Frequency cooperative control method, system, storage medium and equipment for Saggoke new energy direct-current delivery system

Abstract

The invention discloses a frequency cooperative control method, system, storage medium and equipment for a Sagomean new energy direct current delivery system, and belongs to the technical field of power system frequency modulation. The objective of the invention is to solve the problem that there is no frequency cooperative control method capable of comprehensively considering various frequency modulation devices included in a Saggoke new energy direct current delivery system at present. The method comprises the following steps of: firstly, establishing a frequency response model of the Sagoligo new energy direct current delivery system considering thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC frequency modulation response by thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC frequency modulation control modules in a detailed electromagnetic transient model of the Sagoligo new energy direct current delivery system; and then a comprehensive score is obtained according to the frequency modulation performance index and the frequency modulation cost index, and a droop coefficient and a virtual inertia coefficient of wind power, photovoltaic and electrochemical energy storage and MMC-HVDC are obtained through optimization by adopting a differential evolution algorithm, so that frequency cooperative control is realized.

Description

Technical Field

[0001] The present application belongs to the technical field of power system frequency regulation, and specifically relates to a frequency coordination control method, system, storage medium and equipment for a new energy direct current transmission system. Background Art

[0002] Based on the requirements of development, we should accelerate the development of new wind power and photovoltaic bases focusing on deserts, Gobi and desert areas. However, such large-scale new energy bases are usually far away from the main grid and transmitted through large-capacity DC. They lack conventional supporting power sources. In addition, the output of new energy units is uncertain and volatile, which makes the frequency problem of the "Shagohuang" new energy DC transmission system prominent. In order to improve the frequency support capability of the system and ensure the stable operation of the "Shagohuang" new energy base, it is urgent to propose a frequency coordination control method that takes into account the frequency modulation response of each equipment in the base.

[0003] Currently, there are many solutions for frequency coordinated control, such as:

[0004] Wang Sen et al. proposed a “wind-storage coordinated control strategy for improving secondary frequency drop” (Modern Electric Power, 2024, 1-11). This article can reduce the system power shortage by limiting the power drop value of the wind turbine, and can significantly improve the secondary frequency drop of the system by combining with the rapid adjustment of energy storage. However, this method has limited effect on improving the overall frequency response characteristics of the system.

[0005] Chen Peng et al. proposed a "wind-fire-storage coordinated frequency regulation control strategy based on multi-scale decomposition" (Acta Energiae Solaris Sinica, 2024, 45(3): 428-435). This article considers the different response time scales of wind-fire-storage when participating in grid frequency regulation, and uses a multi-scale decomposition method of frequency difference instructions based on wavelet packet decomposition and a complementary matching scheme in which wind-fire-storage responds to medium, low and high frequency difference components respectively. This method makes full use of the frequency regulation capacity of wind storage to improve the frequency response characteristics of the system. However, this method considers limited frequency regulation equipment and cannot meet the needs of the "Shagohuang" new energy DC transmission system.

[0006] In summary, the frequency coordination control methods currently proposed are mostly targeted at a few types of frequency regulation equipment, and cannot fully take into account the thermal, wind, solar, storage and MMC equipment included in the "Shagohuang" new energy DC transmission system. In addition, the existing methods are mostly targeted at some power plants or large power grids, and their adaptability to the "Shagohuang" new energy DC transmission system remains to be verified. Summary of the invention

[0007] This application aims to solve the problem that there is currently no frequency coordination control method that can comprehensively consider the various frequency modulation equipment included in the Shagohuang New Energy DC transmission system.

[0008] In a first aspect, an embodiment of the present application provides a frequency coordination control method of a Shagohuang renewable energy DC transmission system, comprising the following steps:

[0009] Based on the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, a frequency response model of the Shagohuang new energy DC transmission system is established, which takes into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC. MMC-HVDC is a flexible DC transmission system.

[0010] The frequency response model of the Shagohuang renewable energy DC transmission system includes a frequency response model of a thermal power unit, a frequency response model of a wind power unit, a frequency response model of a photovoltaic unit, a frequency response model of an electrochemical energy storage device, and a frequency response model of an MMC-HVDC;

[0011] According to the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model are determined, as well as the frequency regulation dead zone of the thermal power unit corresponding to the frequency response model, the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work proportion coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit. The frequency regulation power capacity proportion of the thermal power unit, wind power, photovoltaic, energy storage and flexible DC, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, energy storage and flexible DC and the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work proportion coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit and the regulation coefficient of the thermal power unit are input into the established frequency response model of the Shagohuang new energy DC transmission system to obtain the frequency response;

[0012] Based on the frequency response, the frequency regulation performance index and the frequency regulation cost index are determined, and a comprehensive score is obtained according to the frequency regulation performance index and the frequency regulation cost index, and the differential evolution algorithm is used to optimize the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC; the frequency regulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmax The frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ;

[0013] Frequency coordinated control is achieved based on the optimized droop coefficients and virtual inertia coefficients of wind power, photovoltaics, electrochemical energy storage and MMC-HVDC.

[0014] Furthermore, the frequency response model of the MMC-HVDC is as follows:

[0015]

[0016] In the formula, ΔP MMC (s) is the frequency response of MMC-HVDC, K MMC1 is the virtual inertia coefficient of MMC-HVDC, K MMC2 is the MMC-HVDC droop coefficient, T MMC is the inertia time constant of MMC-HVDC frequency modulation; s is the Laplace operator, and Δf(s) is the frequency deviation of Shagohuang New Energy Base.

[0017] Furthermore, the frequency response model of the electrochemical energy storage device is:

[0018]

[0019] In the formula, ΔP BESS (s) is the frequency response of the electrochemical energy storage device, K BESS1 is the virtual inertia coefficient of the electrochemical energy storage device, K BESS2 is the droop coefficient of the electrochemical energy storage device, T BESS is the frequency modulation inertia time constant of the electrochemical energy storage device; s is the Laplace operator, and Δf(s) is the frequency deviation of the Shagohuang new energy base.

