Power distribution method and device for new energy station with energy storage configuration

Abstract

The invention relates to the technical field of new energy and energy storage grid-connected operation control, and particularly provides a power distribution method and device for a new energy station configured with energy storage, and the method comprises the steps: enabling the energy storage charge state of the new energy station configured with energy storage and the load shedding reserve percentage of a fan to serve as the input of a fuzzy controller, obtaining a system frequency modulation distribution coefficient output by the fuzzy controller; and on the basis of the system frequency modulation distribution coefficient, determining the energy storage and the active output regulation quantity of a fan when the new energy station configured with the energy storage performs frequency response. According to the technical scheme, frequency modulation service can be provided for a large power grid, frequency modulation pressure is relieved, and the power grid is promoted to keep stable frequency.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy and energy storage grid-connected operation control, and in particular to a power distribution method and device for a new energy station equipped with energy storage. Background Art

[0002] At present, due to the unclear control mode of new energy stations equipped with energy storage and unclear technical requirements related to control, the revision of the standard has not yet involved the specific technical requirements after the new energy stations are equipped with energy storage, resulting in a lack of technical basis and guiding principles for the control of new energy stations equipped with energy storage.

[0003] As energy transformation continues to advance, the physical form and operating characteristics of the power system are changing accordingly. Problems such as voltage regulation and stability, frequency regulation and stability, short-circuit capacity and dynamic reactive power of new energy stations are prominent. It is necessary to study the regulation mode of new energy stations that takes into account stability under new scenarios. Therefore, it is particularly important to form a unified understanding of how to regulate and manage new energy stations equipped with energy storage. Summary of the invention

[0004] In order to overcome the above-mentioned defects, the present invention proposes a power distribution method and device for a new energy station equipped with energy storage.

[0005] In a first aspect, a method for allocating power to a new energy station configured with energy storage is provided, the method comprising:

[0006] The energy storage charge state of the new energy station equipped with energy storage and the percentage of wind turbine load reduction and reserve are used as the input of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller;

[0007] Based on the system frequency regulation allocation coefficient, the active output adjustment amount of the energy storage and the wind turbine when the new energy station equipped with energy storage performs frequency response is determined.

[0008] Preferably, the wind turbine load reduction reserve percentage is as follows:

[0009]

[0010] In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

[0011] Preferably, the fuzzy linguistic variables corresponding to the energy storage charge state, wind turbine load reduction standby percentage and system frequency modulation allocation coefficient are: VL, L, M, H, VH, wherein VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

[0012] Furthermore, the fuzzy controller uses triangular and trapezoidal membership functions to describe fuzzy linguistic variables.

[0013] Furthermore, when the frequency of the grid connection point increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0014]

[0015] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0016] Furthermore, when the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0017]

[0018] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0019] Furthermore, when the new energy station configured with energy storage performs frequency response, the active output adjustment amount of the energy storage and the wind turbine is as follows:

[0020]

[0021] In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

[0022] In a second aspect, a power distribution device for a new energy station configured with energy storage is provided, wherein the power distribution device for a new energy station configured with energy storage comprises:

[0023] An analysis module is used to use the energy storage charge state of the new energy station equipped with energy storage and the percentage of wind turbine load reduction and reserve as inputs of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller;

[0024] A determination module is used to determine the active output adjustment amount of energy storage and wind turbines when a new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient.

[0025] Preferably, the wind turbine load reduction reserve percentage is as follows:

[0026]

[0027] In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

[0028] Preferably, the fuzzy linguistic variables corresponding to the energy storage charge state, wind turbine load reduction standby percentage and system frequency modulation allocation coefficient are: VL, L, M, H, VH, wherein VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

[0029] Furthermore, the fuzzy controller uses triangular and trapezoidal membership functions to describe fuzzy linguistic variables.

[0030] Furthermore, when the frequency of the grid connection point increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0031]

[0032] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0033] Furthermore, when the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0034]

[0035] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0036] Furthermore, when the new energy station configured with energy storage performs frequency response, the active output adjustment amount of the energy storage and the wind turbine is as follows:

[0037]

[0038] In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

[0039] In a third aspect, a computer device is provided, comprising: one or more processors;

[0040] The processor is configured to execute one or more programs;

[0041] When the one or more programs are executed by the one or more processors, the power allocation method for a new energy station configured with energy storage is implemented.

