Self-adaptive energy storage coordination control method and device based on virtual synchronous machine

Abstract

The invention discloses a self-adaptive energy storage coordination control method and device based on a virtual synchronous machine, and the method comprises the steps: obtaining the real-time frequency of a new energy power system, and determining a frequency deviation; adjusting the output of the energy storage power supply based on the frequency deviation in combination with the optimal control parameter of the frequency stability response model corresponding to the energy storage power supply; adjusting the optimal control parameter and controlling the output of the energy storage power supply based on the frequency deviation after the output of the energy storage power supply is adjusted and in combination with the proportional distribution coefficient of the optimal control parameter; and the optimal control parameters are repeatedly adjusted, and the output process of the energy storage power supply is controlled until the frequency deviation reaches a preset steady-state value. The method can have high response speed and coordination performance, and can improve the economic benefit of a power grid and reduce the operation cost through stable power supply.

Description

Technical Field

[0001] The present invention belongs to the technical field of frequency stability optimization of new energy power systems, and specifically relates to an adaptive energy storage coordination control method and device based on a virtual synchronous machine. Background Art

[0002] With the transformation of the global energy structure and the rapid changes in new energy technologies, large-scale grid-connected operation of renewable energy such as wind power and solar energy has become an inevitable trend. New energy power systems play an important role in reducing carbon emissions and optimizing energy structures. However, due to their strong output volatility and difficulty in scheduling, they have brought unprecedented challenges to frequency stability. The traditional frequency control mechanism based on inertial response can no longer fully meet the regulation needs of new energy power systems. Exploring frequency control strategies suitable for the characteristics of new energy has important theoretical and practical significance.

[0003] Although various frequency control methods have been proposed and applied to actual power grids, these control methods often seem to be powerless in the face of rapidly changing power grid environments. For example, traditional PI control methods may encounter problems such as response lag and insufficient stability when dealing with large-scale renewable energy access. At the same time, although existing intelligent control methods have good adaptability, they still face challenges of high computational complexity and poor real-time performance in practical applications. In existing research, virtual synchronous generator (VSG) technology is considered to be an effective way to improve the dynamic stability of power systems after renewable energy is connected to the grid because it can simulate inertia and damping characteristics. However, VSG still faces optimization problems such as response speed and coordination performance in practical applications. How to organically combine it with VSG technology to comprehensively improve the frequency stability of renewable energy power systems is still a current research difficulty.

[0004] Therefore, in order to develop new frequency stability control strategies and improve the overall performance of the power grid, designing an adaptive energy storage coordination control strategy based on VSG is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] In view of the defects in the above-mentioned prior art, the present invention provides an adaptive energy storage coordination control method and device based on virtual synchronous machine, which can have higher response speed and coordination performance, and can improve the economic benefits of the power grid and reduce operating costs through stable power supply.

[0006] In a first aspect, the present invention provides an adaptive energy storage coordination control method based on a virtual synchronous machine, comprising:

[0007] Obtain the real-time frequency of the renewable energy power system and determine the frequency deviation;

[0008] Based on the frequency deviation, the output of the energy storage power supply is adjusted in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply;

[0009] Based on the frequency deviation after adjusting the output of the energy storage power supply and combining the proportional distribution coefficient of the optimal control parameter, the optimal control parameter is adjusted and the output of the energy storage power supply is controlled;

[0010] The optimal control parameters are repeatedly adjusted and the output process of the energy storage power supply is controlled until the frequency deviation reaches a predetermined steady-state value.

[0011] Furthermore, based on the frequency deviation, the output of the energy storage power supply is adjusted in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, including:

[0012] The frequency deviation is compared with a predetermined steady-state value, and when the frequency deviation exceeds the predetermined steady-state value, the energy storage power supply is put into operation;

[0013] Based on the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, the output power of the energy storage power supply is controlled.

[0014] Furthermore, the optimal control parameters of the energy storage power source corresponding to the frequency stability response model are determined, including:

[0015] Obtain historical operation data of the renewable energy power system and historical control parameters of the frequency stability response model;

[0016] Based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, and the benefit function, open-loop transfer function and coordinated control force function of the new energy power system are constructed;

[0017] Based on the benefit function and the open-loop transfer function, and in combination with the historical operation data of the new energy power system and the historical control parameters of the frequency stability response model, the benefit coefficient and stability coefficient corresponding to different control parameter combinations are determined respectively;

[0018] Based on the coefficient of variation, benefit coefficient and stability coefficient of each control parameter and combined with the coordinated control force function, the coordinated control force coefficient corresponding to different control parameter combinations is determined;

[0019] Based on the coordinated control force coefficient, the control parameters that achieve the optimal control effect are determined.