[0020] Furthermore, the frequency deviation of the Shagohuang New Energy Base Where ΔP L is the active power disturbance, ΔP G (s) is the weighted sum of the frequency modulation power capacity of each equipment, H is the system equivalent inertia time constant, and D is the system load damping coefficient.

[0021] Furthermore, the process of obtaining a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index includes the following steps:

[0022] For the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir , maximum frequency change rate r fmax and frequency adjustment mileage compensation cost C fr Perform standardization to obtain a standardized value v1 of the maximum frequency deviation, a standardized value v2 of the transient steady-state frequency deviation, a standardized value v3 of the lowest frequency point time, a standardized value v4 of the maximum frequency change rate, and a standardized value v5 of the frequency modulation mileage compensation cost;

[0023] Based on the weights of various frequency regulation performance indicators and frequency regulation cost indicators, a comprehensive score G=a1·v1+a2·v2+a3·v3+a4·v4+a5·v5 is obtained, where a1 to a5 are their corresponding weights respectively.

[0024] Furthermore, the process of optimizing the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC using differential evolution algorithm includes the following steps:

[0025] S401. Based on the input of the capacity proportion of each equipment, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheating time coefficient of the thermal power unit, the regulation coefficient of the thermal power unit, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC, and the frequency response model of the frequency regulation dead zone of each equipment; the frequency regulation response time of each equipment is input into the frequency response model;

[0026] S402, within the frequency modulation parameter group range, based on the droop coefficient and virtual inertia coefficient of each equipment obtained in S401, generate the first batch of n sets of frequency modulation parameter groups according to a fixed step length;

[0027] S403, assigning each set of frequency modulation parameter groups to the established frequency response model, taking the failure of the largest thermal power plant in the system as the typical working condition, calculating the frequency modulation performance index and frequency modulation cost index of the frequency response model under the typical working condition; setting the weights of the maximum frequency deviation, the transient steady-state frequency deviation, the lowest frequency point time, the maximum frequency change rate and the frequency modulation mileage compensation cost according to actual needs, quantitatively calculating the comprehensive score G of the first batch of n sets of frequency modulation parameter groups, comparing and selecting the one with the higher score, and obtaining the optimal frequency modulation parameter group in the first batch of frequency modulation parameter groups;

[0028] S404, within the frequency modulation parameter group range, using the differential evolution algorithm to iteratively optimize the droop coefficient and virtual inertia coefficient of each equipment to generate the next batch of frequency modulation parameter groups;

[0029] S405, looping and iterating steps S403 and S404 until the upper limit of the number of iterations is reached, and obtaining the optimized droop coefficient and virtual inertia coefficient of each equipment.

[0030] Furthermore, in the process of inputting the frequency modulation response time of each device into the frequency response model, the frequency modulation response time of each device is obtained by the following steps:

[0031] The electromagnetic transient model corresponding to each equipment is connected to a system consisting of a unit with infinite rated capacity and a line. The voltage and frequency of the system remain constant, that is, the rated capacity is considered to be infinite. At time t0, a frequency step drop signal is input to the frequency modulation control module of each equipment. The time from time t0 to the active power reaching 90% of the active power target value and entering the ±2%P n The time value of the time consumed, that is, the frequency modulation response time T s ;P n It is the rated active power.

[0032] In a second aspect, the embodiment of the present application provides a frequency coordination control system of a Shagohuang new energy DC transmission system, which includes:

[0033] The frequency response model construction unit of Shagohuang new energy DC transmission system: The frequency response model of Shagohuang new energy DC transmission system taking into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is established by using the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of Shagohuang new energy DC transmission system. MMC-HVDC is a flexible DC transmission system.

[0034] The frequency response model of the Shagohuang renewable energy DC transmission system includes a frequency response model of a thermal power unit, a frequency response model of a wind power unit, a frequency response model of a photovoltaic unit, a frequency response model of an electrochemical energy storage device, and a frequency response model of an MMC-HVDC;

[0035] Frequency response model parameter assignment unit: According to the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, determine the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage, and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model, as well as the frequency regulation dead zone of the thermal power unit corresponding to the frequency response model, the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit. Input the frequency regulation power capacity proportion of the thermal power unit, wind power, photovoltaic, energy storage, and flexible DC, as well as the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, energy storage, and flexible DC, and the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit into the established Shagohuang new energy DC transmission system frequency response model to obtain the frequency response;

[0036] Droop coefficient and virtual inertia coefficient optimization unit: determine the frequency regulation performance index and frequency regulation cost index based on the frequency response, obtain a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index, and use the differential evolution algorithm to optimize the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC; the frequency regulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmax The frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ;

[0037] Frequency coordinated control control unit: frequency coordinated control is achieved based on the optimized droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC.

[0038] Furthermore, the frequency response model of the MMC-HVDC is as follows:

[0039]

[0040] In the formula, ΔP MMC (s) is the frequency response of MMC-HVDC, K MMC1 is the virtual inertia coefficient of MMC-HVDC, K MMC2 is the MMC-HVDC droop coefficient, T MMC is the inertia time constant of MMC-HVDC frequency modulation; s is the Laplace operator, and Δf(s) is the frequency deviation of Shagohuang New Energy Base.

[0041] Furthermore, the frequency response model of the electrochemical energy storage device is:

[0042]

[0043] In the formula, ΔP BESS (s) is the frequency response of the electrochemical energy storage device, K BESS1 is the virtual inertia coefficient of the electrochemical energy storage device, K BESS2 is the droop coefficient of the electrochemical energy storage device, T BESS is the frequency modulation inertia time constant of the electrochemical energy storage device; s is the Laplace operator, and Δf(s) is the frequency deviation of the Shagohuang new energy base.

[0044] Furthermore, the frequency deviation of the Shagohuang New Energy Base Where ΔP L is the active power disturbance, ΔP G (s) is the weighted sum of the frequency modulation power capacity of each equipment, H is the system equivalent inertia time constant, and D is the system load damping coefficient.

