A frequency regulation control method for wind-storage combined system considering energy storage capacity optimization

Abstract

The present invention belongs to the technical field of frequency regulation control of power systems, and particularly relates to a frequency regulation control method for a wind-storage combined system that takes energy storage capacity optimization into consideration. With the goal of minimizing the total cost of the wind-storage combined system, an energy storage capacity optimization configuration model that takes economic factors into consideration is established, and the energy storage capacity optimization model is solved using a PSO algorithm to determine the optimal energy storage capacity configuration scheme required for the wind farm. According to the configuration scheme, a dynamic frequency response fuzzy controller for the wind-storage combined system is designed, and a fuzzy logic-based coordinated control strategy for wind power and energy storage is formulated to make full use of the active reserve margin of wind turbines and the limited capacity of energy storage equipment, so as to realize the dynamic coordinated operation of wind power and energy storage to participate in system frequency regulation. The method has the lowest total system cost and good economy. The fuzzy control method is used to perform dynamic frequency control on the wind-storage combined system, and there is no need to perform quantitative mathematical modeling on the controlled process, so it has strong practicality.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system frequency regulation control, and in particular relates to a frequency regulation control method for a wind-storage combined system taking into account energy storage capacity optimization. Background Art

[0002] Wind turbines are connected to the grid through power electronic converters. As the capacity of wind power connected to the grid increases, the frequency characteristics of the system deteriorate. Although wind turbines can participate in system frequency regulation through speed control, pitch angle control and integrated control, it is difficult to ensure that wind turbines have a lasting and reliable active frequency support capability due to the randomness and volatility of wind speed. Energy storage has the technical advantages of flexible control, fast response, strong short-term power throughput, and easy change of regulation direction; combining energy storage with wind turbines, giving wind turbines reliable frequency response capabilities with limited energy storage system configuration, realizing the complementary advantages of wind turbines and energy storage, and participating in frequency regulation in the form of a wind-storage joint system.

[0003] However, due to the high cost of energy storage, it is necessary to consider the economic benefits of wind-storage combined systems participating in system frequency response and study the economic feasibility of wind-storage system configuration energy storage. Existing research has mostly focused on the participation of independent equipment in wind-storage combined systems in frequency regulation control, lacking consideration of the total cost economics of frequency regulation operation of wind-storage combined systems and the effective coordination of wind turbines and energy storage in the process of wind-storage combined systems responding to system frequency regulation requirements. Summary of the invention

[0004] In view of the problems existing in the background technology, the present invention provides a frequency regulation control method for a wind-storage combined system taking into account the optimization of energy storage capacity, so as to realize the dynamic coordinated operation of wind power and energy storage in the wind-storage combined system to participate in system frequency regulation through reasonable energy storage capacity configuration.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions: a frequency regulation control method for a wind-storage combined system considering the optimization of energy storage capacity, which takes the minimum total cost of the wind-storage combined system as the goal, establishes an energy storage capacity optimization model considering economy, configures the frequency regulation capacity of energy storage in the wind-storage combined system, and realizes the dynamic coordinated operation of wind power and energy storage in the wind-storage combined system to participate in system frequency regulation; the method comprises the following steps:

[0006] Step 1: Establish an energy storage capacity optimization configuration model that takes economic factors into consideration to determine the optimal energy storage capacity configuration required for the wind farm;

[0007] Step 2: Design a fuzzy controller for the dynamic frequency response of the wind-storage combined system and formulate a wind power and energy storage coordinated control strategy based on fuzzy logic.

[0008] In the above-mentioned wind-storage combined system frequency regulation control method considering energy storage capacity optimization, the implementation of step 1 specifically includes the following steps:

[0009] Step 1.1, establish energy storage capacity optimization model;

[0010] Step 1.1.1. The objective function of the energy storage capacity optimization model is to minimize the total cost of system frequency regulation operation. The cost function is obtained by the difference between the total operating cost and the frequency regulation benefit:

[0011] min F=C total -I total

[0012] Among them, F is the total cost of system frequency regulation operation, C total is the total operating cost of the wind-storage combined system, I total For FM benefits;

[0013] 1) The total operating cost of the wind-storage combined system is:

[0014] C total =C con +C dam +C soc +C cha

[0015] Among them, C con is the investment and construction cost of energy storage equipment, C dam is the attenuation loss during the energy storage operation, C soc is the penalty cost of SOC exceeding the limit of energy storage, C cha The opportunity cost of wind turbine load reduction operation;

