obtain income. For new energy stations, renting shared energy storage can reduce the construction and operation and maintenance costs of mandatory energy storage for new energy stations, thereby not only improving the utilization rate of renewable energy, but also enabling new energy stations to obtain more power income after being connected to the grid; for users, by renting shared energy storage, they can fully utilize the grid price difference to realize peak-valley arbitrage.

[0034] Next, the market subject operation mode of the shared energy storage frequency modulation is explained. For example, Figure 4which shows the operation mode of market subject of shared energy storage frequency modulation according to one embodiment of the application. In the mode, the market transaction subject of shared energy storage participating in frequency modulation can include power generation enterprises such as thermal power and gas turbine, and third-party institutions such as energy storage power station and integrated energy supplier; the market operation subject includes power dispatching institution (i.e. power dispatching center) and power transaction institution.

[0035] The power dispatching institution and the power transaction institution are the core departments of the frequency modulation market, which are responsible for collecting and releasing all relevant information of the frequency modulation market. The main responsibilities of the power dispatching center include: daily operation of the power frequency modulation auxiliary service market; organizing transactions according to the established market rules and calling power according to the transaction results; releasing market information, providing market transaction and calling results to the power transaction center; evaluating the running state of the power frequency modulation auxiliary service market; and implementing power dispatching, etc. The main work of the power transaction center includes: managing the registration transactions of transaction subjects; providing settlement basis and corresponding services for power market transactions; and being responsible for disclosing relevant market information, etc.

[0036] When the shared energy storage participates in the frequency modulation market bidding and clearing, the power dispatching institution predicts and analyzes the day-ahead frequency modulation demand according to the predicted power generation capacity of each power generation subject and the load demand, and releases the frequency modulation demand, price range, etc. in the frequency modulation market. Each market subject declares the frequency modulation capacity, frequency modulation mileage, capacity price and mileage price in the frequency modulation market according to the available capacity of frequency modulation and the technical characteristics of the unit, the power dispatching institution sorts the mileage price declared by each unit from low to high, clears in turn until the clearing quantity meets the day-ahead frequency modulation demand, and takes the mileage price of the last clearing unit as the unified clearing price to pre-clear each unit. After the clearing is completed, the power dispatching center evaluates the actual frequency modulation of each unit, calculates the comprehensive frequency modulation performance of each unit from three aspects of adjustment rate, adjustment accuracy and response time, and settles the clearing quantity of each unit based on the calculation result.

[0037] Within the shared energy storage, the shared energy storage provider utilizes advanced intelligent system control technology to optimize the scheduling of each energy storage. The shared energy storage operator can realize the collaborative control of pumped storage, compressed air energy storage, flywheel energy storage, and various electrochemical energy storage through intelligent communication technology. The shared energy storage operator obtains the idle capacity available for frequency modulation of each energy storage unit, as well as the cost and unit parameters of each unit in advance, and performs aggregation and analysis on these information, and calculates the declared capacity and declared price of the shared energy storage cluster in the day-ahead frequency modulation market. After the day-ahead bidding of the shared energy storage is completed and the winning amount is determined, the shared energy storage operator optimizes the scheduling of each energy storage in the cluster according to the day-ahead frequency modulation winning amount. When the shared energy storage operator directly purchases the idle capacity of each energy storage unit, the shared energy storage obtains the income in the frequency modulation market, which is directly attributed to the shared energy storage operator; when the shared energy storage operator cooperates with each energy storage owner by signing a medium and long-term contract, the income obtained in the frequency modulation market needs to be fairly distributed according to the actual output of each energy storage.

[0038] According to one embodiment of the present application, the market participants of the frequency modulation auxiliary service market include the power dispatch center and a plurality of shared energy storages and thermal power units. That is, the market transaction participants participating in the frequency modulation auxiliary service market include a plurality of (one or more) shared energy storages and a plurality of thermal power units. Further, in this embodiment, the market transaction participants participating in the day-ahead frequency modulation market include at least one shared energy storage and at least one thermal power unit.

[0039] Finally, the operating state of the energy storage, the unit frequency modulation cost of the energy storage, and the comprehensive frequency modulation performance index are described.

[0040] 1) Operating state of energy storage

[0041] The SOC (State of Charge) of the energy storage represents the state of charge of the energy storage, also known as the remaining capacity. It represents the ratio of the remaining capacity of the energy storage after a period of use or long-term storage to its rated capacity, commonly expressed in percentage, and its value range is 0-1. When SOC=0, it means that the energy storage has no available capacity, and when SOC=1, it means that the energy storage is in a full charge state. In short, SOC is used to reflect the remaining capacity of the energy storage. In some embodiments, it can be calculated by the following formula.

[0042]

[0043] In the formula, SOC i , t represents the state of charge (%) of the energy storage i (or energy storage unit i, representing any energy storage) at time period t, represents the remaining capacity (MW) of the energy storage i at time period (t-1), represents the frequency modulation capacity (MWh) of the energy storage i at time period t, respectively represent the charging efficiency and discharging efficiency of the energy storage i (%), represents the rated capacity of the energy storage i in the current life under full charge (MWh).

[0044] SOH (State of Health) of the energy storage, i.e., the health status of the energy storage. It represents the ratio of the storage capacity of the energy storage in the current full charge state to the storage capacity of the energy storage in the brand-new state. This value can be defined and calculated from multiple perspectives, such as battery capacity, power, internal resistance, etc. When the SOH of the energy storage decreases to a certain extent, it can be considered that the energy storage has aged to a certain extent and may be close to the end of life (EOL). Therefore, SOH is an index describing the current health status of the energy storage and can be used to predict the time when the energy storage reaches EOL, so as to carry out corresponding maintenance and management.

[0045] The calculation methods of the electrochemical energy storage SOH include the energy accumulation method, the internal resistance measurement method, the open circuit voltage method and the capacity measurement method. Among them, the energy accumulation method is used for calculation and analysis in the embodiment. The energy accumulation method calculates the SOH by recording the total energy transmitted by the energy storage in the charging and discharging process, compares the current full charge capacity of the energy storage with its initial rated capacity, and then obtains the percentage of SOH. It should be noted that this method is based on the condition that the capacity attenuation degree of the battery is proportional to the total energy transmitted. Specifically, in some embodiments, the SOH can be calculated by the following formula.

[0046]

[0047] In the formula, SOH i，t represents the health status of the energy storage i in the t period, represents the rated capacity of the energy storage i in the brand-new state (MWh), and ε i represents the degradation rate of the energy storage i with the output capacity (%).

[0048] 2) Unit frequency regulation cost of the energy storage

[0049] Since the energy storage frequency regulation focuses on the change of the unit power, the unit mileage cost of the energy storage unit frequency regulation is used to represent the unit cost of the energy storage frequency regulation in the embodiment. The unit fixed cost of the energy storage frequency regulation is calculated by calculating the total life cycle cost and the total life cycle frequency regulation mileage of the energy storage, and the unit variable cost of the energy storage frequency regulation is calculated based on the actual operation cost of the energy storage. The sum of the two is the unit mileage cost of the energy storage frequency regulation, which is as follows.

[0050] Unit fixed cost:

[0051] The total life cycle cost of the energy storage includes the initial investment cost of the energy storage at the construction of the project, the annual operation and maintenance cost and replacement cost during the actual operation, and the recycling cost at the end of the life of the project. In some embodiments, the total fixed cost of the energy storage power station in the whole life cycle can be calculated by taking the time when the energy storage power station is put into operation as the starting point of the conversion, Y being the life cycle, and the total fixed cost of the energy storage (any energy storage) in the whole life cycle being C may be represented by the following formula.

[0052]

[0053] In the formula, represents the total fixed cost of the energy storage (any energy storage) in the whole life cycle, C inv represents the initial investment cost of the energy storage, specifically including the total cost (ten thousand yuan) generated by design, hardware, software, engineering, procurement, construction, etc., C OM represents the annual operation and maintenance cost of the energy storage (ten thousand yuan), C R represents the annual replacement cost of the energy storage (ten thousand yuan), C Rec represents the recycling cost of the energy storage (ten thousand yuan), r represents the interest rate (% or discount rate), and y represents the service life of the energy storage.

[0054] The unit mileage cost of the frequency modulation of the energy storage can be calculated by averaging the total life cycle cost of the energy storage to the total frequency modulation mileage of the energy storage in the whole life cycle, that is, the ratio of the total investment of the energy storage power station to the total frequency modulation mileage of the energy storage power station, which can be specifically seen from the following formula.

[0055]

[0056] In the formula, C D represents the unit fixed cost of the energy storage (any energy storage) (yuan / MW), S sum represents the total frequency modulation mileage of the energy storage power station (that is, the energy storage) in the whole life cycle (MW), N c represents the effective frequency modulation response times of the energy storage in the whole life cycle, S mil represents the frequency modulation mileage of the average frequency modulation (MW), and a represents the effective AGC frequency modulation response coefficient of the energy storage power station, and a ≤ 1, wherein a is related to the type of the frequency modulation actually participated by the energy storage and the proportion of the dispatching of the energy storage, and in an ideal case, a tends to 1. N c may be calculated by the following formula.