[0045] Furthermore, the process of obtaining a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index includes the following steps:

[0046] For the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir , maximum frequency change rate r fmax and frequency adjustment mileage compensation cost C fr Perform standardization to obtain a standardized value v1 of the maximum frequency deviation, a standardized value v2 of the transient steady-state frequency deviation, a standardized value v3 of the lowest frequency point time, a standardized value v4 of the maximum frequency change rate, and a standardized value v5 of the frequency modulation mileage compensation cost;

[0047] Based on the weights of various frequency regulation performance indicators and frequency regulation cost indicators, a comprehensive score G=a1·v1+a2·v2+a3·v3+a4·v4+a5·v5 is obtained, where a1 to a5 are their corresponding weights respectively.

[0048] Furthermore, the process of optimizing the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC using differential evolution algorithm includes the following steps:

[0049] S401. Based on the input of the capacity proportion of each equipment, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheating time coefficient of the thermal power unit, the regulation coefficient of the thermal power unit, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC, and the frequency response model of the frequency regulation dead zone of each equipment; the frequency regulation response time of each equipment is input into the frequency response model;

[0050] S402, within the frequency modulation parameter group range, based on the droop coefficient and virtual inertia coefficient of each equipment obtained in S401, generate the first batch of n sets of frequency modulation parameter groups according to a fixed step size;

[0051] S403, assigning each set of frequency modulation parameter groups to the established frequency response model, taking the failure of the largest thermal power plant in the system as the typical working condition, calculating the frequency modulation performance index and frequency modulation cost index of the frequency response model under the typical working condition; setting the weights of the maximum frequency deviation, the transient steady-state frequency deviation, the lowest frequency point time, the maximum frequency change rate and the frequency modulation mileage compensation cost according to actual needs, quantitatively calculating the comprehensive score G of the first batch of n sets of frequency modulation parameter groups, comparing and selecting the one with the higher score, and obtaining the optimal frequency modulation parameter group in the first batch of frequency modulation parameter groups;

[0052] S404, within the frequency modulation parameter group range, using the differential evolution algorithm to iteratively optimize the droop coefficient and virtual inertia coefficient of each equipment to generate the next batch of frequency modulation parameter groups;

[0053] S405, looping and iterating steps S403 and S404 until the upper limit of the number of iterations is reached, and obtaining the optimized droop coefficient and virtual inertia coefficient of each equipment.

[0054] Furthermore, in the process of inputting the frequency modulation response time of each device into the frequency response model, the frequency modulation response time of each device is obtained by the following steps:

[0055] The electromagnetic transient model corresponding to each equipment is connected to a system consisting of a unit with infinite rated capacity and a line. The voltage and frequency of the system remain constant, that is, the rated capacity is considered to be infinite. At time t0, a frequency step drop signal is input to the frequency modulation control module of each equipment. The time from time t0 to the active power reaching 90% of the active power target value and entering the ±2%P n The time value of the time consumed, that is, the frequency modulation response time T s ;P n It is the rated active power.

[0056] In a third aspect, an embodiment of the present application provides a computer storage medium, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the frequency coordination control method of the Shagohuang new energy DC transmission system.

[0057] In the fourth aspect, an embodiment of the present application provides a frequency coordination control device for a Shagohuang new energy DC transmission system, the device comprising a processor and a memory, the memory storing at least one instruction, the at least one instruction being loaded and executed by the processor to implement a frequency coordination control method for a Shagohuang new energy DC transmission system.

[0058] Compared with the prior art, the beneficial effects of this application are:

[0059] In view of the current situation that the frequency support capability of the Shagohuang new energy DC transmission system is weak and the frequency support capability of each equipment in the base has yet to be explored, this application comprehensively considers the frequency modulation response of wind power, photovoltaics, electrochemical energy storage and MMC-HVDC, and proposes a frequency coordination control method and system for the Shagohuang new energy DC transmission system. This application establishes a system frequency response model based on wind power, photovoltaics, electrochemical energy storage and MMC-HVDC, and in particular, this application proposes a frequency response model of MMC-HVDC, so that the new energy DC transmission system of this application can include multiple equipment such as fire, wind, light, storage and MMC to meet the needs of the "Shagohuang" new energy DC transmission system. In addition, this application combines the proposed evaluation index system and differential evolution algorithm to optimize the system frequency modulation parameters. On the established frequency response model, according to the weights of the maximum frequency deviation, transient steady-state frequency deviation, frequency minimum point time, maximum frequency change rate and frequency modulation mileage compensation cost, the comprehensive score of the first batch of frequency modulation parameter groups is quantitatively calculated, and then the droop coefficient and virtual inertia coefficient of each equipment are optimized through iteration to obtain the optimal control parameters. Therefore, this application can fully call the frequency modulation capabilities of each equipment and effectively improve the system frequency response characteristics while ensuring economy. This application can provide technical support for the new energy consumption and safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is the topology diagram of the Shagohuang new energy DC transmission system for this application;

[0061] Figure 2 This is a frequency response model diagram of the Shagohuang new energy DC transmission system of this application;

[0062] Figure 3 This is a flow chart of frequency modulation parameter optimization for this application;

[0063] Figure 4 This is a simulation comparison chart before and after the frequency modulation parameters are optimized for this application. DETAILED DESCRIPTION

[0064] This application proposes a frequency coordination control method and equipment for the Shagohuang new energy direct current transmission system, which comprehensively considers the frequency modulation response of wind power, photovoltaics, electrochemical energy storage and MMC-HVDC, and optimizes the system frequency modulation parameters based on the established system frequency response model, combined with the proposed evaluation index system and differential evolution algorithm, to fully call on the frequency modulation capabilities of each equipment and effectively improve the system frequency response characteristics while ensuring economy. This method can provide technical support for the new energy consumption and safe and stable operation of the power system. The following is a detailed description of this application in conjunction with specific implementation methods.

[0065] Specific implementation method one.