[0016] 1.1) C con The investment and construction cost of energy storage equipment is:

[0017] C con =λ v V r +λ p P r

[0018] In the formula, λ v is the unit capacity price; p is the price per unit power; V r is the rated capacity of energy storage, in MWh; P r is the rated power of the energy storage, in MW;

[0019] 1.2) C dam The attenuation loss during energy storage operation is:

[0020]

[0021] In the formula, β v is the energy storage attenuation loss coefficient; P es,t is the active output value of energy storage participating in frequency regulation; t0, t s are the start and end times of the optimization operation respectively;

[0022] 1.3) C soc The penalty cost of energy storage SOC exceeding the limit is:

[0023]

[0024] In the formula, α SOC is the energy storage SOC over-limit cost coefficient; t0, t s are the start and end times of the optimization operation; SOC t is the SOC value of energy storage at time t; SOC max , SOC min is the upper and lower limits of the energy storage SOC value; μ H For energy storage in SOC t >SOC max Type flag, μ L For energy storage in SOC t <SOC min Type flag when

[0025] 1.4) C cha The opportunity cost caused by the wind turbine load reduction operation, that is, the loss of revenue due to the wind turbine load reduction operation is:

[0026]

[0027] In the formula, τ t is the market electricity price; γ t P is the load shedding standby level of the fan; MPPT,t is the active output of the fan in MPPT control mode; t0, t s are the start and end times of the optimization operation respectively;

[0028] 2)I total The formula for calculating frequency modulation revenue is as follows:

[0029]

[0030] Where η req P is the unit compensation price of frequency regulation electricity of wind-storage combined system; w,t is the active output value of the fan participating in frequency regulation, P es,t is the active output value of energy storage participating in frequency regulation; t0, t s are the start and end times of the optimization operation respectively;

[0031] Step 1.1.2, the constraints include: energy storage system SOC constraint, energy storage system charging and discharging power constraint, wind turbine frequency regulation power constraint;

[0032] 1) The SOC of the energy storage system meets the constraints during the frequency regulation of the wind-storage combined system:

[0033] SOC c,min ≤SOC c,t ≤SOC c,max

[0034] SOC d,min ≤SOC d,t ≤SOC d,max

[0035] In the formula, SOC c,t is the SOC value of energy storage at time t during the charging process; SOC d,t is the SOC value of energy storage at time t during the discharge process; SOC c,min , SOC c,max The maximum and minimum SOC of the energy storage system during the charging process; SOC d,min , SOC d,max is the maximum and minimum SOC of the energy storage system during the discharge process;

[0036] 2) The charging and discharging power of the energy storage system should meet the constraints:

[0037] P c,min ≤P c,t ≤P c,max

[0038] P d,min ≤P d,t ≤P d,max

[0039] Where P c,t P is the charging power of energy storage at time t during the charging process; d,t is the discharge power of energy storage at time t during the discharge process; P c,min , P c,max is the minimum charging power and maximum charging power of energy storage; P d,min , P d,max is the minimum discharge power and maximum discharge power of energy storage;

[0040] 3) During the frequency regulation process, the output of the wind turbine participating in the frequency regulation and its reserve level should satisfy the constraint relationship. The additional output of the wind turbine should not exceed its active reserve margin, and the constraint conditions should be met:

[0041] 0≤ΔP W,t ≤γ t ·P MPPT,t ;

[0042] In the formula, ΔP W,t P is the change in active output of the wind turbine participating in the frequency response; MPPT,t is the active output of the fan in MPPT control mode; γ t It is the load shedding standby level for the fans;

[0043] Step 1.2: The PSO algorithm solves the energy storage capacity optimization model to obtain the required energy storage capacity solution.