[0020] Furthermore, based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, including:

[0021] Based on the historical control parameters of the frequency stability response model, determine the standard deviation and average value of each control parameter;

[0022] Based on the standard deviation and the mean of each control parameter, the coefficient of variation of each control parameter was determined.

[0023] Furthermore, the coefficient of variation of each control parameter satisfies the following relationship:

[0024]

[0025] In the formula, CV i is the coefficient of variation of the ith control parameter; σ i is the standard deviation of the ith control parameter; X i is the average value of the i-th control parameter;

[0026] The benefit function satisfies the following relationship:

[0027] Δf=SP sνg +CP res +AΔP grid

[0028] Where Δf is the power system benefit function, S is the correlation between the frequency stability response model and the frequency response of the new energy power system; P svg is the active power output of the energy storage power supply controlled by the frequency stability response model; C is the frequency response coefficient of other renewable energy sources; P res is the active power output of other renewable energy sources; A is the control effectiveness coefficient; ΔP grid is the power change of the new energy power system;

[0029] The open-loop transfer function satisfies the following relationship:

[0030]

[0031] Where H(s) is the open-loop transfer function; K d is the frequency modulation coefficient; P re is the proportion of renewable energy power generation in total power generation; T d is the damping time constant; T p is the adjustment time constant; s is the complex variable in Laplace transform.

[0032] Furthermore, the coordinated control force function satisfies the following relationship:

[0033]

[0034] Where K is the coordination control function, c(n) is the benefit coefficient of the new energy power system, p(e) is the stability coefficient of the new energy power system, and q(w) is the coefficient of variation of the control parameters.

[0035] Furthermore, the stability coefficients corresponding to different control parameter combinations are determined, including:

[0036] Determine the frequency response of the open-loop transfer function based on the historical operating data of the renewable energy power system and the historical control parameters of the frequency stability response model;

[0037] Based on the frequency response of the open-loop transfer function, the gain margin of each set of control parameters is given;

[0038] Determining a stability coefficient for each set of control parameters based on the gain margin;

[0039] The calculation formula of gain margin is:

[0040]

[0041] Where GM is the gain margin, G(jω)H(jω) is the frequency response of the open-loop transfer function, and ω is the angular frequency.

[0042] Further, based on the frequency deviation after adjusting the output of the energy storage power supply, and in combination with the proportional distribution coefficient of the optimal control parameter, the optimal control parameter is adjusted and the output of the energy storage power supply is controlled, including:

[0043] Obtain frequency deviation after adjusting the output of energy storage power supply in real time;

[0044] When the frequency deviation after adjusting the output of the energy storage power source reaches a maximum value, determine the optimal control parameter with the maximum probability value of contributing to the frequency regulation of the new energy power system;

[0045] The optimal control parameter with the largest probability value is adjusted to control the output of the energy storage power supply.

[0046] Furthermore, the probability value of the contribution to the frequency regulation of the new energy power system satisfies the following relationship:

[0047]

[0048] Where P nm is the probability value of the contribution of the nth control parameter to the frequency regulation of the renewable energy power system at the mth time node, Q nm is the dimensionless value of the nth control parameter at the mth time node, i is the total time node, Q nk is the dimensionless value of the nth control parameter at the kth time node, C nm is the original value of the nth control parameter at the mth time node, is the mean value of the control parameter at the mth time node, σC m is the standard value of the control parameter at the mth time node.

[0049] Furthermore, the frequency stability response model satisfies the following relationship:

[0050]

[0051] In the formula, ΔP VSG is the output power deviation of the frequency stability response model, T B is the time constant, J1 is the virtual moment of inertia, D1 is the virtual damping coefficient, s is the complex variable in Laplace transform, R is the governor gain, a and T are the characteristic coefficient and equivalent inertia time constant of the turbine respectively, M is the moment of inertia, D is the damping coefficient, ΔP load is the load active power.