[0042] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed, the power allocation method for the new energy station configured with energy storage is implemented.

[0043] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0044] The present invention provides a power distribution method and device for a new energy station equipped with energy storage, comprising: using the energy storage charge state and the wind turbine load reduction reserve percentage of the new energy station equipped with energy storage as inputs of a fuzzy controller to obtain a system frequency regulation allocation coefficient output by the fuzzy controller; determining the active output adjustment amount of the energy storage and the wind turbine when the new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient. The technical solution provided by the present invention can make full use of the active reserve margin of the wind turbine and the limited capacity of the energy storage equipment, thereby improving the economy of the operation of the wind-storage system. At the same time, by having wind power and energy storage participate in frequency regulation, the shortcomings of the current frequency regulation performance of only traditional units are improved, and the frequency stability of the power grid is improved. For a wind-storage combined system in which wind power and energy storage participate in frequency regulation at the same time, the frequency regulation characteristics of each frequency regulation resource are fully utilized to achieve the optimal frequency regulation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic flow chart of the main steps of the power allocation method of a new energy station configured with energy storage according to an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of a power distribution method for a new energy station configured with energy storage according to an embodiment of the present invention;

[0047] Figure 3 is a variable membership function curve diagram of an embodiment of the present invention;

[0048] Figure 4 is a structural diagram of a new energy-energy storage combined system according to an embodiment of the present invention;

[0049] Figure 5 is a fuzzy logic control input-output relationship diagram when the system frequency is reduced according to an embodiment of the present invention;

[0050] Figure 6is a curve diagram of energy storage SOC value of an embodiment of the present invention;

[0051] Figure 7 is a total power balance diagram of the system according to an embodiment of the present invention;

[0052] Figure 8 It is a system dynamic frequency curve diagram under different modes of the embodiment of the present invention. DETAILED DESCRIPTION

[0053] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0054] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] As disclosed in the background technology, at present, due to the unclear control mode of new energy stations equipped with energy storage and unclear technical requirements related to control, the revision of the standard has not yet involved the specific technical requirements after the new energy stations are equipped with energy storage, resulting in a lack of technical basis and guiding principles for the control of new energy stations equipped with energy storage.

[0056] As energy transformation continues to advance, the physical form and operating characteristics of the power system are changing accordingly. Problems such as voltage regulation and stability, frequency regulation and stability, short-circuit capacity and dynamic reactive power of new energy stations are prominent. It is necessary to study the regulation mode of new energy stations that takes into account stability under new scenarios. Therefore, it is particularly important to form a unified understanding of how to regulate and manage new energy stations equipped with energy storage.

[0057] In order to improve the above-mentioned problems, the present invention provides a power distribution method and device for a new energy station equipped with energy storage, comprising: using the energy storage charge state and the wind turbine load reduction reserve percentage of the new energy station equipped with energy storage as the input of the fuzzy controller to obtain the system frequency regulation allocation coefficient output by the fuzzy controller; determining the active output adjustment amount of the energy storage and the wind turbine when the new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient. The technical solution provided by the present invention can make full use of the active reserve margin of the wind turbine and the limited capacity of the energy storage equipment, thereby improving the economy of the operation of the wind-storage system. At the same time, by allowing wind power and energy storage to participate in frequency regulation, the shortcomings of the current frequency regulation performance of only traditional units are improved, and the frequency stability of the power grid is improved. For the wind-storage combined system in which wind power and energy storage participate in frequency regulation at the same time, the frequency regulation characteristics of each frequency regulation resource are fully utilized to achieve the optimal frequency regulation effect.

[0058] The above scheme is described in detail below.

[0059] Example 1

[0060] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart of the main steps of a method for allocating power to a new energy station configured with energy storage according to an embodiment of the present invention. Figure 1 As shown, the power allocation method for a new energy station configured with energy storage in an embodiment of the present invention mainly includes the following steps:

[0061] Step S101: using the energy storage charge state of the new energy station configured with energy storage and the wind turbine load reduction reserve percentage as inputs of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller;

[0062] Step S102: determining the active output adjustment amount of the energy storage and the wind turbine when the new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient.