[0044] In the above-mentioned wind-storage combined system frequency regulation control method considering energy storage capacity optimization, the implementation of step 2 specifically includes the following steps:

[0045] Step 2.1, design the dynamic frequency response fuzzy controller of the wind-storage combined system and determine the controller input and output;

[0046] Step 2.1.1 Reduce the load level of the fan to t , energy storage state of charge SOC t , as the input variable of the fuzzy controller;

[0047] Step 2.1.2: Function of the percentage of wind turbine load shedding and reserve reserve χ t Reflects the ability of the fan to participate in frequency regulation at time t. The calculation formula is as follows:

[0048]

[0049] In the formula, ΔP R,t is the frequency modulation requirement of the system at time t; γ t Leave a spare level for fan load shedding; P m,t is the active output of the wind turbine operating in MPPT mode at time t;

[0050] Step 2.1.3: The output of the fuzzy controller is the system frequency modulation allocation coefficient ε t When the total frequency regulation demand of the wind-storage combined system is constant, the frequency regulation power ΔP borne by the wind turbine and energy storage for frequency response is W,t and ΔP ES,t Dynamically determined by the system frequency modulation allocation coefficient:

[0051]

[0052] ΔP W,t and ΔP ES,t are the active output changes of the wind turbine and energy storage in frequency response at time t, ε t is the allocation coefficient. When the total active power frequency regulation demand of the wind-storage combined system is constant, ΔP W,t and ΔP ES ,t is given by ε tThe complementary relationship of decision;

[0053] Step 2.2, formulate fuzzy logic reasoning rules to obtain the wind power and energy storage coordinated control strategy;

[0054] Select triangle and trapezoid membership functions to perform fuzzy segmentation of input and output space for control;

[0055] For the input variable SOC t and χ t , and the output variable ε t , five fuzzy linguistic variables are defined to describe the state of the input variables: VL is very low; L is low; M is medium; H is high; VH is very high; and corresponding fuzzy logic inference rules are defined for the frequency increase and frequency decrease scenarios respectively.

[0056] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a frequency regulation control method for a wind-storage combined system taking into account the optimization of energy storage capacity, and rationally arranges the frequency regulation capacity of energy storage in the wind-storage combined system by means of optimization, minimizes the total system cost, and has good economy; the adopted fuzzy control strategy for the dynamic frequency response of the wind-storage combined system makes full use of the active reserve margin of the wind turbine and the limited capacity of the energy storage equipment, and realizes the dynamic coordinated operation of wind power and energy storage to participate in the system frequency regulation; the fuzzy control does not require quantitative mathematical modeling of the controlled process, and has strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is an overall flow chart of a frequency regulation control method for a wind-storage combined system considering energy storage capacity optimization according to an embodiment of the present invention;

[0058] Figure 2 This is a structural diagram of a wind-storage combined system in an embodiment of the present invention;

[0059] FIG3( a ) is a membership function of the fuzzy controller input variable SOC in an embodiment of the present invention;

[0060] FIG3( b ) is a membership function of the input variable χ of the frequency increase scenario of the fuzzy controller in an embodiment of the present invention;

[0061] FIG3( c ) is a membership function of the fuzzy controller frequency reduction scenario input variable χ in an embodiment of the present invention;

[0062] FIG3( d ) is a membership function of the output variable allocation coefficient ε of the fuzzy controller in an embodiment of the present invention;

[0063] Figure 4 This is the wind power storage output curve in the embodiment of the present invention. DETAILED DESCRIPTION

[0064] The technical solutions in the embodiments of the present invention will be described clearly and completely below in combination with the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0065] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0066] The present invention will be further described below in conjunction with specific embodiments, but the present invention is not limited thereto.

[0067] In view of the above problems, this embodiment proposes a frequency regulation control method for a wind-storage combined system that takes into account the optimization of energy storage capacity. With the goal of minimizing the total cost of the wind-storage combined system, an energy storage capacity optimization model that takes economic efficiency into consideration is established to reasonably arrange the frequency regulation capacity of energy storage in the wind-storage combined system; then a fuzzy control strategy for the dynamic frequency response of the wind-storage combined system is proposed, which makes full use of the active reserve margin of the wind turbine and the limited capacity of the energy storage equipment, and realizes the dynamic coordinated operation of wind power and energy storage to participate in the system frequency regulation.

[0068] like Figure 1 As shown in the figure, it is a flow chart of the method of the present invention, using the PSO algorithm to solve the established energy storage capacity optimization model to obtain the required energy storage capacity solution; design the dynamic frequency response fuzzy controller of the wind-storage joint system, and obtain the wind power and energy storage coordinated control strategy according to the frequency regulation requirements of the system. Figure 2 The figure shows the structure diagram of the wind-storage combined system.