[0052] In a second aspect, the present invention further provides an adaptive energy storage coordination control device based on a virtual synchronous machine, which adopts the adaptive energy storage coordination control method based on a virtual synchronous machine, and the device comprises:

[0053] A deviation determination module, which is used to obtain the real-time frequency of the new energy power system and determine the frequency deviation;

[0054] An optimal control module, which is used to adjust the output of the energy storage power supply based on the frequency deviation and in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply;

[0055] The regulating control module is used to adjust the optimal control parameters and control the output of the energy storage power supply based on the frequency deviation after adjusting the output of the energy storage power supply and in combination with the proportional distribution coefficient of the optimal control parameters; repeatedly adjust the optimal control parameters and control the output process of the energy storage power supply until the frequency deviation reaches a predetermined steady-state value.

[0056] Furthermore, the optimal control module includes:

[0057] The frequency deviation is compared with a predetermined steady-state value, and when the frequency deviation exceeds the predetermined steady-state value, the energy storage power supply is put into operation;

[0058] Based on the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, the output power of the energy storage power supply is controlled.

[0059] Further, the device includes an optimal parameter determination module, which includes:

[0060] Obtain historical operation data of the renewable energy power system and historical control parameters of the frequency stability response model;

[0061] Based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, and the benefit function, open-loop transfer function and coordinated control force function of the new energy power system are constructed;

[0062] Based on the benefit function and the open-loop transfer function, and in combination with the historical operation data of the new energy power system and the historical control parameters of the frequency stability response model, the benefit coefficient and stability coefficient corresponding to different control parameter combinations are determined respectively;

[0063] Based on the coefficient of variation, benefit coefficient and stability coefficient of each control parameter and combined with the coordinated control force function, the coordinated control force coefficient corresponding to different control parameter combinations is determined;

[0064] Based on the coordinated control force coefficient, the control parameters that achieve the optimal control effect are determined.

[0065] Furthermore, the optimal parameter determination module includes:

[0066] Based on the historical control parameters of the frequency stability response model, determine the standard deviation and average value of each control parameter;

[0067] Based on the standard deviation and the mean of each control parameter, the coefficient of variation of each control parameter was determined.

[0068] Furthermore, the optimal parameter determination module includes:

[0069] Determine the frequency response of the open-loop transfer function based on the historical operating data of the renewable energy power system and the historical control parameters of the frequency stability response model;

[0070] Based on the frequency response of the open-loop transfer function, the gain margin of each set of control parameters is given;

[0071] A stability coefficient for each set of control parameters is determined based on the gain margin.

[0072] Furthermore, the regulation control module includes:

[0073] Obtain frequency deviation after adjusting the output of energy storage power supply in real time;

[0074] When the frequency deviation after adjusting the output of the energy storage power source reaches a maximum value, determine the optimal control parameter with the maximum probability value of contributing to the frequency regulation of the new energy power system;

[0075] The optimal control parameter with the largest probability value is adjusted to control the output of the energy storage power supply.

[0076] The present invention provides an adaptive energy storage coordination control method and device based on a virtual synchronous machine, which has at least the following beneficial effects:

[0077] (1) By determining the optimal control parameters, the response speed of frequency coordination control can be improved, and by adjusting the optimal control parameters, it can have higher coordination performance and frequency regulation effect.

[0078] (2) The quantification of coordinated control force can accurately evaluate the contribution of various control parameters to the frequency regulation of the renewable energy power system, thereby achieving more accurate and efficient frequency control. The present invention can optimize the frequency stability response model and help improve the overall performance and adaptability of the renewable energy power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A flowchart of an adaptive energy storage coordination control method based on a virtual synchronous machine provided by the present invention;

[0080] Figure 2 A flowchart for determining optimal control parameters provided by an embodiment of the present invention;

[0081] Figure 3 A flow chart for determining a stability coefficient provided for an embodiment of the present invention;

[0082] Figure 4 A schematic diagram of a control framework provided for an embodiment of the present invention;

[0083] Figure 5 A schematic diagram of a frequency stability response model provided by an embodiment of the present invention;

[0084] Figure 6 A schematic diagram of an adaptive energy storage coordination control device based on a virtual synchronous machine provided by the present invention. DETAILED DESCRIPTION

[0085] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. 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.