[0063] The schematic diagram of frequency modulation dynamic allocation based on fuzzy logic algorithm is as follows Figure 2 As shown in the figure, the wind turbine load reduction operation level and the energy storage charge state are used as the input variables of the fuzzy controller; according to the actual frequency regulation demand analysis, fuzzy logic rules suitable for different frequency regulation scenarios are designed to obtain the frequency regulation demand allocation coefficient of the wind-storage operation state and frequency regulation capacity in the wind-storage joint system, so as to realize the dynamic coordinated operation of wind-storage to participate in frequency regulation.

[0064] In this embodiment, the percentage of wind turbine load reduction and standby is as follows:

[0065]

[0066] In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

[0067] In this embodiment, the fuzzy linguistic variables corresponding to the energy storage charge state, the wind turbine load reduction standby percentage and the system frequency modulation allocation coefficient are: VL, L, M, H, VH, where VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

[0068] The fuzzy logic reasoning process of the fuzzy controller first defines the membership function to describe the fuzzy variables. The control effect under the conditions of triangular and trapezoidal membership functions is more ideal, and the fuzzy segmentation of the input and output space can be performed. Therefore, the fuzzy controller uses triangular and trapezoidal membership functions to describe the fuzzy language variables.

[0069] Select triangle and trapezoid membership functions to perform fuzzy segmentation of input and output space and perform fuzzy logic control. The membership functions of input and output variables are as follows: Figure 3 shown.

[0070] For the input variable SOC t and χ t , define fuzzy linguistic variables to describe the state of the input variable: VL (very low); L (low); M (medium); H (high); VH (very high). For the output variable system frequency modulation allocation coefficient ε t , define its fuzzy linguistic variables to be the same as the input variables. Figure 3 When the SOC value in (a) is lower than 0.1, the battery power is too low. To extend the battery life, the corresponding membership function value is VL, and the energy storage will stop its discharge process. When the energy storage rated capacity is constant after optimization, SOC can reflect the frequency response capability of the energy storage.

[0071] Next, we introduce the fuzzy logic reasoning rules in different scenarios.

[0072] When the frequency of the grid connection point increases:

[0073] When the system frequency increases, the energy storage device is in a charging state. A lower SOC value means that the energy storage has a higher ability to store energy from the grid. At this time, the wind turbine can be less loaded to improve the economy of system frequency regulation.

[0074] When the SOC value is low and χ is high, the dynamic allocation coefficient ε of the frequency regulation demand will take a higher value, which means that the energy storage will bear more frequency regulation demand;

[0075] When the SOC value is high and χ is high, the dynamic allocation coefficient ε of the frequency regulation demand will take a lower value, which means that the wind turbine load shedding will bear more frequency regulation demand;

[0076] When the SOC value is low and χ is low, the dynamic allocation coefficient ε of the frequency regulation demand will take a higher value, which means that the frequency regulation demand will be borne by energy storage first.

[0077] Therefore, when the grid connection point frequency increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0078]

[0079] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0080] When the grid connection point frequency decreases:

[0081] When the system frequency decreases, the energy storage device is in a discharging state, and the wind turbine should increase its active power to support the system frequency recovery. A higher SOC value means that the energy storage has sufficient power reserves to send active power to the grid for frequency support.

[0082] When the SOC value is high and χ is low, the dynamic allocation coefficient ε of the frequency regulation demand will take a higher value, which means that the energy storage will bear more frequency regulation demand;

[0083] When the SOC value is low and χ is high, the frequency regulation demand dynamic allocation coefficient ε will take a lower value, which means that the wind turbine will bear more frequency regulation demand;

[0084] When the SOC value is low and χ is low, the dynamic allocation coefficient ε of the frequency regulation demand will take a higher value, which means that the frequency regulation demand will be borne by energy storage first.

[0085] Therefore, when the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0086]

[0087] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0088] In one embodiment, when the new energy station configured with energy storage performs frequency response, the active output adjustment amount of the energy storage and the wind turbine is as follows:

[0089]

[0090] In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

[0091] In order to verify the economic and effectiveness of the optimal configuration of energy storage capacity and the coordinated control strategy in the frequency regulation control of the wind-storage combined system, a Figure 4 The wind-storage combined system shown in the figure has a wind farm output of 200MW, and is equipped with an energy storage device for auxiliary frequency regulation to form a wind-storage combined system. DFIG is a doubly-fed asynchronous wind turbine generator, and ES is energy storage.