[0057]

[0058] In the formula, ψ represents the annual operation proportion of the energy storage power station (%); t eff represents the duration of the effective frequency modulation response of the energy storage power station (min), t eff the value is related to the application scenario, and the AGC auxiliary frequency modulation is generally 0.5-3 min; t intis the interval time (min) representing the effective frequency modulation response of the energy storage, which is generally tens of seconds to several minutes; Y represents the service life (years) of the energy storage system, wherein Y is related to the depth of discharge (DOD) of the energy storage frequency modulation system during operation and the duration t of the effective frequency modulation response of the energy storage system eff The energy storage participates in frequency modulation, which belongs to short-time high-frequency low-depth charging and discharging, and the service life of the system cycle is much higher than the service life under the full charging and discharging state.

[0059] Unit variable cost:

[0060] The actual variable cost of the energy storage during operation when participating in frequency modulation includes the charging cost, the wear cost of mechanical equipment, or the cycle life attenuation cost (determined according to the type of energy storage) of electrochemical energy storage. Specifically, in some embodiments, the total variable cost of one energy storage t period of frequency modulation Can be expressed as follows.

[0061]

[0062] In the formula, C C，t represents the charging cost (ten thousand yuan) of the energy storage t period, C Mn，t represents the wear cost (ten thousand yuan) of the energy storage t period, which needs to be distinguished according to the specific type of energy storage.

[0063] Based on this, the unit variable cost C v of one energy storage t period can be expressed as follows.

[0064]

[0065] In the formula, P t represents the actual frequency modulation output mileage of the energy storage t period.

[0066] In summary, according to the unit fixed cost and the unit variable cost of the energy storage frequency modulation, the unit cost mc of the energy storage frequency modulation can be obtained, which can be seen in the following formula.

[0067] mc=C D +C v

[0068] 3) Comprehensive frequency modulation performance index of energy storage

[0069] The comprehensive frequency modulation performance index covers response speed, regulation accuracy, duration and energy conversion efficiency of the energy storage system. The indexes can not only reflect the ability of the energy storage frequency modulation technology, but also are important basis for evaluating whether the energy storage frequency modulation technology can meet the frequency modulation demand of the power system. According to an embodiment of the present application, the comprehensive frequency modulation performance index of the energy storage can be calculated by the response speed, regulation accuracy and response time in the actual frequency modulation process of the energy storage, and the specific calculation formula is as follows: when the calculated values of K1, K2 and K3 are less than 0.1, 0.1 is taken.

[0070] K p = K1 x K2 x K3

[0071] In the formula, K p represents the comprehensive frequency modulation performance index of the energy storage, K1 represents the regulation rate index, K2 represents the regulation accuracy index, and K3 represents the response time index.

[0072] The regulation rate, regulation accuracy and response time are described in turn as follows.

[0073] The regulation rate refers to the rate of the unit responding to the set point instruction, which can be divided into the rising rate and the falling rate, and the specific calculation process is as follows.

[0074] The actual regulation rate can be calculated according to the following formula.

[0075]

[0076] In the formula, v i，j represents the jth regulation rate of the energy storage unit i (MW / min), represents the output of the energy storage unit i at the end of the jth frequency modulation (MW), Si，j represents the output of the energy storage unit i at the start of the jth frequency modulation (MW), represents the time at the end of the jth frequency modulation of the energy storage unit i, Si，j represents the time at the start of the jth frequency modulation of the unit i, di，j represents the critical point power of the jth regulation start-stop grinding of the unit i (MW), di，j represents the actual consumption time of the jth regulation start-stop grinding of the unit i (min).

[0077] It can be seen that when the unit does not meet the typical frequency modulation set point control process (fails to enter the target dead zone), the regulation rate is the active variation amount of the unit output at the end of the instruction minus the output at the time of crossing the dead zone, divided by the required time.

[0078] After the actual regulation rate is obtained, the regulation rate regulation index can be calculated according to the following formula:

[0079]

[0080] wherein, represents the jth frequency regulation rate evaluation index of the energy storage unit i, v N，i represents the standard regulation rate (MW / min) of the unit i, wherein, if if the calculated value is less than 0.1, 0.1 is taken.

[0081] In addition, if the unit enters a deep regulation working condition below 50% of the rated output, the frequency regulation rate requirement is 80% of the conventional regulation.

[0082] The regulation accuracy refers to the difference between the actual output and the set point output after the unit responds stably. The absolute value of the difference between the actual output and the instruction is integrated, and then the integral is divided by the integral time, so that the regulation deviation amount of the period can be obtained. See the following formula for details.

[0083]

[0084] wherein, ΔP i，j represents the jth frequency regulation deviation amount of the energy storage unit i, P i，j (t) represents the actual output (MW) at period t, P i，j represents the set point instruction value at the period, T Ei，j represents the end point of the period of the jth frequency regulation of the energy storage unit i, T Si，j represents the start point of the period of the jth frequency regulation of the energy storage unit i.

[0085] If the unit fails to enter the target dead zone, the regulation accuracy is the minimum value of the deviation between the actual output and the target output in the period from crossing the same direction dead zone to the end time of the instruction. See the following formula for calculation.

[0086]

[0087] wherein, represents the jth frequency regulation accuracy index of the energy storage unit i, δ represents the regulation allowed deviation amount (%), which is 1% of the rated active power of the unit. When the unit enters a deep regulation working condition below 50% of the rated output, the frequency regulation accuracy requirement is 125% of the conventional regulation.

[0088] The response time refers to the time taken by the unit to reliably cross the frequency regulation dead zone in the same direction as the regulation direction at the original output point after the EMS system issues an instruction. In some embodiments, the time difference between upward and downward regulation, and the unit response time can be calculated in turn by the following formulas.

[0089]

[0090]

[0091]

[0092] In the formula, Tij represents the response time index of the jth frequency modulation of the energy storage unit i, T0 and T1 represent the start reaction time before the output of the upward frequency modulation and the end reaction time of the start output, respectively, T5 and T6 represent the start reaction time before the output of the downward frequency modulation and the end reaction time of the start output, respectively, Tij represents the reaction time of the jth upward frequency modulation of the unit i, Tij represents the reaction time of the jth downward frequency modulation of the unit i, t i，j Tij represents the response time of the jth frequency modulation of the unit i, t s Tij represents the standard response time. In addition, the frequency modulation response time of the thermal power unit should be less than 1 min. When the unit enters the deep regulation working condition below 50% of the rated output, the frequency modulation response time is 125% of the conventional unit.

[0093] So far, it is clear that the operation mode of shared energy storage, the market subject when shared energy storage participates in the frequency modulation market, the unit cost of energy storage frequency modulation, and the comprehensive frequency modulation performance index of energy storage are known. Next, the energy storage scheduling method 200 of the shared energy storage participating in the frequency modulation auxiliary service market of the application is described. In this embodiment, the frequency modulation auxiliary service market is further referred to as the day-ahead frequency modulation market. As shown in the formula, Figure 2 The method 200 starts from 210. In 210, the basic parameters are obtained.

[0094] According to one embodiment of the application, the basic parameters include the available capacity, available mileage, capacity bid, mileage bid of each shared energy storage, the available capacity, available mileage, capacity bid, mileage bid of each thermal power unit, the capacity demand, mileage demand, capacity bid interval, mileage bid interval of the power dispatching center, and the basic information of each thermal power unit and each energy storage unit. Of course, if other market subjects are included, the basic parameters should also include the available capacity, available mileage, capacity bid, mileage bid of the subject, such as gas turbines, integrated energy suppliers, etc.

[0095] Subsequently, entering 220, a master-slave game model of the shared energy storage day-ahead frequency modulation is constructed with the power dispatch center as the master and the shared energy storage and the thermal power unit as the slave, with the minimum total dispatch cost of the power dispatch center as the upper target and the maximum day-ahead frequency modulation benefit of each shared energy storage and thermal power unit as the lower target. In this model, the Stackelberg master-slave game method can be used to construct an external master-slave game model of the shared energy storage participating in the day-ahead frequency modulation market with the power dispatch center as the leader and the shared energy storage and the thermal power unit as the follower. It should be noted that if other market subjects such as gas turbines and integrated energy suppliers are also included in some embodiments, the lower target should also include the maximum day-ahead frequency modulation benefit of the subject.

[0096] Specifically, according to one embodiment of the present application, the master-slave game model of the shared energy storage day-ahead frequency modulation can be constructed in the following way.

[0097] Firstly, according to the winning capacity and winning mileage of each shared energy storage and thermal power unit in each period of the day-ahead frequency modulation market and the capacity clearing price and mileage clearing price of each period of the day-ahead frequency modulation market, the total dispatch cost of the power dispatch center is determined, and a dispatch center day-ahead frequency modulation cost model is constructed with the minimum total dispatch cost as the first objective function.

[0098] The total dispatch cost of the power dispatch center includes the cost of purchasing frequency modulation capacity and the cost of purchasing frequency modulation mileage. Based on this, in some embodiments, the first objective function can be specifically as follows:

[0099]

[0100] wherein F L represents the total dispatch cost of the power dispatch center, represents the capacity clearing price (yuan / MWh) of each bidding subject in the t period of the day-ahead frequency modulation market, represents the mileage clearing price (yuan / MW) of each bidding subject in the t period of the day-ahead frequency modulation market, represents the winning capacity (MWh) of the shared energy storage m in the t period of the day-ahead frequency modulation market, represents the winning mileage (MW) of the shared energy storage m in the t period of the day-ahead frequency modulation market, represents the winning capacity (MWh) of the thermal power unit n in the t period of the day-ahead frequency modulation market, represents the winning mileage (MW) of the thermal power unit n in the t period of the day-ahead frequency modulation market, M represents the number of shared energy storages participating in the day-ahead frequency modulation market, i.e., there are M energy storage clusters participating in the day-ahead frequency modulation market, N represents the number of thermal power units participating in the day-ahead frequency modulation market, i.e., there are N thermal power units participating in the day-ahead frequency modulation market, and T represents the total number of periods, i.e., one day is divided into T periods.