[0086] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0087] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0088] like Figure 1 As shown, the present invention provides an adaptive energy storage coordination control method based on a virtual synchronous machine, which may include:

[0089] Obtain the real-time frequency of the renewable energy power system and determine the frequency deviation;

[0090] Based on the frequency deviation, the output of the energy storage power supply is adjusted in combination with the optimal control parameters of the frequency stability response model constructed based on the virtual synchronous machine corresponding to the energy storage power supply;

[0091] Based on the frequency deviation after adjusting the output of the energy storage power supply and combining the proportional distribution coefficient of the optimal control parameter, the optimal control parameter is adjusted and the output of the energy storage power supply is controlled;

[0092] The optimal control parameters are repeatedly adjusted and the output process of the energy storage power supply is controlled until the frequency deviation reaches a predetermined steady-state value.

[0093] The key to the adaptive energy storage coordinated control method in actual application scenarios is to continuously identify and adjust the control parameters to optimize dynamic performance. This process is based on a feedback mechanism, and dynamically adjusts the controller parameters by monitoring the deviation between the output and the expected target in real time. First, monitor the grid frequency in real time to determine whether energy storage power is needed. When it is detected that the frequency deviation exceeds the threshold, evaluate the proportional allocation coefficient of the control method and adjust the energy storage output. If the frequency deviation reaches the maximum value, adjust the control parameters and continue to monitor the frequency change until the system frequency deviation returns to the steady-state value, ending a frequency adjustment.

[0094] The present invention can determine the frequency deviation by the absolute value of the difference between the real-time frequency and the standard frequency of the new energy power system. The control parameters include virtual moment of inertia and virtual damping coefficient, and may also include virtual impedance, droop characteristics, moment of inertia and damping coefficient.

[0095] After determining the frequency deviation, the present invention adjusts the output of the energy storage power supply based on the frequency deviation and in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, which may include:

[0096] The frequency deviation is compared with a predetermined steady-state value, and when the frequency deviation exceeds the predetermined steady-state value, the energy storage power supply is put into operation;

[0097] Based on the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, the output power of the energy storage power supply is controlled.

[0098] like Figure 2 As shown, the optimal control parameters of the energy storage power source corresponding to the frequency stability response model can be determined by:

[0099] Obtain historical operation data of the renewable energy power system and historical control parameters of the frequency stability response model;

[0100] Based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, and the benefit function, open-loop transfer function and coordinated control force function of the new energy power system are constructed; among them, the benefit function satisfies the following relationship:

[0101] Δf=SP sνg +CP res +AΔP grid

[0102] Where Δf is the power system benefit function, S is the correlation between the frequency stability response model and the frequency response of the new energy power system, and represents the response characteristics of the virtual synchronous machine in the power system; P svg The frequency stability response model controls the active power output of the energy storage power supply and simulates the rotational inertia characteristics of the traditional synchronous generator; C represents the undetermined parameter, which is the frequency response coefficient of other renewable energy sources; P res is the active power output of other renewable energy sources; A is the control effectiveness coefficient, which reflects the role of coordinated control strategy in stabilizing the frequency of new energy power system; ΔP grid It is the power variation of the new energy power system, which refers to the power deviation caused by load changes;

[0103] The VSG technology of the present invention improves the system stability of the new energy power system through precise frequency regulation and adaptive energy storage. It integrates advanced coordinated control strategies to improve response speed and reliability. The stability calculation adopts open-loop transfer function calculation to satisfy the following relationship:

[0104]

[0105] Where H(s) is the open-loop transfer function, which represents the relationship between input and output; K d P is the frequency modulation coefficient, which reflects the frequency modulation capability of the system and affects the system's ability to adjust frequency changes; re is the proportion of renewable energy installed capacity, reflecting the proportion of renewable energy power generation in total power generation, which directly affects the overall stability of the system; T d is the damping time constant, which reflects the response speed of the system when the frequency fluctuates; T pis the adjustment time constant, reflecting the frequency adjustment capability of the system when the load changes; s is the complex variable in Laplace transform;

[0106] Coordinate the control force function to satisfy the following relationship:

[0107]

[0108] In the formula, K is the coordinated control function, c(n) is the benefit coefficient of the new energy power system, which is determined by the calculation result of the power system benefit function, p(e) is the stability coefficient of the new energy power system, which is determined by the gain margin result calculated by the open-loop transfer function, and q(w) is the coefficient of variation of the control parameters, which is obtained by comprehensive calculation of the coefficient of variation of each group of control parameters, and can be calculated by arithmetic mean, geometric mean and weighted mean;

[0109] Based on the benefit function and the open-loop transfer function, and in combination with the historical operation data of the new energy power system and the historical control parameters of the frequency stability response model, the benefit coefficient and stability coefficient corresponding to different control parameter combinations are determined respectively;

[0110] Based on the coefficient of variation, benefit coefficient and stability coefficient of each control parameter and combined with the coordinated control force function, the coordinated control force coefficient corresponding to different control parameter combinations is determined;

[0111] Based on the coordinated control force coefficient, the control parameters that achieve the optimal control effect are determined.