[0092] The wind farm is represented by an equivalent DFIG model, and is equipped with energy storage equipment for auxiliary frequency regulation to form a wind-storage joint system. The energy storage equipment uses Vanadium Redox Flow Battery (VRB), which has high cyclability, high ramp rate and short response time, and is very suitable for frequency regulation control.

[0093] Construct a capacity optimization model and set the parameters in the optimization model to the unit energy cost λ of energy storage v is the reference value, λ v The value is 5×10 5 $ / MWh, all cost parameters are normalized. The normalized values ​​of the variable parameters in the energy storage capacity optimization model are shown in Table 1.

[0094] Table 1

[0095]

[0096]

[0097] The energy storage capacity required for the system is optimized, and the optimal energy storage configuration scheme for the simulation system is obtained according to the energy storage capacity optimization model. The energy storage configuration required for the wind-storage combined system has a rated capacity of 28.92MWh and a rated power of 40MW.

[0098] Taking the system frequency reduction scenario as an example, when the system has continuous load changes, fuzzy logic control is performed in multiple time periods. According to the formulated fuzzy logic control rules, the fuzzy logic control input-output relationship is obtained as follows: Figure 5 shown.

[0099] Taking into account the volatility of actual wind speed, to simplify the analysis, the reserved spare capacity of the wind turbine is set to 10% of the maximum output power under MPPT control, and the initial SOC value of the energy storage is set to 0.4. The change curve of the energy storage SOC value is shown in Figure 6 shown.

[0100] In the process of frequency regulation of wind-storage combined system, the frequency regulation strategy of wind power and energy storage is determined according to the output of fuzzy logic controller. The output of wind turbine during load shedding operation and the charging and discharging power of energy storage system are Figure 7 As shown:

[0101] It can be seen from the simulation results that through the fuzzy logic control method, the active output of wind power and energy storage in the wind-storage combined system is coordinated in real time, and the response system frequency is stable.

[0102] The load level in one of the time periods and the results of the optimized allocation of active power of wind power and energy storage are selected to verify the control effect of the proposed dynamic optimization allocation strategy on the dynamic frequency of the system. The control effect of the system dynamic frequency is compared when the wind turbine is not assisted by energy storage equipment and the wind turbine adopts MPPT control without participating in the frequency mode, and when the wind turbine adopts MPPT control without participating in the frequency but considers the participation of energy storage in the frequency modulation mode. The system dynamic frequency curves under different modes are shown in Figure 2. Figure 8 shown.

[0103] By comparing the system dynamic frequency curves under different control modes, the optimized allocation strategy considering the frequency regulation characteristics of wind power and energy storage is developed. Through the coordinated cooperation of wind power and energy storage, the wind turbine fully exploits its frequency regulation capability through load reduction and standby, and the lowest frequency point is 49.75Hz. When wind power adopts MPPT control mode without participating in frequency response and does not consider the auxiliary mode of energy storage frequency regulation, the dynamic frequency characteristics are the worst, and the lowest frequency point drops to 49.56Hz. After considering energy storage to participate in frequency regulation control, the lowest frequency point is 49.67Hz, and the frequency characteristics are improved, but compared with the wind-storage coordinated mode, the lowest frequency point differs by 0.08Hz. It can be seen that the optimized allocation strategy considering the frequency regulation characteristics of wind power and energy storage can obtain the optimal system dynamic frequency characteristics through the coordinated cooperation of wind power and energy storage.

[0104] Example 2

[0105] Based on the same inventive concept, the present invention also provides a power distribution device for a new energy station configured with energy storage, the power distribution device for a new energy station configured with energy storage comprising:

[0106] An analysis module is used to use the energy storage charge state of the new energy station equipped with energy storage and the percentage of wind turbine load reduction and reserve as inputs of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller;

[0107] A determination module is used to determine the active output adjustment amount of energy storage and wind turbines when a new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient.

[0108] Preferably, the wind turbine load reduction reserve percentage is as follows:

[0109]

[0110] In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

[0111] Preferably, the fuzzy linguistic variables corresponding to the energy storage charge state, wind turbine load reduction standby percentage and system frequency modulation allocation coefficient are: VL, L, M, H, VH, wherein VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

[0112] Furthermore, the fuzzy controller uses triangular and trapezoidal membership functions to describe fuzzy linguistic variables.