[0101] Further, in order to construct the day-ahead frequency regulation cost model of the dispatch center, the supply and demand of the units and the dispatch center and the output of each unit need to be constrained, including: the capacity constraint and the mileage constraint of each shared energy storage, the capacity constraint and the mileage constraint of each thermal power unit, and the frequency regulation supply and demand balance constraint of the power dispatch center and the shared energy storage and the thermal power unit. Among them, in order to facilitate description, the above constraints are referred to as the first constraint condition. The constraints in the first constraint condition are described below.

[0102] The frequency regulation supply and demand balance constraint: this constraint indicates that the total capacity bid amount of all energy storage clusters and thermal power units in the t period is consistent with the total capacity demand amount of the dispatch center in the t period, and the mileage balance constraint is the same. Among them, the capacity balance constraint and the mileage balance constraint are as follows.

[0103]

[0104]

[0105] In the formula, represents the total capacity demand amount (MWh) of the system in the t period, represents the total mileage demand amount (MW) of the system in the t period.

[0106] The capacity and mileage constraints of the shared energy storage: this constraint indicates that the capacity bid amount and the mileage bid amount of the shared energy storage cannot exceed the required range of the shared energy storage, which is as follows.

[0107]

[0108]

[0109] In the formula, represents the maximum capacity output (MWh) of the energy storage cluster m (i.e., the shared energy storage m), represents the historical frequency regulation mileage call coefficient (frequency regulation mileage multiplier) of the energy storage cluster m, represents the maximum value of the frequency regulation mileage that can be called by the energy storage cluster m (MW).

[0110] The capacity constraint and the mileage constraint of the thermal power unit: this constraint indicates that the capacity and mileage bid amount of the thermal power unit cannot exceed the required range of the unit, which is as follows.

[0111]

[0112]

[0113] In the formula, represents the maximum capacity output of the thermal power unit n, a frequency modulation mileage multiplier of the thermal power unit n, a maximum value of the frequency modulation mileage that the thermal power unit n can be called.

[0114] At this point, the day-ahead frequency modulation cost model of the dispatch center is constituted by the first objective function and the first constraint condition.

[0115] Then, according to the total income obtained by each thermal power unit in the day-ahead frequency modulation market and the frequency modulation cost and start-stop cost thereof, the day-ahead frequency modulation income of each thermal power unit is determined, and a dispatch operation model of each thermal power unit is constructed with the maximum day-ahead frequency modulation income of each thermal power unit as a second objective function.

[0116] The day-ahead frequency modulation income of the thermal power unit, that is, the net income (or frequency modulation compensation income) obtained by the thermal power unit in the day-ahead frequency modulation market, is constituted by the frequency modulation auxiliary service market income f G , the frequency modulation cost and the start-stop cost . Based on this, in some embodiments, the second objective function can be specifically as follows:

[0117]

[0118]

[0119]

[0120] Wherein, F G represents the day-ahead frequency modulation income of the thermal power unit (that is, any thermal power unit), f G represents the total income obtained by the thermal power unit in the day-ahead frequency modulation market, n G represents the comprehensive frequency modulation performance index of the thermal power unit, represents the frequency modulation cost of the thermal power unit, represents the start-stop cost of the thermal power unit, represents the out-of-clear capacity (MWh) of the thermal power unit in the day-ahead frequency modulation market t period, represents the out-of-clear mileage (MW) of the thermal power unit in the day-ahead frequency modulation market t period, represents the capacity out-of-clear price (yuan / MWh) of the thermal power unit in the day-ahead frequency modulation market t period, represents the mileage out-of-clear price (yuan / MW) of the thermal power unit in the day-ahead frequency modulation market t period, and MC' represents the unit frequency modulation cost of the thermal power unit.

[0121] Further, in order to construct the dispatching operation model of the thermal power unit, the range of its offer, the declared capacity, the mileage and the power variation amount in unit time need to be constrained, specifically including: the frequency modulation declared amount constraint of the thermal power unit, the frequency modulation declared price constraint and the climbing constraint. In order to facilitate the description, the above constraints are referred to as the second constraint condition. The constraints in the second constraint condition are described below.

[0122] The frequency modulation declared amount constraint of the thermal power unit: when the thermal power unit declares the capacity and mileage in the frequency modulation market, it cannot exceed the maximum value of the declared amount, specifically, the capacity declared amount constraint and the mileage declared amount constraint can be seen in the following formula.

[0123]

[0124]

[0125] In the formula, represents the frequency modulation capacity declared by the thermal power unit at the t period (MWh), represents the frequency modulation mileage declared by the thermal power unit at the t period (MW), represents the maximum frequency modulation capacity declared amount of the thermal power unit (MWh), G represents the frequency modulation mileage multiplier of the thermal power unit, represents the maximum available frequency modulation mileage of the thermal power unit (MW).

[0126] The frequency modulation declared price constraint of the thermal power unit: the thermal power unit makes an offer according to its own power generation cost, but the declared price cannot exceed the declared price range issued by the dispatching trading center, specifically as follows.

[0127]

[0128]

[0129] In the formula, represents the capacity offer of the thermal power unit at the t period (yuan / MWh), represents the mileage offer of the thermal power unit at the t period (yuan / MW), respectively represent the lower limit and the upper limit of the capacity offer range issued by the dispatching trading center (yuan / MWh), respectively represent the lower limit and the upper limit of the mileage offer range issued by the dispatching trading center (yuan / MW).

[0130] The ramping constraint of the thermal power unit: It is a limit to the power change amount of the unit in a unit time, and is usually expressed as a constraint on the increase or decrease rate of the unit output. Specifically, the ramping constraint specifies the maximum power value that the thermal power unit can increase or decrease in a unit time (such as per minute or per hour). This limit can ensure that the power output of the unit does not change too drastically when responding to changes in system load, thereby helping to maintain the stability and reliability of the power system. The ramping constraint of the thermal power unit can be specifically seen in the following formula.

[0131]

[0132] In the formula, ΔP u represents the maximum value of the output change (MW) allowed by the thermal power unit in a frequency modulation period, represents the discharge mileage (MW) of the thermal power unit in the day-ahead frequency modulation market (t-1) period.

[0133] So far, the dispatching and running model of the thermal power unit is composed of the second objective function and the second constraint condition.

[0134] Next, according to the total income obtained by each shared energy storage in the day-ahead frequency modulation market and its frequency modulation cost, the day-ahead frequency modulation income of each shared energy storage is determined, and the maximum day-ahead frequency modulation income of each shared energy storage is taken as the third objective function to build the dispatching and running model of each shared energy storage.

[0135] Among them, the day-ahead frequency modulation income of the shared energy storage, i.e. the net income obtained by the shared energy storage in the day-ahead frequency modulation market, is composed of the frequency modulation auxiliary service market income f ES and the cost C ES of providing frequency modulation service. The frequency modulation auxiliary service market income includes capacity income and mileage income. Based on this, in some embodiments, the third objective function can be specifically as follows:

[0136] max F ES = f ES · n ES - C ES

[0137]

[0138]

[0139] Among them, F ES represents the day-ahead frequency modulation income of the shared energy storage, f ES represents the total income obtained by the shared energy storage in the day-ahead frequency modulation market, n ES represents the comprehensive frequency modulation performance index of the shared energy storage, C ES represents the frequency modulation cost of the shared energy storage, the capacity clearing price (yuan / MWh) of the day-ahead frequency modulation market t period, the mileage clearing price (yuan / MW) of the day-ahead frequency modulation market t period, the winning capacity (MWh) of the shared energy storage in the day-ahead frequency modulation market t period, the winning mileage (MW) of the shared energy storage in the day-ahead frequency modulation market t period, and MC" represents the unit frequency modulation cost (yuan / MW) of the shared energy storage.

[0140] Further, in order to construct the dispatch operation model of the shared energy storage, the bid price, bid quantity and charge-discharge power of the energy storage cluster participating in the frequency modulation market need to be constrained, which specifically includes the frequency modulation bid quantity constraint, frequency modulation bid price constraint and charge-discharge power constraint of the shared energy storage. For convenience of description, the above constraints are referred to as the third constraint condition. The constraints in the third constraint condition are described below.

[0141] The frequency modulation bid price constraint of the shared energy storage: the capacity bid and mileage bid of the shared energy storage need to follow the bid interval requirements issued by the dispatch trading center. Specifically, the bid interval of the capacity and mileage can be seen from the following formula.

[0142]

[0143]

[0144] In the formula, respectively represent the upper and lower limits of the energy storage capacity bid (yuan / MWh), represents the capacity bid of the energy storage cluster in the t period (yuan / MWh), respectively represent the upper and lower limits of the energy storage mileage bid (yuan / MW), represents the mileage bid of the energy storage cluster in the t period (yuan / MW).

[0145] The frequency modulation bid quantity constraint of the shared energy storage: the frequency modulation capacity and mileage declared by the energy storage cluster in each period must be within the range of its actual available capacity and mileage, which is specifically as follows.