[0066] This embodiment is a frequency coordination control method for the Shagohuang renewable energy DC transmission system. Figure 1 The topology of the Shagohuang renewable energy DC transmission system shown in the figure is used as an example to illustrate, which specifically includes thermal power, wind power, photovoltaic, electrochemical energy storage, MMC-HVDC, LCC-HVDC and base loads. It should also be noted that this implementation method is based on Figure 1 The topology is used as an example for explanation. When the existing Shagohuang new energy DC transmission system does not include all the elements described above, the method of the present application is applicable, and the present application will not provide additional explanation of the present application based on other topologies.

[0067] A frequency coordination control method for a Shagohuang renewable energy DC transmission system described in this embodiment includes the following steps:

[0068] S1. Establish a detailed electromagnetic transient model of the Shagohuang renewable energy DC transmission system:

[0069] First, according to the "Planning and Layout Plan for Large-scale Wind Power and Photovoltaic Bases with a Focus on Deserts, Gobi and Wasteland Areas" issued by the National Energy Administration, the technical plan of the Shagohuang New Energy DC Transmission System and the capacity ratio of each equipment are established. The equipment includes thermal power, wind power, photovoltaics, energy storage, MMC-HVDC, and MMC-HVDC is a flexible DC transmission system; according to the national standard GB / T40595-2021, the actual unit model and the actual needs of the Shagohuang New Energy DC Transmission System, the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of wind power, photovoltaics, electrochemical energy storage and flexible DC in the Shagohuang New Energy DC Transmission System are set, as well as the frequency regulation dead zone of the thermal power unit, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit.

[0070] Then, the electromagnetic transient models of thermal power, wind power, photovoltaics, energy storage and flexible direct current are constructed. Based on the electromagnetic transient models of thermal power, wind power, photovoltaics, energy storage and flexible direct current, the detailed electromagnetic transient model of the Shagohuang new energy direct current transmission system is obtained. The frequency modulation control modules in the electromagnetic transient models of thermal power, wind power, photovoltaics, energy storage and flexible direct current constitute the frequency control link of the detailed electromagnetic transient model of the Shagohuang new energy direct current transmission system.

[0071] S2. Based on the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, a frequency response model of the Shagohuang new energy DC transmission system taking into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is established:

[0072] Based on the detailed electromagnetic transient model of the Shagohuang New Energy DC transmission system, the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model are determined, as well as the frequency regulation dead zone of the corresponding frequency response model of the thermal power unit, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit.

[0073] The frequency dead zone refers to the frequency difference set to prevent unnecessary actions when the frequency difference changes within a small range in the Shagohuang New Energy Base. When the frequency control modules of the Shagohuang New Energy Base are greater than the frequency dead zone, the frequency control modules are put into operation. db_TH is the frequency regulation dead zone corresponding to the thermal power unit, f db_W is the frequency regulation dead zone corresponding to the wind turbine, f db_PV is the frequency regulation dead zone corresponding to the photovoltaic unit, f db_BESS is the frequency modulation dead zone corresponding to electrochemical energy storage, f db_MMC It is the frequency modulation dead zone corresponding to MMC-HVDC.

[0074] According to the detailed electromagnetic transient model and frequency control link of the Shagohuang renewable energy DC transmission system, the frequency response model of the Shagohuang renewable energy DC transmission system taking into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is obtained, as shown in the attached figure. Figure 2 As shown in the figure, the frequency response model of Shagohuang renewable energy DC transmission system includes:

[0075] Frequency response model of thermal power units:

[0076]

[0077] Where ΔP TH (s) is the frequency response of the thermal power unit, K M is the mechanical advantage coefficient, F H is the work proportionality coefficient of the high-pressure steam cylinder, T R is the steam cylinder reheating time coefficient, s is the Laplace operator, R TH is the regulation coefficient of thermal power units, and Δf(s) is the frequency deviation of Shagohuang New Energy Base.

[0078] Frequency response model of wind turbine:

[0079]

[0080] Where ΔP W (s) is the frequency response of the wind turbine, K W1 is the virtual inertia coefficient of the wind turbine, K W2 is the droop coefficient of the wind turbine, TW is the inertia time constant of wind power frequency regulation.

[0081] Frequency response model of photovoltaic cells:

[0082]

[0083] Where ΔP PV (s) is the frequency response of the photovoltaic unit, K PV1 is the virtual inertia coefficient of the photovoltaic unit, K PV2 is the droop coefficient of the photovoltaic unit, T PV is the inertia time constant of photovoltaic frequency modulation.

[0084] Frequency response model of electrochemical energy storage device:

[0085]

[0086] Where ΔP BESS (s) is the frequency response of the electrochemical energy storage device, K BESS1 is the virtual inertia coefficient of the electrochemical energy storage device, K BESS2 is the droop coefficient of the electrochemical energy storage device, T BESS is the frequency modulation inertia time constant of the electrochemical energy storage device.

[0087] Frequency response model of MMC-HVDC:

[0088]

[0089] Where ΔP MMC (s) is the frequency response of MMC-HVDC, K MMC1 is the virtual inertia coefficient of MMC-HVDC, K MMC2 is the MMC-HVDC droop coefficient, T MMC is the inertia time constant of MMC-HVDC frequency modulation.

[0090] Frequency deviation model of Shagohuang new energy base:

[0091]

[0092]

[0093] Where ΔP L is the active power disturbance, ΔP G (s) is the weighted sum of the frequency modulation power capacity of each equipment, r S_TH is the proportion of frequency regulation power capacity of thermal power units, r S_W is the proportion of wind turbine frequency modulation power capacity, r S_PV is the proportion of frequency modulation power capacity of photovoltaic units, r S_BESSis the proportion of electrochemical energy storage frequency modulation power capacity, r S_MMC is the proportion of MMC-HVDC frequency modulation power capacity, H is the system equivalent inertia time constant, and D is the system load damping coefficient; H TH is the inertia time constant of the thermal power unit, S n_ty and S n_total are the capacity of each equipment (including thermal power TH, wind power W, photovoltaic PV, electrochemical energy storage BESS and MMC-HVDC) and the total system capacity, r S_ty is the capacity ratio of each equipment.