[0112] By quantifying the coordinated control force, the contribution of various control strategies (different groups of control parameters) to system frequency regulation can be accurately evaluated, thereby achieving more accurate and efficient frequency control. The adaptive energy storage coordinated control method of the present invention can optimize the frequency stability response model and help improve the overall performance and adaptability of the new energy power system.

[0113] Among them, based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, including:

[0114] Based on the historical control parameters of the frequency stability response model, determine the standard deviation and average value of each control parameter;

[0115] Based on the standard deviation and mean value of each control parameter, the coefficient of variation of each control parameter is determined. Specifically, the importance of each control parameter is evaluated by using the weighted coefficient of variation method to meet the following relationship:

[0116]

[0117] In the formula, CV iis the coefficient of variation of the i-th control parameter, which is used to measure the relative dispersion of the parameter. The larger the coefficient of variation, the more unstable the parameter change, and the higher its importance to the control of the new energy power system; σ i is the standard deviation of the ith control parameter, which mainly reflects the discrete degree of the parameter value; X i is the average value of the i-th control parameter, reflecting the central tendency of the parameter.

[0118] like Figure 3 As shown, the stability coefficients corresponding to different control parameter combinations are determined, including:

[0119] Determine the frequency response of the open-loop transfer function based on the historical operating data of the renewable energy power system and the historical control parameters of the frequency stability response model;

[0120] Based on the frequency response of the open-loop transfer function, the gain margin of each set of control parameters is given to satisfy the following relationship:

[0121]

[0122] Where GM is the gain margin, G(jω)H(jω) is the frequency response of the open-loop transfer function, and ω is the angular frequency;

[0123] The stability coefficient of each group of control parameters is determined based on the gain margin, that is, the gain margin of each group of control parameters is determined as the corresponding stability coefficient.

[0124] The present invention can achieve rapid response to the new energy power system through the optimal control parameters. After adjusting the output of the energy storage power supply through the optimal control parameters to achieve frequency adjustment of the new energy power system, since the optimal control parameters are obtained through historical control data, there is a certain error in the current state. In order to reduce the error, the optimal control parameters can be adjusted based on the frequency deviation after adjusting the output of the energy storage power supply, combined with the proportional distribution coefficient of the optimal control parameters, and the output of the energy storage power supply can be controlled, including:

[0125] Obtain frequency deviation after adjusting the output of energy storage power supply in real time;

[0126] When the frequency deviation after adjusting the output of the energy storage power source reaches a maximum value, determine the optimal control parameter with the maximum probability value of contributing to the frequency regulation of the new energy power system;

[0127] The optimal control parameter with the largest probability value is adjusted to control the output of the energy storage power supply.

[0128] Among them, the probability value of contribution to the frequency regulation of the new energy power system satisfies the following relationship:

[0129]

[0130] Where P nm is the probability value of the contribution of the nth control parameter to the frequency regulation of the renewable energy power system at the mth time node, Q nm is the dimensionless value of the nth control parameter at the mth time node, k is the index of the summation operation, ranging from 1 to i, i is the total time node, Q nk is the dimensionless value of the nth control parameter at the kth time node, C nm is the original value of the nth control parameter at the mth time node, is the mean value of the control parameter at the mth time node, σC m is the standard value of the control parameter at the mth time node.

[0131] Among them, the standard value satisfies the following relationship:

[0132]

[0133] Where N is the number of control parameters.