[0069] This embodiment is implemented by the following technical solution, a frequency regulation control method of a wind-storage combined system considering energy storage capacity optimization, comprising the following steps:

[0070] S1. Establish an energy storage capacity optimization configuration model that takes economic considerations into account and determine the optimal energy storage capacity configuration required for the wind farm. Specifically, the following steps are included:

[0071] S1.1, establish an energy storage capacity optimization model.

[0072] The energy storage capacity optimization model comprehensively considers the investment and operation costs of energy storage equipment in the wind-storage combined system, the opportunity cost of wind turbine load reduction operation, and the frequency regulation benefits of the wind-storage combined system. The objective function of the energy storage capacity optimization model is to minimize the total cost of system frequency regulation operation. The cost function is obtained by the difference between the total operating cost and the frequency regulation benefit:

[0073] min F=C total -I total

[0074] Among them, F is the total cost of system frequency regulation operation, C total is the total operating cost of the wind-storage combined system, I total For FM benefits;

[0075] The total operating cost of a wind-storage combined system consists of four parts:

[0076] C total =C con +C dam +C soc +C cha

[0077] Among them, C con is the investment and construction cost of energy storage equipment, C dam is the attenuation loss during the energy storage operation, C soc is the penalty cost of SOC exceeding the limit of energy storage, C cha The opportunity cost of wind turbine load reduction operation;

[0078] C con Investment and construction costs for energy storage equipment:

[0079] C con =λ v V r +λ p P r

[0080] In the formula, λ v is the unit capacity price; p is the price per unit power; V r is the rated capacity of energy storage, in MWh; P r is the rated power of the energy storage, in MW.

[0081] Since the direction of charging and discharging power of energy storage will change frequently during the frequency regulation process, the attenuation loss of energy storage batteries needs to be taken into account in the energy storage operation cost. dam is the attenuation loss during energy storage operation:

[0082]

[0083] In the formula, β v is the energy storage attenuation loss coefficient; P es,t is the active output value of energy storage participating in frequency regulation; t0, t s To optimize the start and end times of the run.

[0084] During the frequency modulation process, the energy storage device may be overcharged or over-discharged, so the SOC over-limit cost of the energy storage needs to be considered. soc The penalty cost for exceeding the SOC limit of energy storage is:

[0085]

[0086] In the formula, α SOC is the energy storage SOC over-limit cost coefficient; t0, t s are the start and end times of the optimization operation; SOC t is the SOC value of energy storage at time t; SOC max , SOC min is the upper and lower limits of the energy storage SOC value; μ H For energy storage in SOC t >SOC max Type flag, μ L For energy storage in SOC t <SOC min The type flag of the time.

[0087] The wind turbine considers providing stable frequency support for the system by reducing load, so the wind turbine needs to reserve a part of wind reserve capacity, resulting in certain wind abandonment costs. cha The opportunity cost caused by the wind turbine load reduction operation, that is, the loss of revenue caused by the wind turbine load reduction operation:

[0088]

[0089] In the formula, τ t is the market electricity price; γ t P is the load shedding standby level of the fan; MPPT , t is the active output of the wind turbine in MPPT control mode. The opportunity cost of wind turbine load shedding is directly related to the reserve level of the wind turbine. The frequency regulation reserve level γ t The higher it is, the greater the opportunity cost of the wind turbine's load-reduced operation.

[0090] Since the wind-storage combined system can obtain certain frequency regulation benefits by participating in frequency response. Method for calculating frequency regulation benefits:

[0091]

[0092] Where η req P is the unit compensation price of frequency regulation electricity of wind-storage combined system; w,t is the active output value of the fan participating in frequency regulation, P es,t is the active output value of energy storage participating in frequency regulation; t0, t s are the start and end times of the optimization operation respectively;

[0093] The constraints include energy storage system SOC constraints, energy storage system charging and discharging power constraints, and wind turbine frequency regulation power constraints.