[0146]

[0147]

[0148] In the formula, represents the frequency modulation capacity (MWh) declared by the energy storage cluster in the t period, represents the frequency modulation mileage (MW) declared by the energy storage cluster in the t period, represents the maximum available capacity (MWh) of the energy storage cluster for frequency modulation, ES represents the frequency modulation mileage multiplier of the energy storage cluster, The maximum frequency regulation mileage (MW) indicates that the energy storage cluster can be called.

[0149] Charge-discharge power constraint: the charge-discharge power of the energy storage participating in frequency regulation cannot exceed the maximum power of the system, and the energy storage unit cannot charge and discharge at the same time, specifically, the power constraints of its charging and discharging can be seen in the following formula.

[0150]

[0151]

[0152] In the formula, u t The 0 / 1 variable of the energy storage charge-discharge state, ut=1 indicates that the energy storage is in the charging state, ut=0 indicates that the shared energy storage is in the discharging state, R t , R ch，max , R dis，max respectively represent the maximum charge power and discharge power (MW) of the energy storage, respectively represent the charge power and discharge power of the shared energy storage at time t.

[0153] So far, the third objective function and the third constraint condition constitute the scheduling operation model of the shared energy storage.

[0154] Finally, taking the scheduling center day-ahead frequency regulation cost model as the upper model, and taking the scheduling operation model of each thermal power unit and the scheduling operation model of each shared energy storage as the lower model, a master-slave game model of shared energy storage day-ahead frequency regulation is constructed.

[0155] So far, the master-slave game model of shared energy storage day-ahead frequency regulation has been constructed. Subsequently, at 230, the obtained basic parameters are input into the constructed master-slave game model for solving, to obtain the capacity bid amount, mileage bid amount and clearing price of each shared energy storage and thermal power unit in the day-ahead frequency regulation market. Similarly, it needs to be explained that if other market subjects such as gas turbines, integrated energy suppliers, etc. are also included in some embodiments, the solving result also includes the capacity bid amount, mileage bid amount, clearing price and revenue value of the subject in the day-ahead frequency regulation market.

[0156] In some embodiments, when solving the constructed master-slave game model, the solving direction of the lower layer model and the upper layer model can be unified by first constructing a Lagrange function using duality theory to convert the maximization problem of the lower layer into a single-objective minimization problem; then, the original multi-objective optimization problem can be converted into a single-objective solving problem by adding the converted target function of the lower layer to the target function of the upper layer; then, the constraints of the lower layer are converted into the constraints of the single-objective problem based on the complementary relaxation theory of KKT; finally, the Gurobi toolbox in Python is used for solving to obtain the capacity and mileage in the day-ahead frequency regulation market, the clearing price and the income of each unit. Figure 5 In addition, the function solving direction conversion by constructing a Lagrange function using duality theory and the conversion of the constraints of part of the target functions in the model into the constraints of the total target problem based on the complementary relaxation theory of KKT are relatively mature techniques in the field, and will not be described here.

[0157] It can be seen that, in this embodiment, the shared energy storage and thermal power units are selected as the frequency regulation bidding subjects, and an external game model of shared energy storage participating in day-ahead frequency regulation is constructed. Considering that the market subjects when the shared energy storage participates in the external game include the power dispatching and trading center, thermal power units and energy storage, this embodiment uses the method of Stackelberg master-slave game, takes the power dispatching center as the upper leader, constructs an upper layer model with the minimum total dispatching cost of the power dispatching center as the target, and takes the energy storage and thermal power units as followers, and constructs a lower layer model with the maximum income of the units participating in the frequency regulation market as the target. When solving, the target function of the lower layer is converted into a single-objective function for solving the maximum based on the KKT condition and duality theory, the lower layer problem is converted into the constraints of the upper layer problem by constructing the Lagrange function of the lower layer model, the adjusted target function is linearly converted by using Big-M, and the Gurobi optimization software in Python is used for solving, and finally the capacity and mileage in the day-ahead frequency regulation market, the clearing price and the income of each unit are calculated.

[0158] After obtaining the capacity of each time period, the mileage of the winning bid, the clearing price, and the revenue of the shared energy storage in the day-ahead frequency modulation market, the shared energy storage centralized control platform needs to reasonably allocate the winning bid of frequency modulation according to the characteristics of each energy storage to ensure that the cluster and the internal energy storage obtain the maximum benefit under the premise of high-quality completion of the grid frequency modulation task. Based on this, in some embodiments, the method of cooperative game can be used to realize the optimal scheduling of each energy storage in the shared energy storage cluster to match the most suitable energy storage scheduling set for different frequency modulation periods, as follows.

[0159] In 240, an internal cooperative game model for the day-ahead frequency modulation of each shared energy storage is constructed with the minimum total frequency modulation cost and the optimal total frequency modulation performance of each energy storage as the target. Specifically, the model can be constructed in the following way.

[0160] For each shared energy storage, the total frequency modulation cost of each energy storage aggregated by the shared energy storage in each time period is determined according to the mileage of the winning bid of each energy storage in each time period and the unit mileage price of each energy storage frequency modulation, and the minimum total frequency modulation cost is taken as the fourth objective function. The total frequency modulation cost refers to the total frequency modulation cost of all energy storages in the shared energy storage in all frequency modulation time periods. Based on this, in some embodiments, the fourth objective function can be as follows:

[0161]

[0162] In the formula, C FM represents the total cost of day-ahead frequency modulation (yuan) of a shared energy storage, i.e., the total frequency modulation cost of each energy storage aggregated by the shared energy storage, T represents the division of one day into T frequency modulation time points, I represents the number of energy storages aggregated in the shared energy storage, i.e., there are I energy storage subjects in the energy storage cluster, represents the mileage of winning bid (MW) of energy storage i in time period t, represents the unit mileage price (yuan / MW) of energy storage i frequency modulation.

[0163] Then, the total frequency modulation performance of each energy storage aggregated by the shared energy storage is determined according to the mileage of the winning bid of each energy storage in each time period and the historical comprehensive frequency modulation performance index of each energy storage, and the maximum total frequency modulation performance is taken as the fifth objective function.

[0164] In the allocation of frequency modulation capacity in the shared energy storage, the comprehensive frequency modulation performance indicators of the adjustment rate, adjustment accuracy and response time of each energy storage need to be considered. The adjustment rate reflects the speed of the energy storage system in responding to the frequency modulation instruction, which is crucial to ensure the frequency stability of the power system. The adjustment accuracy measures the deviation between the actual output of the energy storage system and the required output of the frequency modulation instruction, which is directly related to the pros and cons of the frequency modulation effect. The response time is the time from receiving the frequency modulation instruction to starting the actual adjustment of the output, which determines how quickly the energy storage system can respond to the demand changes of the power system. Therefore, in the allocation of frequency modulation capacity, these indicators need to be considered comprehensively to ensure that each energy storage system can obtain a reasonable allocation of frequency modulation capacity according to its performance characteristics, thereby realizing stable and efficient operation of the power system. Such an allocation method not only can fully exert the advantages of each energy storage system, but also can improve the frequency modulation capacity of the entire power system, providing a strong guarantee for the stable operation of the power market.

[0165] In this embodiment, the product of the historical comprehensive frequency modulation performance parameter of the energy storage and the scalar in each period is taken as the comprehensive frequency modulation performance of the energy storage participating in the day-ahead frequency modulation, and therefore the fifth objective function can be specifically as follows.

[0166]

[0167] In the formula, K FM represents the comprehensive frequency modulation performance of all energy storages in day-ahead frequency modulation, i.e., the total frequency modulation performance of the aggregated energy storages of the shared energy storage, represents the scalar (MW) of the energy storage i in the t period, K i represents the historical comprehensive frequency modulation performance indicator of the energy storage i, in specific embodiments, the comprehensive frequency modulation performance indicator of a typical day of the energy storage i can be selected as the historical comprehensive frequency modulation performance indicator of the energy storage i, or the daily average of the comprehensive frequency modulation performance indicators of a month of the energy storage i can be selected as the historical comprehensive frequency modulation performance indicator of the energy storage i, of course, this is only an example, and the present application is not limited in this regard.

[0168] Finally, the fourth objective function and the fifth objective function are combined, and the capacity output, mileage output, charging and discharging power, state of charge, state of health of the aggregated energy storages of the shared energy storage and the capacity supply-demand balance and mileage supply-demand balance of the shared energy storage are constrained to construct an internal cooperative game model of the shared energy storage.

[0169] Supply-demand balance constraint: the frequency modulation capacity sum and the mileage sum of all energy storage subjects in the t period are equal to the winning capacity sum and the mileage of the energy storage cluster in the period, specifically, the capacity balance constraint and the mileage balance constraint of the energy storage can be seen in the following formula.

[0170]

[0171]

[0172] wherein, denotes the capacity output (MWh) of the energy storage unit i at time period t, denotes the mileage output (MW) of the energy storage unit i at time period t, denote the capacity and mileage bid of the shared energy storage in the day-ahead frequency regulation market at time period t, respectively.

[0173] Energy storage output constraint: the capacity output and the mileage output of the energy storage unit i at time period t cannot exceed the maximum limit of the energy storage output. Specifically, the capacity output constraint and the mileage output constraint of the energy storage unit can be seen in the following formula.