[0094] Input active power disturbance ΔP in the frequency deviation model of Shagohuang new energy base L The frequency response deviation Δf(s) is output through the model main loop, and the output Δf(s) is calculated in the frequency response loop of each device and subtracted from the input value to generate a deviation signal, which is then processed through the model main loop for the next step.

[0095] S3. Test the frequency modulation response time of wind power, photovoltaic power, electrochemical energy storage and MMC-HVDC in the Shagohuang New Energy DC transmission system;

[0096] The test method for the frequency modulation response time of wind power, photovoltaic power, electrochemical energy storage and MMC-HVDC is as follows: the electromagnetic transient models of the above-mentioned equipment are connected to the infinite system (a system composed of a rated capacity infinite unit and line, the voltage and frequency of the system are kept constant and regarded as infinite), and the frequency step drop signal (dropped to 49.9Hz) is input to the frequency modulation control module of each equipment at time t0, and the time from time t0 to the active power reaching 90% of the active power target value and entering ±2%P is calculated. n (This time is t1) time consumption, P n is the rated active power, which is the frequency modulation response time T s .

[0097] S4. Based on the evaluation index system composed of frequency regulation performance index and frequency regulation cost index and differential evolution algorithm, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC are optimized;

[0098] The frequency modulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmax The frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ; Among them, r fmax The values ​​can be directly obtained by calculating the data. The calculation methods of other indicators are as follows:

[0099] Δf nadir =f nadir -f n (8)

[0100] In the formula, f nadir is the minimum frequency value of Shagohuang New Energy Base, f n This is the rated frequency of the Shagohuang New Energy Base.

[0101] Δf qss =f qss -f n (9)

[0102] In the formula, f qss This is the temporary steady-state frequency of the Shagohuang New Energy Base.

[0103] T nadir =t nadir -t0 (10)

[0104] In the formula, t nadir is the moment when the frequency of Shagohuang New Energy Base reaches the lowest point, and t0 is the moment when the disturbance of Shagohuang New Energy Base begins.

[0105] C fr =∑C fr_ty (|P peak_ty -P 0_ty |+|P qss_ty -P peak_ty |) (11)

[0106] In the formula, C fr_ty is the unit frequency regulation mileage cost of each equipment, which is obtained according to the relevant regulations of the power grid where the system is located; P peak_ty is the peak active power of each equipment during the frequency modulation process, P 0_ty is the steady-state active power of each equipment, P qss_ty is the temporary steady-state active power of each equipment.

[0107] Standardization of each evaluation index value unifies the data range of different dimensions to between 0 and 1, eliminating the influence of data magnitude and dimension. Assuming there are n sets of frequency modulation parameter groups (droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC), each set of schemes has i frequency modulation indicators, and a comprehensive evaluation is performed among different evaluation indicators. The standardized value of the i-th frequency modulation indicator corresponding to each set of frequency modulation parameter groups is as follows:

[0108]

[0109] From this, we can calculate the standardized value v1 of the maximum frequency deviation, the standardized value v2 of the transient steady-state frequency deviation, the standardized value v3 of the lowest frequency point time, the standardized value v4 of the maximum frequency change rate, and the standardized value v5 of the frequency modulation mileage compensation cost.

[0110] Given the weights of each frequency regulation performance index and frequency regulation cost index according to actual needs, the comprehensive score G is calculated as follows:

[0111] G=a1·v1+a2·v2+a3·v3+a4·v4+a5·v5 (13)

[0112] Where a1 is the weight of the maximum frequency deviation, a2 is the weight of the transient frequency deviation, a3 is the weight of the lowest frequency point time, a4 is the weight of the maximum frequency change rate, and a5 is the weight of the frequency regulation mileage compensation cost.

[0113] As attached Figure 3 As shown in the figure, the process of optimizing the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is as follows:

[0114] S401, input the capacity proportion of each equipment, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheating time coefficient of the thermal power unit, the regulation coefficient of the thermal power unit, the droop coefficient and the virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC into the frequency response model established in S2; assign the frequency regulation dead zone of each equipment as a constraint to the established frequency response model;

[0115] Input the frequency modulation response time of each device tested in step S3 (as the frequency modulation inertia time constant) into the established frequency response model;

[0116] S402. Within the range of the frequency modulation parameter group given in the national standard GB / T 40595-2021, based on the droop coefficient and virtual inertia coefficient of each equipment obtained in S401, generate the first batch of n sets of frequency modulation parameter groups according to a fixed step size;

[0117] S403, assigning each set of frequency modulation parameter groups to the established frequency response model, taking the failure of the largest thermal power plant in the system as the typical working condition, calculating the frequency modulation performance index and frequency modulation cost index of the frequency response model under the typical working condition; setting the weights of the maximum frequency deviation, the transient steady-state frequency deviation, the lowest frequency point time, the maximum frequency change rate and the frequency modulation mileage compensation cost according to actual needs, quantitatively calculating the comprehensive score G of the first batch of n sets of frequency modulation parameter groups, comparing and selecting the one with the higher score, and obtaining the optimal frequency modulation parameter group in the first batch of frequency modulation parameter groups;

[0118] S404. Within the range of the frequency modulation parameter group given in the national standard GB / T 40595-2021, the differential evolution algorithm is used to iteratively optimize the droop coefficient and virtual inertia coefficient of each equipment to generate the next batch of frequency modulation parameter groups;

[0119] S405, looping and iterating steps S403 and S404 until the upper limit of the number of iterations is reached, and obtaining the optimized droop coefficient and virtual inertia coefficient of each equipment.

[0120] Example:

[0121] In order to verify the effectiveness of the proposed frequency coordinated control method for the Shagohuang renewable energy DC transmission system, based on the attached Figure 1 The topological structure shown builds the electromagnetic transient model of the Shagohuang renewable energy DC transmission system, and the specific parameters are shown in Table 1.