[0134] like Figure 4 As shown, the control framework of the adaptive energy storage coordinated control method of the present invention is: the energy is connected to the system through the grid interface, and is monitored in real time by the grid measurement and battery system. Inner loop current control and virtual impedance ensure current stability, and the excitation regulator adjusts the voltage. The Robb equation describes the dynamic response of the new energy power system, and the virtual speed regulator simulates the inertia of the synchronous motor. The charge and discharge control optimizes the battery performance, coordinates the model interface, and the controller and other control components to achieve efficient management of the energy storage power supply. VSG technology converts the collected power system data into a high-precision grid model, and fine-tunes the model through a coordinated control process. Among them, the virtual regulator simulates the speed controller from the external characteristics to ensure that the output frequency has a droop characteristic. The droop proportional coefficient satisfies the following relationship:

[0135] H m0 =H ref +l(I ref -I g )

[0136] Where l is the droop ratio coefficient, which determines the degree of influence of frequency deviation on output power. The numerical frequency mainly refers to the rated frequency of the new energy power system, which is usually a fixed value (50hz or 60hz). g It refers to the actual frequency measured in real time during the operation of the new energy power system. m0 is the output power of the virtual regulator, which refers to the actual output power of the virtual regulator after adjustment according to the frequency deviation. refIt is the reference active power value, which refers to the expected output power of the renewable energy power system without frequency deviation. The power difference controls the torque output frequency of the virtual regulator.

[0137] Damping power reduces power oscillations, satisfying the following relationship:

[0138]

[0139] In the formula, Z represents the damping coefficient, which determines the attenuation rate of the frequency oscillation. v represents the angular frequency of the VSG output voltage, reflecting the rate at which the voltage changes over time; H represents the actual power of the new energy power system; m represents the damping power, which is usually the result of input mechanical power and electromagnetic conversion; J is the virtual moment of inertia, reflecting the system's resistance to frequency changes; H e Represents electromagnetic power.

[0140] The present invention provides a new dimension for the adaptive coordinated control of power systems, helping power grid regulation to achieve highly simulated control effects in a virtual environment that simulates power grids. The application of energy storage adaptive coordinated control strategies based on VSG technology in actual power systems needs to consider the dynamic characteristics and complexity of the power grid to ensure the accuracy of real-time monitoring and control.

[0141] The present invention uses VSG technology to build a high-precision frequency response model. By integrating power grid operation data, an intuitive control interface is provided for dispatchers. The frequency stability response model uses advanced algorithms to dynamically simulate frequency regulation characteristics such as power flow and frequency change, thereby enhancing control over system stability.

[0142] The frequency stability response model uses SVG technology to continuously monitor grid operation data, such as grid frequency and power flow, and provides real-time feedback on these data. Based on these real-time data, the frequency stability response model dynamically adjusts control parameters, dynamically simulates frequency regulation characteristics, and automatically adjusts system parameters. The frequency stability response model adopts a centralized control perspective to provide a real-time monitoring and decision-making platform for grid operators. While meeting the response requirements of different grid conditions, it ensures the effectiveness and economy of regulation.

[0143] like Figure 5 As shown, the frequency stability response model satisfies the following relationship:

[0144]

[0145] In the formula, ΔP VSG is the output power deviation of the frequency stability response model, T Bis the time constant, J1 is the virtual moment of inertia, D1 is the virtual damping coefficient, s is the complex variable in Laplace transform, R is the governor gain, a and T are the characteristic coefficient and equivalent inertia time constant of the turbine respectively, M is the moment of inertia, D is the damping coefficient, ΔP load is the load active power.

[0146] The present invention achieves rapid and stable response of the new energy power system under large-scale fluctuations by deeply analyzing the output characteristics and dynamic behavior of new energy, and improves frequency stability based on enhancing the adaptive regulation capability of the system. The expected contribution of the present invention is that the implementation of this strategy is expected to enhance the adaptability and stable operation capability of the power system to the grid connection of new energy, and also provide theoretical support and technical reference for the frequency stability problem of similar systems.

[0147] like Figure 6 As shown, the present invention also provides an adaptive energy storage coordination control device based on a virtual synchronous machine, which adopts the above-mentioned adaptive energy storage coordination control method based on a virtual synchronous machine, and the device includes:

[0148] A deviation determination module, which is used to obtain the real-time frequency of the new energy power system and determine the frequency deviation;

[0149] An optimal control module, which is used to adjust the output of the energy storage power supply based on the frequency deviation and in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply;

[0150] The regulating control module is used to adjust the optimal control parameters and control the output of the energy storage power supply based on the frequency deviation after adjusting the output of the energy storage power supply and in combination with the proportional distribution coefficient of the optimal control parameters; repeatedly adjust the optimal control parameters and control the output process of the energy storage power supply until the frequency deviation reaches a predetermined steady-state value.