[0174]

[0175]

[0176] wherein, denotes the maximum frequency regulation capacity output (MWh) of the energy storage i, denotes the frequency regulation mileage multiplier of the energy storage i, denotes the maximum frequency regulation mileage (MW) of the energy storage i.

[0177] Charge and discharge power constraint: the charge and discharge power of each energy storage unit cannot exceed its system power limit, and at the same time, the energy storage can only be charged or discharged at the same time, therefore, the charge and discharge power constraint of the energy storage can be seen in the following formula.

[0178]

[0179] wherein, denote the discharge power and the charge power (MW) of the energy storage i at time period t, respectively; denote the 0-1 variable of the energy storage charge and discharge, respectively, and denote the charge and discharge state of the energy storage i at time period t, taking 1 indicates that the energy storage i is in the discharging state at time period t, taking 0 indicates that the energy storage i is not in the discharging state at time period t, taking 1 indicates that the energy storage i is in the charging state at time period t, taking 0 indicates that the energy storage i is not in the charging state at time period t; i cap，dis，max 、 denote the maximum discharge and charge power (MW) allowed by the energy storage i, respectively.

[0180] SOC constraint: the SOC of the energy storage can be used to determine the available capacity of the unit in the next period when participating in frequency modulation, and the unit cannot be called again when the SOC of the energy storage exceeds the system limit value of the unit. Specifically, the SOC constraint of the energy storage unit can be seen in the following formula.

[0181] SOC min，i ≤SOC i，t ≤SOC max，i

[0182] In the formula, SOC i，t represents the SOC of the energy storage i in the t period, SOC max，i , SOC min，i respectively represent the upper limit and lower limit of the SOC of the energy storage i.

[0183] SOH constraint: the SOH of the energy storage is the ratio of the capacity of the battery from full state to the capacity discharged at a certain rate under standard conditions to the rated capacity (actual initial capacity), which reflects the health state of the battery, and when the health state of the energy storage unit exceeds or is lower than the limit value of the system, the unit cannot be called again. Specifically, the health state constraint of the energy storage can be seen in the following formula.

[0184] SOH min，i ≤SOH i，t ≤SOH max，i

[0185] In the formula, SOH i，t represents the SOH of the energy storage i in the t period, SOH min，i , SOH max，i respectively represent the lower limit and upper limit of the SOH of the energy storage i.

[0186] So far, the internal cooperative game model of the shared energy storage is constituted by the above constraint conditions, the fourth objective function and the fifth objective function. Next, enter 250, for each shared energy storage, according to the capacity bid amount, the mileage bid amount and the clearing price of each period in the day-ahead frequency modulation market, the internal cooperative game model of the shared energy storage is solved, and the dispatching result of each energy storage aggregated by the shared energy storage is obtained. Specifically, the dispatching result includes the capacity output and the mileage output of each energy storage in each period in the day-ahead frequency modulation market.

[0187] Among them, considering that the internal cooperative game model of the shared energy storage constructed belongs to a linear double objective optimization scheduling problem, therefore, the priority and weight of the two objectives can be established according to the importance of the cost and the frequency modulation performance when solving, the hierarchical sequence method is used to solve the above double objective programming problem, specifically, the Gurobi toolbox in Python can be used for solving, the solving process can be seen in Figure 6In addition, the layered sequence method is used to solve the double-target problem, which is a mature technology in the field, and will not be described in detail.

[0188] Further, after obtaining the scheduling results of each energy storage in the shared energy storage, according to an embodiment of the present application, the improved Shapely value method can be used to distribute the benefits of each energy storage in the shared energy storage.

[0189] Here, the premise of Shapely cooperative game and the traditional Shapely value calculation method are described first. First, regarding the premise of Shapely cooperative game. For a coalition N = {1, 2, 3,..., n} consisting of n members, S is a subset thereof, representing a combination. Assume that the cost of member i after distribution is R i , R(S) is the cost of combination S, R({i}) is the individual cost of member i without cooperation, and R(N) represents the cost of combination N, i.e. the cost of coalition N. Generally, a coalition that can maintain cooperation needs to meet three conditions: (1) individual rationality condition; (2) overall superadditive condition; (3) overall constraint condition. The three conditions meet the requirements of individual cost reduction, overall cost reduction, and total cost unchanged before and after distribution, respectively, which can be seen in the following formulas.

[0190] R i ≤R({i})

[0191]

[0192]

[0193] Second, regarding the traditional Shapely value calculation method. In the Shapely value method, the contribution of each participant is measured by comparing the total cost of cooperation when the participant participates in cooperation and does not participate in cooperation. Specifically, for each possible participant combination, the total cost of cooperation under the combination is calculated, and the marginal contribution of each participant to the combination cost is determined. Then, according to the probability of each participant appearing in all possible combinations and its corresponding marginal contribution, the Shapely value of each participant, i.e. the cost it should be distributed, is calculated.

[0194] According to the Shapely calculation method, first, a cooperative game coalition N containing each energy storage is constructed, which can be randomly formed according to the Shapely cooperative game theory (2 n-1) a combination mode, v represents a characteristic function, and v(Φ) = 0, assuming that other coalitions except the empty set are S, then v(S) is the total cost after the participants in the coalition S cooperate. Wherein, the Shapley value calculation method can be seen from the following formula.

[0195]

[0196] In the formula, The cost allocation value of the i-th subject is represented by |S i | represents the number of subjects in the coalition S, n represents the number of participants in the large coalition, v(S) represents the total cost of the coalition S, and v(S\{i}) represents the cost after removing i from the coalition S, The probability of the occurrence of the coalition S is represented by a weighted factor.

[0197] It can be seen that the traditional Shapley value method only considers the marginal contribution of each subject in different combination states, and does not consider the total capacity output and mileage output of each subject. Based on this, the application proposes to apply the traditional Shapley value method to allocate the cost of each energy storage unit, and simultaneously consider the actual capacity contribution degree and mileage contribution degree of each unit, and improve the original cost allocation factor from the capacity contribution degree and the mileage contribution degree. Then, the improved allocation factor is used to allocate the revenue of the shared energy storage participating in the day-ahead frequency modulation market. According to one embodiment of the application, the improved profit allocation factor of each energy storage unit in any shared energy storage can be calculated by the following formula.

[0198]

[0199] In the formula, R' d The profit allocation factor vector {R'1, R'2, R'3…R' d} composed of the improved profit allocation factors of d energy storages aggregated by the shared energy storage is represented by R d ω1, ω2, ω3 respectively represent the capacity output contribution degree, the mileage output contribution degree and the improvement weight coefficient of the original cost allocation factor, and ω1+ω2+ω3=1, The capacity output contribution degree vector composed of the capacity output contribution degrees of d energy storages aggregated by the shared energy storage is represented by τ d The mileage output contribution degree vector {τ1, τ2, τ3…τ d} composed of the mileage output contribution degrees of d energy storages aggregated by the shared energy storage is represented by d} and R d The original cost allocation factor vector {R1, R2, R3…R d} composed of the original cost allocation factors of d energy storages aggregated by the shared energy storage is represented by R d Specifically, R'1, R'2, R'3…R' d drespectively represent the profit distribution factors of the energy storages 1, 2, 3…d after improvement, respectively represent the capacity output contribution degrees of the energy storages 1, 2, 3…d, τ1, τ2, τ3…τ d respectively represent the mileage output contribution degrees of the energy storages 1, 2, 3…d, R1, R2, R3…R d respectively represent the original cost allocation factors of the energy storages 1, 2, 3…d.

[0200] Based on this, according to one embodiment of the present application, when the improved Shapely value method is used to distribute the benefits of each energy storage in the shared energy storage, for each shared energy storage, the improved profit distribution factor of each energy storage can be obtained by using the above formula according to the capacity output contribution degree, the mileage output contribution degree and the original cost allocation factor of each energy storage in the shared energy storage, and then the improved profit distribution factor is used to distribute the benefits of each energy storage in the shared energy storage. Specifically, in some embodiments, for each energy storage, the product of the improved profit distribution factor and the total benefit of the shared energy storage can be calculated, and this product is taken as the benefit of the energy storage.

[0201] Wherein, regarding the capacity output contribution degree and the mileage output contribution degree of each energy storage in the shared energy storage, according to one embodiment of the present application, it can be obtained by the following way. Specifically, for each energy storage in the shared energy storage: the ratio of the total capacity output of the energy storage (i.e. the sum of the capacity output of each period) to the total capacity output of the shared energy storage (i.e. the sum of the capacity output of each period, or the sum of the capacity mid-values of each period) is taken as the capacity output contribution degree of the energy storage; the ratio of the total mileage output of the energy storage (i.e. the sum of the mileage output of each period) to the total mileage output of the shared energy storage (i.e. the sum of the mileage output of each period, or the sum of the mileage mid-values of each period) is taken as the mileage output contribution degree of the energy storage. Of course, this is only an example, and other ways can also be used to obtain it, which is not limited by the present application. Regarding the original cost allocation factor, it can be obtained by using the traditional Shapely value method based on the above obtained capacity output and mileage output of each energy storage in each period in the day-ahead frequency regulation market. Wherein, the calculation of the cost allocation factor by using the Shapely value method is a relatively mature technology in the art, which will not be described here.

[0202] Thus, the optimized scheduling and benefit distribution of each energy storage in the shared energy storage cluster are completed. In addition, in order to verify the effectiveness of the proposed energy storage scheduling method for shared energy storages participating in the frequency regulation auxiliary service market, the present application also gives a specific example of Mengxi, which is described below.