[0122] Table 1 Main parameters of the system

[0123]

[0124] Taking the 600MW thermal power plant fault tripping as a typical working condition, the frequency curves of the system before and after parameter optimization are compared, as shown in the attached figure. Figure 4 As shown in the simulation results, the overall frequency deviation of the system is significantly reduced after the disturbance occurs, the lowest frequency point is increased by 0.0397Hz, the transient steady-state frequency is increased by 0.0232Hz, and the frequency modulation cost is not significantly increased, which proves the effectiveness of the method.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present application, which should be included in the scope of the claims of the present application. Specific implementation method 2:

[0127] This embodiment is a frequency coordination control system of the Shagohuang renewable energy DC transmission system, including:

[0128] The frequency response model construction unit of Shagohuang new energy DC transmission system: The frequency response model of Shagohuang new energy DC transmission system taking into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is established by using the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of Shagohuang new energy DC transmission system. MMC-HVDC is a flexible DC transmission system.

[0129] The frequency response model of the Shagohuang renewable energy DC transmission system includes a frequency response model of a thermal power unit, a frequency response model of a wind power unit, a frequency response model of a photovoltaic unit, a frequency response model of an electrochemical energy storage device, and a frequency response model of an MMC-HVDC;

[0130] Frequency response model of thermal power units:

[0131]

[0132] Where ΔP TH (s) is the frequency response of the thermal power unit, K M is the mechanical advantage coefficient, F H is the work proportionality coefficient of the high-pressure steam cylinder, T R is the steam cylinder reheating time coefficient, s is the Laplace operator, R TH is the regulation coefficient of thermal power units, and Δf(s) is the frequency deviation of Shagohuang New Energy Base.

[0133] Frequency response model of wind turbine:

[0134]

[0135] Where ΔP W (s) is the frequency response of the wind turbine, K W1 is the virtual inertia coefficient of the wind turbine, K W2 is the droop coefficient of the wind turbine, T W is the inertia time constant of wind power frequency regulation.

[0136] Frequency response model of photovoltaic cells:

[0137]

[0138] Where ΔP PV (s) is the frequency response of the photovoltaic unit, K PV1 is the virtual inertia coefficient of the photovoltaic unit, K PV2 is the droop coefficient of the photovoltaic unit, T PV is the inertia time constant of photovoltaic frequency modulation.

[0139] Frequency response model of electrochemical energy storage device:

[0140]

[0141] Where ΔP BESS (s) is the frequency response of the electrochemical energy storage device, K BESS1 is the virtual inertia coefficient of the electrochemical energy storage device, K BESS2 is the droop coefficient of the electrochemical energy storage device, T BESS is the frequency modulation inertia time constant of the electrochemical energy storage device.

[0142] Frequency response model of MMC-HVDC:

[0143]

[0144] Where ΔP MMC (s) is the frequency response of MMC-HVDC, K MMC1 is the virtual inertia coefficient of MMC-HVDC, K MMC2 is the MMC-HVDC droop coefficient, T MMC is the inertia time constant of MMC-HVDC frequency modulation.

[0145] Frequency deviation model of Shagohuang new energy base:

[0146]

[0147] Where ΔP L is the active power disturbance, ΔP G (s) is the weighted sum of the frequency modulation power capacity of each equipment, H is the system equivalent inertia time constant, and D is the system load damping coefficient.

[0148] Frequency response model parameter assignment unit: According to the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, determine the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage, and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model, as well as the frequency regulation dead zone of the thermal power unit corresponding to the frequency response model, the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit. Input the frequency regulation power capacity proportion of the thermal power unit, wind power, photovoltaic, energy storage, and flexible DC, as well as the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, energy storage, and flexible DC, and the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit into the established Shagohuang new energy DC transmission system frequency response model to obtain the frequency response;

[0149] Droop coefficient and virtual inertia coefficient optimization unit: determine the frequency regulation performance index and frequency regulation cost index based on the frequency response, obtain a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index, and use the differential evolution algorithm to optimize the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC; the frequency regulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmaxThe frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ;

[0150] Furthermore, the process of obtaining a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index includes the following steps:

[0151] For the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir , maximum frequency change rate r fmax and frequency adjustment mileage compensation cost C fr Perform standardization to obtain a standardized value v1 of the maximum frequency deviation, a standardized value v2 of the transient steady-state frequency deviation, a standardized value v3 of the lowest frequency point time, a standardized value v4 of the maximum frequency change rate, and a standardized value v5 of the frequency modulation mileage compensation cost;

[0152] Based on the weights of various frequency regulation performance indicators and frequency regulation cost indicators, a comprehensive score G=a1·v1+a2·v2+a3·v3+a4·v4+a5·v5 is obtained, where a1 to a5 are their corresponding weights respectively.

[0153] Furthermore, the process of optimizing the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC using differential evolution algorithm includes the following steps:

[0154] S401. Based on the input of the capacity proportion of each equipment, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheating time coefficient of the thermal power unit, the regulation coefficient of the thermal power unit, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC, and the frequency response model of the frequency regulation dead zone of each equipment; the frequency regulation response time of each equipment is input into the frequency response model;

[0155] S402, within the frequency modulation parameter group range, based on the droop coefficient and virtual inertia coefficient of each equipment obtained in S401, generate the first batch of n sets of frequency modulation parameter groups according to a fixed step length;

[0156] S403, assigning each set of frequency modulation parameter groups to the established frequency response model, taking the failure of the largest thermal power plant in the system as the typical working condition, calculating the frequency modulation performance index and frequency modulation cost index of the frequency response model under the typical working condition; setting the weights of the maximum frequency deviation, the transient steady-state frequency deviation, the lowest frequency point time, the maximum frequency change rate and the frequency modulation mileage compensation cost according to actual needs, quantitatively calculating the comprehensive score G of the first batch of n sets of frequency modulation parameter groups, comparing and selecting the one with the higher score, and obtaining the optimal frequency modulation parameter group in the first batch of frequency modulation parameter groups;

[0157] S404, within the frequency modulation parameter group range, using the differential evolution algorithm to iteratively optimize the droop coefficient and virtual inertia coefficient of each equipment to generate the next batch of frequency modulation parameter groups;

[0158] S405, looping and iterating steps S403 and S404 until the upper limit of the number of iterations is reached, and obtaining the optimized droop coefficient and virtual inertia coefficient of each equipment.