[0151] Furthermore, the optimal control module includes:

[0152] The frequency deviation is compared with a predetermined steady-state value, and when the frequency deviation exceeds the predetermined steady-state value, the energy storage power supply is put into operation;

[0153] Based on the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, the output power of the energy storage power supply is controlled.

[0154] Further, the device includes an optimal parameter determination module, which includes:

[0155] Obtain historical operation data of the renewable energy power system and historical control parameters of the frequency stability response model;

[0156] Based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, and the benefit function, open-loop transfer function and coordinated control force function of the new energy power system are constructed;

[0157] Based on the benefit function and the open-loop transfer function, and in combination with the historical operation data of the new energy power system and the historical control parameters of the frequency stability response model, the benefit coefficient and stability coefficient corresponding to different control parameter combinations are determined respectively;

[0158] Based on the coefficient of variation, benefit coefficient and stability coefficient of each control parameter and combined with the coordinated control force function, the coordinated control force coefficient corresponding to different control parameter combinations is determined;

[0159] Based on the coordinated control force coefficient, the control parameters that achieve the optimal control effect are determined.

[0160] Furthermore, the optimal parameter determination module includes:

[0161] Based on the historical control parameters of the frequency stability response model, determine the standard deviation and average value of each control parameter;

[0162] Based on the standard deviation and the mean of each control parameter, the coefficient of variation of each control parameter was determined.

[0163] Furthermore, the optimal parameter determination module includes:

[0164] Determine the frequency response of the open-loop transfer function based on the historical operating data of the renewable energy power system and the historical control parameters of the frequency stability response model;

[0165] Based on the frequency response of the open-loop transfer function, the gain margin of each set of control parameters is given;

[0166] A stability coefficient for each set of control parameters is determined based on the gain margin.

[0167] Furthermore, the regulation control module includes:

[0168] Obtain frequency deviation after adjusting the output of energy storage power supply in real time;

[0169] When the frequency deviation after adjusting the output of the energy storage power source reaches a maximum value, determine the optimal control parameter with the maximum probability value of contributing to the frequency regulation of the new energy power system;

[0170] The optimal control parameter with the largest probability value is adjusted to control the output of the energy storage power supply.

[0171] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An adaptive energy storage coordination control method based on a virtual synchronous machine, characterized in that: include: Obtain the real-time frequency of the renewable energy power system and determine the frequency deviation; Based on the frequency deviation, the output of the energy storage power supply is adjusted in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply; Based on the frequency deviation after adjusting the output of the energy storage power supply and combining the proportional distribution coefficient of the optimal control parameter, the optimal control parameter is adjusted and the output of the energy storage power supply is controlled; The optimal control parameters are repeatedly adjusted and the output process of the energy storage power supply is controlled until the frequency deviation reaches a predetermined steady-state value.

2. The adaptive energy storage coordinated control method according to claim 1, characterized in that: Based on the frequency deviation, the output of the energy storage power supply is adjusted in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, including: The frequency deviation is compared with a predetermined steady-state value, and when the frequency deviation exceeds the predetermined steady-state value, the energy storage power supply is put into operation; Based on the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply, the output power of the energy storage power supply is controlled.

3. The adaptive energy storage coordinated control method according to claim 1 or 2, characterized in that: The optimal control parameters of the energy storage power source corresponding to the frequency stability response model are determined, including: Obtain historical operation data of the renewable energy power system and historical control parameters of the frequency stability response model; Based on the historical control parameters of the frequency stability response model, the coefficient of variation of each control parameter is determined, and the benefit function, open-loop transfer function and coordinated control force function of the new energy power system are constructed; Based on the benefit function and the open-loop transfer function, and in combination with the historical operation data of the new energy power system and the historical control parameters of the frequency stability response model, the benefit coefficient and stability coefficient corresponding to different control parameter combinations are determined respectively; Based on the coefficient of variation, benefit coefficient and stability coefficient of each control parameter and combined with the coordinated control force function, the coordinated control force coefficient corresponding to different control parameter combinations is determined; Based on the coordinated control force coefficient, the control parameters that achieve the optimal control effect are determined.