[0203] 1) Basic parameters

[0204] In the master-slave game part of the shared energy storage participating in the frequency modulation market, in order to verify the effectiveness and rationality of the double-layer optimization model constructed, the application adopts 3 groups of different specifications of thermal power units and 2 groups of different specifications of energy storage clusters to participate in the day-ahead frequency modulation market for simulation verification. Specifically, taking 1h as a single scheduling period, the scheduling period is 24h, the frequency modulation mileage offer interval of the frequency modulation unit is 6-15 yuan / MW, the frequency modulation capacity compensation price is 60 yuan / MW, and generally the reported capacity of each unit in the frequency modulation market does not exceed 15% of the rated capacity of the unit. Among them, the related parameters and offer of the thermal power unit are shown in Table 1 below, and the related parameters and offer of the energy storage unit are shown in Table 2 below.

[0205] Table 1

[0206]

[0207] Table 2

[0208]

[0209] In the example analysis of the cooperative game model of each energy storage in the shared energy storage, this embodiment selects one group of pumped storage, compressed air energy storage, flywheel energy storage, lithium ion battery energy storage, lead-acid battery energy storage, sodium-sulfur battery energy storage and flow battery energy storage as the participating subject of cooperative game. Among them, the number and technical parameters of each energy storage are shown in Table 3 below.

[0210] Table 3

[0211]

[0212] The frequency modulation demand capacity of the system is generally 5% of the day-ahead predicted load, at the same time, the frequency modulation capacity-mileage ratio of the system is generally 7 to 10, in addition, in the calculation of the unit frequency modulation cost of each energy storage, the charging price takes the time-of-use price of the region as the input parameter. Among them, the system predicted load and frequency modulation capacity demand, mileage demand and time-of-use price randomly generated based on historical data can be referred to Figure 7 .

[0213] 2) Unit frequency modulation cost parameter setting of different types of energy storage

[0214] According to the unit frequency modulation cost model of the energy storage constructed above, the unit fixed cost, unit variable cost and total unit frequency modulation cost of each energy storage are calculated, and the specific calculation results are shown in Table 4 below.

[0215] Table 4

[0216]

[0217] It can be seen that the unit fixed cost and marginal cost of the three mechanical energy storage are obviously higher than that of the electrochemical energy storage, because the initial investment cost and operation and maintenance cost of pumped storage and compressed air energy storage are much higher than that of electrochemical energy storage; since only the charging cost and equipment wear cost or life decay cost are considered in calculating the unit variable cost, the charging unit price of each energy storage is uniform, and the equipment wear cost and life decay cost accounts for a small proportion, so the unit variable cost of each energy storage is not much different.

[0218] Among the three mechanical energy storages, the compressed air energy storage has the lowest charging and discharging efficiency and high operation and maintenance cost, so the unit fixed cost, unit variable cost and marginal cost of the compressed air energy storage are higher than those of the other two energy storages. The unit cost of flywheel energy storage is lower than that of the other two mechanical energy storages, but it has the highest self-discharge rate, so the flywheel energy storage is more suitable for short-term large-scale frequency modulation work. Pumped storage is currently widely used and mature in mechanical energy storage, and has advantages in energy market and auxiliary service market due to its large capacity and stable performance, but its unit frequency modulation cost in frequency modulation market is relatively high, so pumped storage is more used as peak shaving resource in auxiliary service market.

[0219] The unit frequency modulation cost of electrochemical energy storage as a whole is lower than that of mechanical energy storage, and the frequency modulation performance of electrochemical energy storage in frequency modulation market is better, so it is more widely used. Among the four electrochemical energy storages, the marginal cost of lithium ion battery is lower than that of the other three, because the market share of lithium ion battery in battery energy storage is larger, the application technology is more mature and safe, and the energy conversion efficiency is higher, so the lithium ion battery has realized the effect of reducing cost and increasing efficiency compared with other energy storages. The initial investment cost of lead-acid battery is also relatively low, so its unit fixed cost is low; the energy conversion efficiency of sodium-sulfur battery is higher, so its unit variable cost is lower, but the initial investment cost of sodium-sulfur battery is higher, there are safety hazards in high-temperature environment, and the operation and maintenance cost is also high, so its unit fixed cost is higher. The service life of liquid flow battery is longer, and the power capacity is high, so it is often used as backup power and renewable energy storage. The marginal cost of each energy storage is only a bidding factor for participating in the frequency modulation market, and the use amount cannot be reduced because of high cost, so the frequency modulation amount of energy storage should be allocated by considering the multiple performances of each energy storage.

[0220] 3) Shared energy storage master-slave game frequency modulation example analysis

[0221] Analysis of the winning situation of each unit: the winning capacity and winning mileage of energy storage and thermal power unit in the day-ahead frequency modulation market can be seen from Figure 8As can be seen from the figure, the two groups of energy storage occupy most of the frequency modulation capacity in the frequency modulation market. Among them, the first group of energy storage occupies 39.92% of the frequency modulation capacity and 35.32% of the frequency modulation mileage. The second group of energy storage occupies 28.77% of the frequency modulation capacity and 33.08% of the frequency modulation mileage. This is because although the energy storage has a higher price than the thermal power unit in the frequency modulation market, the thermal power unit has greater wear and tear when participating in frequency modulation, and it is more inclined to participate in the energy market to obtain more benefits, so the thermal power unit reports less frequency modulation available capacity in the frequency modulation market. Energy storage does not have this problem, and energy storage provides higher frequency modulation available capacity, so the probability of winning and the amount of winning are also relatively high. The larger the capacity of the energy storage, the smaller the total number of units dispatched by the dispatching center, and the simpler the operation. At the same time, energy storage relies on its own performance to occupy an absolute technical advantage in the frequency modulation market, and its historical comprehensive frequency modulation performance index is higher than that of thermal power. In order to maximize the demand for frequency modulation and reduce the intra-day frequency modulation deviation, the dispatching center also tends to dispatch units with good frequency modulation performance and lower cost.

[0222] Further, the winning capacity of energy storage one (C1) is significantly higher than that of energy storage two (C2), because the unit frequency modulation cost of energy storage one is lower than that of energy storage two, and the historical comprehensive frequency modulation performance index of the first group is higher than that of the second group. However, the frequency mileage multiplier of energy storage two is 15, while the frequency mileage multiplier of energy storage one is 13, so the mileage winning amount of energy storage two is significantly higher than that of energy storage one. In addition, the winning capacity of G1 is higher than that of G2 and G3 in the first 15 hours, and from 16 o'clock, the winning capacity of G2 reverses G1, and at the same time, the winning capacity of G3 also has an upward trend, but it has not exceeded G1 and G2 as a whole. The winning mileage of G1 is higher than that of G2 and G3 in most time periods. G1 occupies more frequency modulation capacity in thermal power units due to its lower frequency modulation cost. The frequency modulation cost of the three groups of thermal power units from low to high is G1

[0223] Analysis of the income of each unit: According to the capacity compensation price of the frequency modulation market in this area, each unit is compensated for capacity at 60 yuan / MW. The frequency modulation mileage bid of each unit from low to high is G3

[0224] Table 5

[0225]

[0226] This shows that the capacity benefit of each unit is significantly higher than the mileage benefit. This is because although the awarded capacity is much lower than the awarded mileage, the provisional capacity compensation price in this region, designed to encourage active participation in the frequency regulation market, is much higher than in other provinces. The ratios of capacity benefit to mileage benefit for each unit are 10.5, 8.08, 8.78, 9.04, and 11.07, respectively. The ratios for C1 and G3 are particularly high, indicating that these two units can actively reserve frequency regulation capacity to participate in the frequency regulation market; the larger the awarded capacity, the higher the benefit. Furthermore, the table shows that the two energy storage units have the highest awarded capacity and mileage, resulting in significantly higher benefits compared to other units. Figure 8 The results show that the mileage winning bids for the two energy storage groups are similar, but because the winning bid capacity for energy storage C1 is significantly higher than that for C2, the overall return for C1 is significantly higher than that for C2. Similarly, although the winning bid mileage for thermal power unit G2 is lower than that for G1 for most of the time, its overall winning bid capacity is basically the same as that for G1. Therefore, the total returns for G1 and G2 are not significantly different. Finally, because G3 has lower winning bids for both capacity and mileage than other units, its overall return is also relatively lower. However, its capacity-to-mileage return ratio is the highest. G3 can actively participate in the frequency regulation market by reducing unit operating costs and improving frequency regulation performance, and it has great potential to obtain higher returns in the frequency regulation market.

[0227] 4) Analysis of Cooperative Game Theory Examples within Energy Storage Clusters

[0228] Scheme Comparison Analysis: This embodiment considers both the cost and overall frequency regulation performance of shared energy storage frequency regulation. Therefore, to verify the effectiveness of the constructed dual-objective optimization model, this embodiment designed three sets of comparison schemes. The specific schemes are shown in Table 6 below. The total benefits and overall performance of energy storage cluster frequency regulation under the three comparison schemes are shown in Table 7 below.