[0113] Furthermore, when the frequency of the grid connection point increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0114]

[0115] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0116] Furthermore, when the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows:

[0117]

[0118] In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

[0119] Furthermore, when the new energy station configured with energy storage performs frequency response, the active output adjustment amount of the energy storage and the wind turbine is as follows:

[0120]

[0121] In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

[0122] Example 3

[0123] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a power distribution method for a new energy station configured with energy storage in the above embodiment.

[0124] Example 4

[0125] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here may include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of a power distribution method for a new energy station configured with energy storage in the above embodiment.

[0126] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0127] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0128] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0129] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for allocating power to a new energy station equipped with energy storage, characterized in that: The method comprises: The energy storage charge state of the new energy station equipped with energy storage and the percentage of wind turbine load reduction and reserve are used as the input of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller; Based on the system frequency regulation allocation coefficient, the active output adjustment amount of the energy storage and the wind turbine when the new energy station equipped with energy storage performs frequency response is determined.

2. The method according to claim 1, characterized in that The fan load shedding reserve percentage is as follows: In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

3. The method according to claim 1, characterized in that The fuzzy linguistic variables corresponding to the energy storage charge state, wind turbine load reduction reserve percentage and system frequency modulation allocation coefficient are: VL, L, M, H, VH, where VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

4. The method according to claim 3, characterized in that The fuzzy controller uses triangular and trapezoidal membership functions to describe fuzzy linguistic variables.

5. The method according to claim 3, characterized in that When the grid connection point frequency increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows: In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

6. The method according to claim 3, characterized in that When the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows: In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

7. The method according to claim 2, characterized in that When the new energy station configured with energy storage performs frequency response, the active output adjustment of energy storage and wind turbine is as follows: In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

8. A power distribution device for a new energy station equipped with energy storage, characterized in that: The device comprises: An analysis module is used to use the energy storage charge state of the new energy station equipped with energy storage and the percentage of wind turbine load reduction and reserve as inputs of the fuzzy controller to obtain the system frequency modulation allocation coefficient output by the fuzzy controller; A determination module is used to determine the active output adjustment amount of energy storage and wind turbines when a new energy station equipped with energy storage performs frequency response based on the system frequency regulation allocation coefficient.

9. The device according to claim 8, characterized in that The fan load shedding reserve percentage is as follows: In the above formula, χ t is the percentage of fan load reduction and reserve at time t, △P R,t is the frequency modulation requirement of the system at time t, γ t P is the fan load shedding reserve level at time t, m,t is the active output of the wind turbine operating in MPPT mode at time t, and f is the grid-connected point frequency.

10. The device according to claim 8, characterized in that The fuzzy linguistic variables corresponding to the energy storage charge state, wind turbine load reduction reserve percentage and system frequency modulation allocation coefficient are: VL, L, M, H, VH, where VL represents very low, L represents low, M represents medium, H represents high, and VH represents very high.

11. The device according to claim 10, characterized in that The fuzzy controller uses triangular and trapezoidal membership functions to describe fuzzy linguistic variables.

12. The device according to claim 10, characterized in that When the grid connection point frequency increases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows: In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

13. The device according to claim 10, characterized in that When the grid connection point frequency decreases, the fuzzy logic inference rule matrix of the fuzzy controller is as follows: In the above formula, χ is the percentage of wind turbine load reduction and reserve, and SOC is the energy storage charge state.

14. The device according to claim 9, characterized in that When the new energy station configured with energy storage performs frequency response, the active output adjustment of energy storage and wind turbine is as follows: In the above formula, △P ES,t is the active output adjustment of energy storage when the new energy station equipped with energy storage performs frequency response at time t, △P W,t is the active output adjustment of the wind turbine when the new energy station with energy storage is performing frequency response at time t, ε t is the system frequency modulation allocation coefficient at time t.

15. A computer device, characterized in that: include: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the power allocation method for a new energy station configured with energy storage as described in any one of claims 1 to 7 is implemented.

16. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the power distribution method for a new energy station configured with energy storage as described in any one of claims 1 to 7 is implemented.

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