4. The adaptive energy storage coordinated control method according to claim 3, characterized in that: The coefficient of variation of each control parameter satisfies the following relationship: In the formula, CV i is the coefficient of variation of the ith control parameter; σ i is the standard deviation of the ith control parameter; X i is the average value of the i-th control parameter; The benefit function satisfies the following relationship: Δf=SP sνg +CP res +AΔP grid Where Δf is the power system benefit function, S is the correlation between the frequency stability response model and the frequency response of the new energy power system; P svg is the active power output of the energy storage power supply controlled by the frequency stability response model; C is the frequency response coefficient of other renewable energy sources; P res is the active power output of other renewable energy sources; A is the control effectiveness coefficient; ΔP grid is the power change of the new energy power system; The open-loop transfer function satisfies the following relationship: Where H(s) is the open-loop transfer function; K d is the frequency modulation coefficient; P re is the proportion of renewable energy power generation in total power generation; T d is the damping time constant; T p is the adjustment time constant; s is the complex variable in Laplace transform.

5. The adaptive energy storage coordinated control method according to claim 3, characterized in that: Coordinate the control force function to satisfy the following relationship: Where K is the coordination control function, c(n) is the benefit coefficient of the new energy power system, p(e) is the stability coefficient of the new energy power system, and q(w) is the coefficient of variation of the control parameters.

6. The adaptive energy storage coordinated control method according to claim 3, characterized in that: Determine the stability coefficients corresponding to different control parameter combinations, including: Determine the frequency response of the open-loop transfer function based on the historical operating data of the renewable energy power system and the historical control parameters of the frequency stability response model; Based on the frequency response of the open-loop transfer function, the gain margin of each set of control parameters is given; Determining a stability coefficient for each set of control parameters based on the gain margin; The calculation formula of gain margin is: Where GM is the gain margin, G(jω)H(jω) is the frequency response of the open-loop transfer function, and ω is the angular frequency.

7. The adaptive energy storage coordinated control method according to claim 1, characterized in that: Based on the frequency deviation after adjusting the output of the energy storage power supply, combined with the proportional distribution coefficient of the optimal control parameter, the optimal control parameter is adjusted and the output of the energy storage power supply is controlled, including: Obtain frequency deviation after adjusting the output of energy storage power supply in real time; When the frequency deviation after adjusting the output of the energy storage power source reaches a maximum value, determine the optimal control parameter with the maximum probability value of contributing to the frequency regulation of the new energy power system; The optimal control parameter with the largest probability value is adjusted to control the output of the energy storage power supply.

8. The adaptive energy storage coordinated control method according to claim 7, characterized in that: The probability value of the contribution to the frequency regulation of the new energy power system satisfies the following relationship: Where P nm is the probability value of the contribution of the nth control parameter to the frequency regulation of the renewable energy power system at the mth time node, Q nm is the dimensionless value of the nth control parameter at the mth time node, i is the total time node, Q nk is the dimensionless value of the nth control parameter at the kth time node, C nm is the original value of the nth control parameter at the mth time node, C m is the mean value of the control parameter at the mth time node, σC m is the standard value of the control parameter at the mth time node.

9. The adaptive energy storage coordinated control method according to claim 1, characterized in that: The frequency stability response model satisfies the following relationship: In the formula, ΔP VSG is the output power deviation of the frequency stability response model, T B is the time constant, J1 is the virtual moment of inertia, D1 is the virtual damping coefficient, s is the complex variable in Laplace transform, R is the governor gain, a and T are the characteristic coefficient and equivalent inertia time constant of the turbine respectively, M is the moment of inertia, D is the damping coefficient, ΔP load is the load active power.

10. An adaptive energy storage coordination control device based on a virtual synchronous machine, characterized in that: The adaptive energy storage coordination control method based on a virtual synchronous machine as claimed in any one of claims 1 to 9 is adopted, and the device comprises: A deviation determination module, which is used to obtain the real-time frequency of the new energy power system and determine the frequency deviation; An optimal control module, which is used to adjust the output of the energy storage power supply based on the frequency deviation and in combination with the optimal control parameters of the frequency stability response model corresponding to the energy storage power supply; The regulating control module is used to adjust the optimal control parameters and control the output of the energy storage power supply based on the frequency deviation after adjusting the output of the energy storage power supply and in combination with the proportional distribution coefficient of the optimal control parameters; repeatedly adjust the optimal control parameters and control the output process of the energy storage power supply until the frequency deviation reaches a predetermined steady-state value.

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