[0229] Table 6

[0230]

[0231] Table 7

[0232]

[0233] The results of the three schemes show that, when considering only a single objective, Scheme 1 has a lower operating cost of 25,828.86 yuan than Scheme 2, and Scheme 2 has a higher frequency regulation performance of 326.8 yuan than Scheme 1. When Scheme 3 considers both objectives, its frequency regulation cost is slightly higher than Scheme 1, but much lower than that of Scheme 2. Furthermore, Scheme 3's frequency regulation performance is 125.69 yuan lower than Scheme 2, but 201.11 yuan higher than Scheme 1. Scheme 3 is close to the optimal value among the single-objective schemes in terms of both cost and frequency regulation performance. Therefore, when considering dual-objective scheduling planning, the results of Scheme 3 are feasible.

[0234] Analysis of the bidding results for each energy storage system: The capacity output and mileage output of each energy storage system within the shared energy storage system are as follows... Figure 9 As shown. From Figure 9 As can be seen, the energy storage resources within the energy storage cluster were fully mobilized. X5 was involved in scheduling at almost every time point, with X6 being actively mobilized from time period 2 to 4; X4 being actively mobilized from time period 5 to 13; and X7 being scheduled more frequently from time period 17 to 20. At each time point, the capacity output and mileage output ratios of each unit were roughly the same, with units having a larger frequency regulation mileage multiplier having a relatively higher mileage output ratio.

[0235] Furthermore, Figure 10 The figure shows the total capacity output and total mileage output of each energy storage system. As can be seen from the figure, because the unit frequency regulation cost of electrochemical energy storage is lower than that of mechanical energy storage, and electrochemical energy storage has a higher historical frequency regulation performance, the capacity and mileage dispatch volume of the four types of electrochemical energy storage are much higher than those of the three types of mechanical energy storage. The capacity output of the four types of electrochemical energy storage accounts for 75.17% of the capacity output of each unit, and the mileage output accounts for 83.43% of the total mileage output of each unit.

[0236] Among the four types of electrochemical energy storage, lithium-ion batteries and lead-acid batteries had the highest utilization rates, accounting for 21.59% and 24.75% of the total capacity output, respectively, and 24.27% and 27.38% of the total range output, respectively. This is because lead-acid batteries have lower unit frequency regulation costs among the four types of electrochemical energy storage. Although the unit frequency regulation cost of lithium-ion batteries is similar to that of sodium-sulfur batteries, lithium-ion batteries have better historical frequency regulation performance than sodium-sulfur batteries. Therefore, the capacity and range utilization of lithium-ion batteries are higher than those of sodium-sulfur batteries. Since the unit frequency regulation cost of sodium-sulfur batteries is higher than that of flow batteries, but the historical frequency regulation performance of flow batteries is better than that of sodium-sulfur batteries, the overall utilization capacity of these two energy storage groups is not significantly different.

[0237] Among the three groups of mechanical energy storage, the flywheel energy storage has the lowest unit frequency modulation cost and the optimal frequency modulation performance, so its dispatch amount is also relatively higher, the mileage modulation multiplier of flywheel energy storage is relatively higher, so its mileage dispatching proportion is also higher, its capacity dispatching amount accounts for 13.83% of the total capacity, and the mileage dispatching amount accounts for 10.17% of the total mileage demand. The pumped storage and compressed air energy storage are second. The compressed air energy storage has a relatively higher unit frequency modulation cost due to its lower charging and discharging efficiency, so its total capacity and total mileage dispatching amount in 24 hours are also less. Although the unit frequency modulation cost of pumped storage is not much different from that of flywheel energy storage, its historical frequency modulation performance is lower, so its capacity and mileage dispatching amount are lower than those of flywheel energy storage.

[0238] From the above dispatching results, it can be seen that electrochemical energy storage occupies an absolute advantage in the frequency modulation market, among which lead-acid batteries and lithium-ion batteries are particularly prominent. Liquid flow batteries and sodium-sulfur batteries can obtain more frequency modulation market share by scaling up applications or improving technical means to reduce unit frequency modulation cost. The three kinds of mechanical energy storage also play a positive role in the frequency modulation market, but the overall frequency modulation performance of mechanical energy storage is slightly inferior to that of electrochemical energy storage, so mechanical energy storage can continuously improve its frequency modulation performance through technical research and development, or it can obtain more benefits by participating in peak shaving and other auxiliary services.

[0239] 5) Improved Shapley value revenue allocation analysis

[0240] Shared energy storage centrally manages and efficiently uses multiple dispersed energy storage devices, allowing them to participate in the electricity market as a whole. Each energy storage owner connects their energy storage device to the shared energy storage, which is then dispatched by the shared energy storage operator. However, due to differences in performance, capacity, service life, and other factors among different energy storage devices, as well as different user demands and contributions to energy storage services, a fair and reasonable revenue allocation mechanism is needed to ensure the stable operation and sustainable development of the cluster. The Shapley value method, as a cost allocation and revenue distribution method in cooperative game theory, has unique advantages. It can allocate costs and benefits based on the contribution of each participant in the cooperation, ensuring that each participant can obtain a revenue share that matches their contribution. This allocation method not only embodies fairness, but also encourages participants to actively participate in cooperation and improve the overall efficiency of the cluster.

[0241] The embodiment is based on the traditional Shapley value method to calculate the cost allocation factor and cost allocation amount of each energy storage unit in the shared energy storage. Since the traditional Shapley value only considers the marginal contribution of each energy storage unit in different combination states, and does not consider the total capacity output and mileage output of each energy storage, the original cost allocation factor is improved from the capacity contribution degree and mileage contribution degree, and the total income obtained by the shared energy storage participating in the day-ahead frequency modulation market is allocated using the improved contribution factor. The weight of the capacity contribution degree and the mileage contribution degree is set to 0.25 by using the weighted average method, and the weight of the original cost allocation factor is set to 0.5, then the cost allocation and the income results of each unit before and after the improvement are shown in Table 8.

[0242] Table 8

[0243]

[0244] From the calculation results in Table 8, it can be seen that the cost allocation value of each energy storage according to the marginal contribution of reducing the combination cost in different combination states is reasonable, and the allocation factor based on the cost is improved in terms of capacity contribution degree and mileage contribution degree, so that the allocation result is more fair and reasonable. Since the capacity and mileage contribution of X4 and X5 is more prominent than other units, the profit allocation factor of X4 and X5 after improvement is increased by 0.3 compared with before, while the allocation factor of x1 and x2 after improvement is decreased by 0.3 and 0.4 respectively, resulting in a decrease in the income obtained by allocation.

[0245] Further, Figure 11 The comparison of the income of each energy storage in the shared energy storage before and after improvement is shown. From the comparison results, it can be seen that the improved income of the three mechanical energy storages is increased compared with before improvement, and the improved income of the three mechanical energy storages is increased by 2809.38 yuan, 3745.39 yuan and 401.27 yuan respectively, among which the income of pumped storage and compressed air energy storage increases more obviously; while the income of lithium ion battery, lead-acid battery and flow battery decreases after improvement, and the income decreases by 2829.92 yuan, 3052.1 yuan and 1112.22 yuan respectively, among which the income of lead-acid battery and lithium ion battery decreases more obviously. This is because the unit frequency modulation cost of pumped storage and compressed air energy storage is higher than that of electrochemical energy storage, so when calculating the marginal contribution of each energy storage in different combination states by using Shapley cooperative game with the goal of minimizing the total cost, the contribution factor is lower. However, the capacity output and mileage output of pumped storage and compressed air energy storage is higher than the total cost contribution weight, so after considering the marginal contribution of each energy storage in cost and the actual capacity and mileage output, the original allocation weight is improved, and the income of pumped storage and compressed air energy storage is improved after improvement, while the income of lithium ion and lead-acid battery decreases slightly.

[0246] In summary, the application proposes a shared energy storage frequency regulation operation mode, specifically, the shared energy storage effectively aggregates idle energy storages distributed at different locations of the power supply side, the power grid side and the load side, and participates in the frequency regulation market as an independent energy storage, so that the frequency regulation pressure of the power grid can be relieved, and the utilization efficiency of idle energy storages distributed at different locations of the source, the grid and the load can be improved, and the superior frequency regulation performance of the energy storage is fully utilized. Moreover, the application constructs a bidding clearing master-slave game model of the shared energy storage frequency regulation and a cooperative game model of each energy storage in the shared energy storage cluster based on game theory, and by simultaneously applying the cooperative game and the non-cooperative game method in the shared energy storage, the optimal scheduling of each energy storage can be realized, and the timeliness and accuracy of the energy storage frequency regulation scheduling are ensured. In addition, the improved Shapley method is used to distribute the income of each energy storage subject in the cluster, so that the fairness can be ensured, thereby ensuring the stable operation and sustainable development of the shared energy storage, and at the same time, the participants can be encouraged to actively participate in cooperation, and the overall benefit of the cluster can be improved.

[0247] The various techniques described herein can be implemented in connection with hardware or software or, where appropriate, with a combination of both. Thus, the methods and apparatus of the application, or certain aspects or portions thereof, can take the form of program code (i.e., instructions) embodied in tangible media, such as removable hard disks, USB flash drives, floppy diskettes, CD-ROMs, ROM or any other machine-readable storage medium wherein, when the program code is loaded into an internal memory of the machine such as a computer, the machine becomes an apparatus for practicing the application.

[0248] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been described in detail in order to not obscure the understanding of this description.

[0249] It is understood that, in the course of the present description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description of related features, for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various aspects, features and embodiments of the application. However, this method of disclosure should not be interpreted as reflecting an intention that the application requires more features than are explicitly recited in each claim. Rather, inventive aspects lie in less than all features of the application.