[0094] The SOC of the energy storage system meets the constraints during the frequency regulation of the wind-storage combined system:

[0095] SOC c,min ≤SOC c,t ≤SOC c,max

[0096] SOC d,min ≤SOC d,t ≤SOC d,max

[0097] In the formula, SOC c,t is the SOC value of energy storage at time t during the charging process; SOC d,t is the SOC value of energy storage at time t during the discharge process; SOC c,min , SOC c,max The maximum and minimum SOC of the energy storage system during the charging process; SOC d,min , SOC d,max is the maximum and minimum SOC of the energy storage system during the discharge process;

[0098] The charging and discharging power of the energy storage system should meet the constraints:

[0099] P c,min ≤P c,t ≤P c,max

[0100] P d,min ≤P d,t ≤P d,max

[0101] Where P c,t P is the charging power of energy storage at time t during the charging process; d,t is the discharge power of energy storage at time t during the discharge process; P c,min , P c,max is the minimum charging power and maximum charging power of energy storage; P d,min , P d,max is the minimum discharge power and maximum discharge power of energy storage;

[0102] During the frequency regulation process, the output of wind turbines participating in the frequency regulation and their reserve level should satisfy the constraint relationship, and the wind turbine's additional output cannot exceed its active reserve margin. Constraints to be satisfied:

[0103] 0≤ΔP W,t ≤γ t ·P MPPT,t

[0104] In the formula, ΔP W,t P is the change in active output of the wind turbine participating in the frequency response; MPPT,tis the active output of the fan in MPPT control mode; γ t It is the load shedding standby level for the fan.

[0105] S1.2, using the PSO algorithm to solve the energy storage capacity optimization model and obtain the required energy storage capacity solution.

[0106] S2: Design a fuzzy controller for the dynamic frequency response of the wind-storage combined system and formulate a wind power and energy storage coordinated control strategy based on fuzzy logic. The specific steps include:

[0107] S2.1, design the dynamic frequency response fuzzy controller of the wind-storage combined system and determine the controller input and output.

[0108] Reduce the load level of the fan t , energy storage state of charge SOC t , as the input variable of the fuzzy controller;

[0109] Energy storage state of charge SOC t Reflects the amount of electricity stored in the energy storage at time t. Function of the percentage of wind turbine load reduction and reserve retention χ t Reflects the ability of the fan to participate in frequency regulation at time t. The calculation formula is as follows:

[0110]

[0111] In the formula, ΔP R,t is the frequency modulation requirement of the system at time t; γ t Leave a spare level for fan load shedding; P m,t is the active power output of the wind turbine operating in MPPT mode at time t.

[0112] The output of the fuzzy controller is the system frequency modulation allocation coefficient ε t , which is dynamically determined by the fuzzy controller.

[0113] Partition coefficient ε t It can determine the dynamic allocation of active power demand between wind turbines and energy storage devices in the process of active participation of the wind-storage combined system in system frequency regulation. When the total frequency regulation demand of the wind-storage combined system is certain, the frequency regulation power ΔP borne by the wind turbine and energy storage for frequency response is W,t and ΔP ES,t Dynamically determined by the system frequency modulation allocation coefficient.

[0114]

[0115] ΔP W,t and ΔP ES,t is the change in active power output of the wind turbine and energy storage in frequency response at time t. When the total active power frequency regulation demand of the wind-storage combined system is constant, these two values ​​are given by εt Determined complementary relationship.

[0116] S2.2, formulate fuzzy logic reasoning rules to obtain the coordinated control strategy of wind power and energy storage.

[0117] In order to achieve the dynamic coordination of wind power and energy storage to meet the system frequency regulation requirements, fuzzy logic reasoning rules are formulated to achieve the coordinated operation of the wind-storage joint system. Triangular and trapezoidal membership functions are selected to perform fuzzy segmentation of the input and output space for control.

[0118] For the input variable SOC t and χ t , and the output variable ε t , define five fuzzy linguistic variables to describe the state of the input variables: VL (very low); L (low); M (medium); H (high); VH (very high). Define corresponding fuzzy logic reasoning rules for the frequency increase and frequency decrease scenarios respectively. As shown in Figure 3(a), it is the membership function of the fuzzy controller input variable SOC. As shown in Figure 3(b), it is the membership function of the fuzzy controller input variable χ for the frequency increase scenario. As shown in Figure 3(c), it is the membership function of the fuzzy controller input variable χ for the frequency decrease scenario; as shown in Figure 3(d), it is the membership function of the fuzzy controller output variable allocation coefficient ε.

[0119] The fuzzy logic reasoning for the frequency increase scenario is shown in Table 1:

[0120] Table 1 Fuzzy logic reasoning table when frequency increases

[0121]

[0122]

[0123] 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 power grid. At this time, the wind turbine can be less loaded to improve the system frequency regulation economy. 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, indicating that the energy storage will bear more frequency regulation demand; 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, indicating that the wind turbine will bear more frequency regulation demand; 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, indicating that the energy storage will bear the frequency regulation demand first.