[0159] Furthermore, in the process of inputting the frequency modulation response time of each device into the frequency response model in step S401, the frequency modulation response time of each device is obtained by the following steps:

[0160] The electromagnetic transient model corresponding to each equipment is connected to a system consisting of a unit with infinite rated capacity and a line. The voltage and frequency of the system remain constant, that is, the rated capacity is considered to be infinite. At time t0, a frequency step drop signal is input to the frequency modulation control module of each equipment. The time from time t0 to the active power reaching 90% of the active power target value and entering the ±2%P n The time value of the time consumed, that is, the frequency modulation response time T s ;P n It is the rated active power.

[0161] Frequency coordinated control control unit: frequency coordinated control is achieved based on the optimized droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC. Specific implementation method three:

[0163] This embodiment is a computer storage medium, in which at least one instruction is stored. The at least one instruction is loaded and executed by a processor to implement the frequency coordination control method of the Shagohuang new energy DC transmission system.

[0164] It should be understood that the instructions include computer program products, software or computerized methods corresponding to any method described in this application; the instructions can be used to program a computer system, or other electronic device. Computer storage media may include readable media on which instructions are stored, which may include but are not limited to magnetic storage media, optical storage media; magneto-optical storage media include read-only memory ROM, random access memory RAM, erasable programmable memory (e.g., EPROM and EEPROM) and flash memory layers, or other types of media suitable for storing electronic instructions. Specific implementation method four:

[0166] This embodiment is a frequency coordination control device of a Shagohuang renewable energy DC transmission system, the device includes a processor and a memory, and it should be understood that it includes any device including a processor and a memory described in this application, and the device may also include other units and modules that perform display, interaction, processing, control, etc. and other functions through signals or instructions;

[0167] At least one instruction is stored in the memory, and the at least one instruction is loaded and executed by the processor to implement the frequency coordination control method of the Shagohuang new energy DC transmission system.

[0168] Those skilled in the art will appreciate that at least one instruction stored is a computer program product corresponding to the method or system. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt 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 codes. The scheme in the embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0169] The present application is described with reference to the flowcharts and / or block diagrams of the methods, systems, and computer program products according to the embodiments of the present application, and may also be used for corresponding devices. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0170] 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.

[0171] 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 A step that specifies a function in one or more boxes.

[0172] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0173] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0174] The above calculation examples of the present application are only used to explain the calculation model and calculation process of the present application in detail, and are not intended to limit the implementation methods of the present application. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the implementation methods here. All obvious changes or modifications derived from the technical solution of the present application are still within the scope of protection of the present application.

Claims

1. A frequency coordination control method for a Shagohuang renewable energy DC transmission system, characterized in that: The following steps are involved: Based on the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, a frequency response model of the Shagohuang new energy DC transmission system is established, which takes into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC. MMC-HVDC is a flexible DC transmission system. The frequency response model of the Shagohuang renewable energy DC transmission system includes a frequency response model of a thermal power unit, a frequency response model of a wind power unit, a frequency response model of a photovoltaic unit, a frequency response model of an electrochemical energy storage device, and a frequency response model of an MMC-HVDC; According to the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, determine the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage, and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model, as well as the frequency regulation dead zone of the thermal power unit corresponding to the frequency response model, the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work proportion coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit. Input the frequency regulation power capacity proportion of the thermal power unit, wind power, photovoltaic, energy storage, and flexible DC, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, energy storage, and flexible DC, and the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work proportion coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit into the established frequency response model of the Shagohuang new energy DC transmission system to obtain the frequency response; Based on the frequency response, the frequency regulation performance index and the frequency regulation cost index are determined, and a comprehensive score is obtained according to the frequency regulation performance index and the frequency regulation cost index, and the differential evolution algorithm is used to optimize the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC; the frequency regulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmax The frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ; Frequency coordinated control is achieved based on the optimized droop coefficients and virtual inertia coefficients of wind power, photovoltaics, electrochemical energy storage and MMC-HVDC.

2. The frequency coordination control method of the Shagohuang renewable energy DC transmission system according to claim 1 is characterized in that: The frequency response model of the MMC-HVDC is as follows: Where ΔP MMC (s) is the frequency response of MMC-HVDC, K MMC1 is the virtual inertia coefficient of MMC-HVDC, K MMC2 is the MMC-HVDC droop coefficient, T MMC is the MMC-HVDC frequency modulation inertia time constant; s is the Laplace operator, and Δf(s) is the frequency deviation of the Shagohuang new energy base.

3. The frequency coordinated control method of the Shagohuang renewable energy DC transmission system according to claim 1 is characterized in that: Frequency response model of electrochemical energy storage device: Where ΔP BESS (s) is the frequency response of the electrochemical energy storage device, K BESS1 is the virtual inertia coefficient of the electrochemical energy storage device, K BESS2 is the droop coefficient of the electrochemical energy storage device, T BESS The frequency modulation inertia time constant of the electrochemical energy storage device; s is the Laplace operator, and Δf(s) is the frequency deviation of the Shagohuang new energy base.

4. A frequency coordinated control method for a Shagohuang renewable energy DC transmission system according to claim 2 or 3, characterized in that: Frequency deviation of Shagohuang New Energy Base Among them, ΔP L is the active power disturbance, ΔP G (s) is the weighted sum of the frequency modulation power capacity of each equipment, H is the system equivalent inertia time constant, and D is the system load damping coefficient.