[0250] Further, unless otherwise noted, the use of the ordinal adjectives such as "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

[0251] While the application has been described in accordance with the various embodiments shown and described, it is to be understood that the application is not limited to those precise embodiments, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the present application. Furthermore, the language used in this specification has been principally selected for readability and instructional purposes and can not have been selected to delineate or circumscribe the patent rights to which it refers. Accordingly, the present application is intended to be illustrative, but not limiting, of the scope of the application, which is set forth with particularity in the claims that follow.

Claims

1. A method for energy storage dispatching shared energy storage participating in the frequency regulation ancillary services market, wherein the shared energy storage is an energy storage cluster aggregating multiple energy storages from at least one side of the power source, the power grid, and the load, and participates in the frequency regulation ancillary services market as an independent market entity, the market entities of the frequency regulation ancillary services market including power dispatch centers and several shared energy storage and thermal power units, the method comprising: Obtain basic parameters, including the available capacity, available mileage, capacity price, and mileage price of each shared energy storage and thermal power unit, as well as the capacity demand, mileage demand, capacity price range, and mileage price range of the power dispatch center; With the goal of minimizing the total daytime frequency regulation cost of the power dispatch center as the upper-level objective and maximizing the daytime frequency regulation revenue of each shared energy storage and thermal power unit as the lower-level objective, a master-slave game model for shared energy storage daytime frequency regulation is constructed, with the power dispatch center as the master and shared energy storage and thermal power units as slaves. The basic parameters are input into the master-slave game model for solution, and the capacity, mileage, and clearing price of each shared energy storage and thermal power unit in the day-ahead frequency regulation market for each time period are obtained. An internal cooperative game model for day-ahead frequency regulation of each shared energy storage is constructed with the goal of minimizing the total frequency regulation cost and optimizing the total frequency regulation performance of all aggregated energy storage. For each shared energy storage, the internal cooperative game model of the shared energy storage is solved based on its capacity bid volume, mileage bid volume and clearing price in the day-ahead frequency regulation market for each time period. The scheduling results of the energy storage aggregated by the shared energy storage are obtained. The scheduling results include the capacity output and mileage output of each energy storage in the day-ahead frequency regulation market for each time period.

2. The method of claim 1, wherein, The shared energy storage aggregates one or more of the following energy storage types: pumped hydro storage, compressed air storage, flywheel storage, lead-acid battery storage, flow battery storage, sodium-sulfur battery storage, and lithium-ion battery storage.

3. The method as described in claim 1 or 2, further comprising allocating revenue among the shared energy storage units using an improved Shapley value method, and allocating revenue among the shared energy storage units using an improved Shapley value method, including: For each shared energy storage, the improved profit distribution factor for each energy storage is obtained based on its capacity output contribution, mileage output contribution, and original cost allocation factor. The improved profit distribution factor is used to distribute the revenue among the energy storage units in the shared energy storage system.

4. The method of claim 3, wherein, For each shared energy storage unit, the improved profit distribution factor for each aggregated energy storage unit is obtained using the following formula: wherein R d represents a profit distribution factor vector composed of d profit distribution factors of the aggregated energy storages, ω1, ω2, ω3 represent the improvement weight coefficients of the capacity output contribution degree, the mileage output contribution degree and the original cost allocation factor respectively, and ω1+ω2+ω3=1, represents a capacity output contribution degree vector composed of d capacity output contribution degrees of the aggregated energy storages, τ d represents a mileage output contribution degree vector composed of d mileage output contribution degrees of the aggregated energy storages, R d represents an original cost allocation factor vector composed of d original cost allocation factors of the aggregated energy storages.

5. The method of claim 1 or 2, wherein, A master-slave game model for daytime frequency regulation of shared energy storage is constructed, with the upper-level objective being to minimize the total daytime frequency regulation cost of the power dispatch center and the lower-level objective being to maximize the daytime frequency regulation revenue of each shared energy storage and thermal power unit. This model includes: Based on the winning bid capacity and winning bid mileage of each shared energy storage and thermal power unit in the day-ahead frequency regulation market for each time period, as well as the capacity clearing price and mileage clearing price in the day-ahead frequency regulation market for each time period, the total day-ahead dispatch cost of the power dispatch center is determined, and the day-ahead frequency regulation cost model of the dispatch center is constructed with the minimum of the total day-ahead dispatch cost as the first objective function. According to the total income obtained by each thermal power unit in the day-ahead frequency modulation market and the frequency modulation cost and start-stop cost of the thermal power unit, the day-ahead frequency modulation income of each thermal power unit is determined, and a dispatching operation model of each thermal power unit is constructed with the maximum day-ahead frequency modulation income of each thermal power unit as a second objective function; According to the total income obtained by each shared energy storage in the day-ahead frequency modulation market and the frequency modulation cost of the shared energy storage, the day-ahead frequency modulation income of each shared energy storage is determined, and a dispatching operation model of each shared energy storage is constructed with the maximum day-ahead frequency modulation income of each shared energy storage as a third objective function; The master-slave game model is constructed with the dispatching center day-ahead frequency modulation cost model as an upper model and the dispatching operation model of each thermal power unit and the dispatching operation model of each shared energy storage as lower models.

6. The method of claim 5, wherein, The master-slave game model further includes first, second and third constraint conditions corresponding to the first, second and third objective functions respectively; The first constraint condition includes capacity and mileage constraints of each shared energy storage, capacity and mileage constraints of each thermal power unit, and frequency modulation supply-demand balance constraints of the power dispatching center and the shared energy storage and the thermal power unit; The second constraint condition includes frequency modulation declaration amount constraints, frequency modulation declaration price constraints and climbing constraints of the thermal power unit; The third constraint condition includes frequency modulation declaration amount constraints, frequency modulation declaration price constraints and charging and discharging power constraints of the shared energy storage.

7. The method of claim 5, wherein, The first objective function includes: wherein F L denotes the total cost of day-ahead dispatch of the power dispatch center, denotes the capacity clearing price of the day-ahead frequency modulation market t period, denotes the mileage clearing price of the day-ahead frequency modulation market t period, denotes the winning capacity of the shared energy storage m in the day-ahead frequency modulation market t period, denotes the winning mileage of the shared energy storage m in the day-ahead frequency modulation market t period, denotes the winning capacity of the thermal power unit n in the day-ahead frequency modulation market t period, denotes the winning mileage of the thermal power unit n in the day-ahead frequency modulation market t period, M denotes the number of shared energy storages participating in the day-ahead frequency modulation market, N denotes the number of thermal power units participating in the day-ahead frequency modulation market, and T denotes the total number of periods. The second objective function includes: wherein F G represents the day-ahead frequency regulation benefit of the thermal power unit, f G represents the total benefit obtained by the thermal power unit in the day-ahead frequency regulation market, n G represents the comprehensive frequency regulation performance of the thermal power unit, represents the frequency regulation cost of the thermal power unit, represents the start-stop cost of the thermal power unit, represents the capacity of the thermal power unit in the day-ahead frequency regulation market t period, represents the mileage of the thermal power unit in the day-ahead frequency regulation market t period, represents the capacity clearing price of the day-ahead frequency regulation market t period, represents the mileage clearing price of the day-ahead frequency regulation market t period, and MC' represents the unit frequency regulation cost of the thermal power unit. The third objective function includes: where F ES represents the day-ahead frequency regulation revenue of the shared energy storage, f ES represents the total day-ahead frequency regulation revenue of the shared energy storage, n ES represents the comprehensive frequency regulation performance of the shared energy storage, C ES represents the frequency regulation cost of the shared energy storage, represents the capacity clearing price of the day-ahead frequency regulation market at time period t, represents the mileage clearing price of the day-ahead frequency regulation market at time period t, represents the winning capacity of the shared energy storage at time period t of the day-ahead frequency regulation market, represents the winning mileage of the shared energy storage at time period t of the day-ahead frequency regulation market, MC" represents the unit frequency regulation cost of the shared energy storage.

8. The method of claim 1 or 2, wherein, An internal cooperation game model of day-ahead frequency modulation of each shared energy storage is constructed with the minimum total frequency modulation cost and the optimal total frequency modulation performance of each energy storage aggregated by the shared energy storage as targets, including: For each shared energy storage, the total frequency modulation cost of each energy storage aggregated by the shared energy storage is determined according to the mileage mid-rank values of the energy storage in each period and the unit mileage price of frequency modulation of each energy storage, and the minimum total frequency modulation cost is taken as a fourth objective function; The total frequency modulation performance of each energy storage aggregated by the shared energy storage is determined according to the mileage mid-rank values of the energy storage in each period and the historical comprehensive frequency modulation performance index of each energy storage, and the maximum total frequency modulation performance is taken as a fifth objective function; The internal cooperation game model of the shared energy storage is constructed by combining the fourth and fifth objective functions and by constraining the capacity output, mileage output, charging and discharging power, state of charge, health state of each energy storage aggregated by the shared energy storage, and the capacity supply-demand balance and mileage supply-demand balance of the shared energy storage.

9. A computing device comprising: at least one processor; and a memory storing program instructions configured to be executed by the at least one processor, the program instructions comprising instructions for performing the method of any one of claims 1-8.

10. A readable storage medium storing program instructions, which, when read and executed by a computing device, cause the computing device to perform the method of any one of claims 1-8.

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