[0124] The fuzzy logic reasoning for the frequency reduction scenario is shown in Table 2:

[0125] Table 2 Fuzzy logic reasoning table when frequency decreases

[0126]

[0127] When the system frequency decreases, the energy storage device is in a discharging state, and the wind turbine should generate additional active power to support the recovery of the system frequency. A higher SOC value means that the energy storage has sufficient power reserves to generate active power to the grid for frequency support. 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 demands; when the SOC value is low 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 will bear more frequency regulation demands; 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 energy storage will bear the frequency regulation demands first.

[0128] In order to verify the economic and effectiveness of the optimal configuration of energy storage capacity and the coordinated control strategy in the wind-storage combined system to participate in frequency regulation control, a Figure 2 The wind farm in the system has an output of 200MW, and is equipped with energy storage equipment for auxiliary frequency regulation to form a wind-storage combined system.

[0129] 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, normalized for all cost parameters.

[0130] The per unit values ​​of the variable parameters in the energy storage capacity optimization model are shown in Table 3:

[0131] Table 3 Variable parameters in the capacity optimization model

[0132]

[0133] 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.

[0134] 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. Taking into account the volatility of actual wind speed, in order to simplify the analysis, the reserved spare capacity of the wind turbine is set to 10% of the maximum output power during MPPT control, and the initial SOC value of the energy storage is set to 0.4. In the process of frequency regulation of the wind-storage combined system, the frequency regulation strategy of wind power and energy storage is determined according to the output of the fuzzy logic controller. The output of the wind turbine during load reduction operation and the charging and discharging power of the energy storage system are as follows: Figure 4 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.

[0135] The above are only preferred embodiments of the present invention, and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the contents of the specification of the present invention should be included in the protection scope of the present invention.