5. A frequency coordinated control method for a Shagohuang renewable energy DC transmission system according to any one of claims 1 to 3, characterized in that: The process of obtaining a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index includes the following steps: For the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir , maximum frequency change rate r fmax and frequency adjustment mileage compensation cost C fr Perform standardization to obtain a standardized value v1 of the maximum frequency deviation, a standardized value v2 of the transient steady-state frequency deviation, a standardized value v3 of the lowest frequency point time, a standardized value v4 of the maximum frequency change rate, and a standardized value v5 of the frequency modulation mileage compensation cost; Based on the weights of various frequency regulation performance indicators and frequency regulation cost indicators, a comprehensive score G=a1·v1+a2·v2+a3·v3+a4·v4+a5·v5 is obtained, where a1 to a5 are their corresponding weights respectively.

6. The frequency coordination control method of the Shagohuang renewable energy DC transmission system according to claim 1 is characterized in that: The process of optimizing the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC using differential evolution algorithm includes the following steps: S401. Based on the input of the capacity proportion of each equipment, the mechanical gain coefficient of the thermal power unit, the work proportion coefficient of the high-pressure steam cylinder of the thermal power unit, the steam cylinder reheating time coefficient of the thermal power unit, the regulation coefficient of the thermal power unit, the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC, and the frequency response model of the frequency regulation dead zone of each equipment; the frequency regulation response time of each equipment is input into the frequency response model; S402, within the frequency modulation parameter group range, based on the droop coefficient and virtual inertia coefficient of each equipment obtained in S401, generate the first batch of n sets of frequency modulation parameter groups according to a fixed step size; S403, assigning each set of frequency modulation parameter groups to the established frequency response model, taking the failure of the largest thermal power plant in the system as the typical working condition, calculating the frequency modulation performance index and frequency modulation cost index of the frequency response model under the typical working condition; setting the weights of the maximum frequency deviation, the transient steady-state frequency deviation, the lowest frequency point time, the maximum frequency change rate and the frequency modulation mileage compensation cost according to actual needs, quantitatively calculating the comprehensive score G of the first batch of n sets of frequency modulation parameter groups, comparing and selecting the one with the higher score, and obtaining the optimal frequency modulation parameter group in the first batch of frequency modulation parameter groups; S404, within the frequency modulation parameter group range, using the differential evolution algorithm to iteratively optimize the droop coefficient and virtual inertia coefficient of each equipment to generate the next batch of frequency modulation parameter groups; S405, looping and iterating steps S403 and S404 until the upper limit of the number of iterations is reached, and obtaining the optimized droop coefficient and virtual inertia coefficient of each equipment.

7. The frequency coordination control method of the Shagohuang renewable energy DC transmission system according to claim 6 is characterized in that: In the process of inputting the FM response time of each device into the frequency response model, the FM response time of each device is obtained by the following steps: The electromagnetic transient model corresponding to each equipment is connected to a system consisting of a unit with infinite rated capacity and a line. The voltage and frequency of the system remain constant, that is, the rated capacity is considered to be infinite. At time t0, a frequency step drop signal is input to the frequency modulation control module of each equipment. The time from time t0 to the active power reaching 90% of the active power target value and entering the ±2%P n The time value of the time consumed, that is, the frequency modulation response time T s ;P n It is the rated active power.

8. A frequency coordination control system for the Shagohuang renewable energy DC transmission system, characterized in that: include: The frequency response model construction unit of Shagohuang new energy DC transmission system: The frequency response model of Shagohuang new energy DC transmission system taking into account the frequency response of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC is established by using the frequency control modules of thermal power, wind power, photovoltaic, electrochemical energy storage and MMC-HVDC in the detailed electromagnetic transient model of Shagohuang new energy DC transmission system. MMC-HVDC is a flexible DC transmission system. The frequency response model of the Shagohuang renewable energy DC transmission system includes a frequency response model of a thermal power unit, a frequency response model of a wind power unit, a frequency response model of a photovoltaic unit, a frequency response model of an electrochemical energy storage device, and a frequency response model of an MMC-HVDC; Frequency response model parameter assignment unit: According to the detailed electromagnetic transient model of the Shagohuang new energy DC transmission system, determine the frequency regulation power capacity proportion of wind power, photovoltaic, energy storage, and flexible DC in the corresponding frequency response model and the frequency regulation dead zone, droop coefficient and virtual inertia coefficient of the frequency response model, as well as the frequency regulation dead zone of the thermal power unit corresponding to the frequency response model, the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit. Input the frequency regulation power capacity proportion of the thermal power unit, wind power, photovoltaic, energy storage, and flexible DC, as well as the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, energy storage, and flexible DC, and the mechanical gain coefficient of the thermal power unit, the high-pressure steam cylinder work ratio coefficient of the thermal power unit, the steam cylinder reheat time coefficient of the thermal power unit, and the regulation coefficient of the thermal power unit into the established Shagohuang new energy DC transmission system frequency response model to obtain the frequency response; Droop coefficient and virtual inertia coefficient optimization unit: determine the frequency regulation performance index and frequency regulation cost index based on the frequency response, obtain a comprehensive score based on the frequency regulation performance index and the frequency regulation cost index, and use the differential evolution algorithm to optimize the droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC; the frequency regulation performance index includes the maximum frequency deviation Δf nadir , transient steady-state frequency deviation Δf qss , Frequency minimum point time T nadir and the maximum frequency change rate r fmax The frequency regulation cost indicator includes the frequency regulation mileage compensation cost C fr ; Frequency coordinated control control unit: frequency coordinated control is achieved based on the optimized droop coefficient and virtual inertia coefficient of wind power, photovoltaic, electrochemical energy storage and MMC-HVDC.

9. A computer storage medium, characterized in that: The storage medium stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the frequency coordination control method of the Shagohuang new energy DC transmission system as described in any one of claims 1 to 7.

10. A frequency coordination control device for the Shagohuang renewable energy DC transmission system, characterized in that: The device includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement a frequency coordination control method of a Shagohuang new energy DC transmission system as described in any one of claims 1 to 7.

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