Claims

1. A frequency modulation control method for a wind-storage combined system considering energy storage capacity optimization, characterized in that: The method aims to minimize the total cost of the wind-storage combined system, establishes an energy storage capacity optimization model that takes economic considerations into account, configures the frequency regulation capacity of energy storage in the wind-storage combined system, and realizes the dynamic coordinated operation of wind power and energy storage in the wind-storage combined system to participate in system frequency regulation; the method includes the following steps: Step 1: Establish an energy storage capacity optimization configuration model that takes economic considerations into account, and determine the optimal energy storage capacity configuration required for the wind farm; the implementation of step 1 specifically includes the following steps: Step 1.1, establish energy storage capacity optimization model; The objective function of the energy storage capacity optimization model is to minimize the total cost of system frequency regulation operation. The cost function is obtained by the difference between the total operating cost and the frequency regulation benefit: minF=C total -I total Among them, F is the total cost of system frequency regulation operation, C total is the total operating cost of the wind-storage combined system, I total For FM benefits; 1) The total operating cost of the wind-storage combined system is: C total =C con +C dam +C soc +C cha Among them, C con is the investment and construction cost of energy storage equipment, C dam is the attenuation loss during the energy storage operation, C soc is the penalty cost of SOC exceeding the limit of energy storage, C cha The opportunity cost of wind turbine load reduction operation; 1.1) C con The investment and construction cost of energy storage equipment is: C con =λ v V r +λ p P r In the formula, λ v is the unit capacity price; p is the price per unit power; V r is the rated capacity of energy storage, in MWh; P r is the rated power of the energy storage, in MW; 1.2) C dam The attenuation loss during energy storage operation is: In the formula, β v is the energy storage attenuation loss coefficient; P es,t is the active output value of energy storage participating in frequency regulation; t0, t s are the start and end times of the optimization operation respectively; 1.3) C soc The penalty cost of energy storage SOC exceeding the limit is: In the formula, α SOC is the energy storage SOC over-limit cost coefficient; t0, t s are the start and end times of the optimization operation; SOC t is the SOC value of energy storage at time t; SOC max , SOC min is the upper and lower limits of the energy storage SOC value; μ H For energy storage in SOC t >SOC max The type flag when μ L For energy storage in SOC t <SOC min Type flag when 1.4) C cha The opportunity cost caused by the wind turbine load reduction operation, that is, the loss of revenue due to the wind turbine load reduction operation is: In the formula, τ t is the market electricity price; γ t P is the fan load shedding standby level; MPPT,t is the active output of the fan in MPPT control mode; t0, t s are the start and end times of the optimization operation respectively; 2)I total The frequency modulation revenue calculation formula is as follows: In the formula, ηre q P is the unit compensation price of frequency regulation electricity of wind-storage combined system; w,t is the active output value of the fan participating in frequency regulation, P es,t is the active output value of energy storage participating in frequency regulation; t0, t s are the start and end times of the optimization operation respectively; Step 1.2, the PSO algorithm solves the energy storage capacity optimization model to obtain the required energy storage capacity solution; Step 2: Design a fuzzy controller for the dynamic frequency response of the wind-storage combined system and formulate a wind power and energy storage coordinated control strategy based on fuzzy logic; the implementation of step 2 specifically includes the following steps: Step 2.1, design the dynamic frequency response fuzzy controller of the wind-storage combined system and determine the controller input and output; Step 2.1.1 Reduce the load level of the fan to t , energy storage state of charge SOC t , as the input variable of the fuzzy controller; Step 2.1.2: Function of the percentage of wind turbine load shedding and reserve reserve χ t Reflects the ability of the fan to participate in frequency regulation at time t. The calculation formula is as follows: Where ΔP R,t is the frequency modulation requirement of the system at time t; γ t Leave a spare level for fan load shedding; P m,t is the active output of the wind turbine operating in MPPT mode at time t; Step 2.1.3: The output of the fuzzy controller is the system frequency modulation allocation coefficient ε t When the total frequency regulation demand of the wind-storage combined system is constant, the frequency regulation power ΔP borne by the wind turbine and energy storage for frequency response is W,t and ΔP ES,t Dynamically determined by the system frequency modulation allocation coefficient: ΔP W,t and ΔP ES,t are the active output changes of the wind turbine and energy storage in frequency response at time t, ε t is the allocation coefficient. When the total active power frequency regulation demand of the wind-storage combined system is constant, ΔP W,t and ΔP ES,t Because of ε t The complementary relationship of decision; Step 2.2, formulate fuzzy logic reasoning rules to obtain the wind power and energy storage coordinated control strategy; Select triangle and trapezoid membership functions to perform fuzzy segmentation of input and output space for control; For the input variable SOC t and χ t , and the output variable ε t , five fuzzy linguistic variables are defined to describe the state of the input variables: VL is very low; L is low; M is medium; H is high; VH is very high; and corresponding fuzzy logic inference rules are defined for the frequency increase and frequency decrease scenarios respectively.

2. The frequency regulation control method of the wind-storage combined system considering the optimization of energy storage capacity according to claim 1 is characterized in that: The constraints of the energy storage capacity optimization model include: energy storage system SOC constraints, energy storage system charging and discharging power constraints, and wind turbine frequency regulation power constraints; 1) The SOC of the energy storage system meets the constraints during the frequency regulation of the wind-storage combined system: SOC c,min ≤SOC c,t ≤SOC c,max SOC d,min ≤SOC d,t ≤SOC d,max In the formula, SOC c,t is the SOC value of energy storage at time t during the charging process; SOC d,t is the SOC value of energy storage at time t during the discharge process; SOC c,min , SOC c,max The maximum and minimum SOC of the energy storage system during the charging process; SOC d,min , SOC d,max is the maximum and minimum SOC of the energy storage system during the discharge process; 2) The charging and discharging power of the energy storage system should meet the constraints: P c,min ≤P c,t ≤P c,max P d,min ≤P d,t ≤P d,max Where P c,t P is the charging power of energy storage at time t during the charging process; d,t is the discharge power of energy storage at time t during the discharge process; P c,min , P c,max is the minimum charging power and maximum charging power of energy storage; P d,min , P d,max is the minimum discharge power and maximum discharge power of energy storage; 3) During the frequency regulation process, the output of the wind turbine participating in the frequency regulation and its reserve level should satisfy the constraint relationship. The additional output of the wind turbine should not exceed its active reserve margin, and the constraint conditions should be met: 0≤ΔP W,t ≤γ t ·P MPPT,t ; Where ΔP W,t P is the change in active output of the wind turbine participating in the frequency response; MPPT,t is the active output of the fan in MPPT control mode; γ t It is the load shedding standby level for the fan.

Images