Transient interaction characteristic analysis method for optical storage direct-flexible system in high-temperature and high-humidity environment

Abstract

The invention discloses a transient interaction characteristic analysis method for an optical storage direct-flexible system in a high-temperature and high-humidity environment, and the method comprises the steps: firstly building a differential algebraic model of a dynamic behavior, and initializing a state and parameters; then, adopting an SAS method to construct an approximate solution, and dynamically adjusting model parameters according to real-time temperature and humidity; establishing a linear equation of a coupling relationship, recursively solving a high-order coefficient, and calculating residual error evaluation precision; solving the high-order nonlinear model by utilizing a parallelization calculation technology, constructing a local RLC topology to carry out transient simulation, recording a time-varying result of a system state, and analyzing a coupling effect of each component; and finally, adjusting the key variable by adopting a self-adaptive control algorithm. According to the invention, based on the SAS calculation method, for the dynamic response of the optical storage direct-flexible system in the high-temperature and high-humidity environment, efficient transient analysis is realized, and the operation reliability and the regulation and control capability of the system are remarkably improved. The method is applied to an on-line monitoring and control platform of a power system, and real-time optimization is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of dynamic analysis of power systems, and in particular to a method for analyzing transient interaction characteristics of a photovoltaic storage direct-flexible system under a high temperature and high humidity environment. Background Art

[0002] Shanghai and East China have the weather characteristics of "rain and heat at the same time", and hot and humid weather often occurs in summer. This extreme weather not only causes large-scale fluctuations in power load levels, but also affects the operating efficiency of various components in the power system, such as sources, networks, loads, and storage, reducing the capacity of peak-shaving resources and increasing the difficulty of peak-shaving. On the source side, high temperature and high humidity weather affects the efficiency of power generation equipment, such as the cooling efficiency of thermal power plants; on the grid side, high humidity increases the difficulty of equipment heat dissipation and the risk of short circuits in transmission lines; on the load side, high temperature weather significantly increases the utilization rate and average power of air-conditioning and refrigeration equipment, resulting in a sharp increase in electricity demand; on the energy storage side, the frequency and depth of use of lithium-ion batteries in high temperature environments are limited, which may accelerate aging and reduce capacity, and even cause safety accidents such as thermal runaway.

[0003] The PV-storage-direct-flexible technology is a solution that utilizes various resources through photovoltaics, energy storage, direct current transmission and flexible operation technologies. Its advantages are: 1) There is abundant sunshine in the summer and the efficiency of photovoltaic power generation is high; 2) The energy storage system plays a role in peak load shifting and valley filling, smoothing the electricity demand curve; 3) The direct current transmission system has low losses and high efficiency and can effectively transmit electricity over long distances; 4) Flexible interaction technology can improve the reliability and responsiveness of the power grid under extreme weather conditions.

[0004] However, the current analysis methods for transient interaction characteristics of PV-storage-DC-flexible systems mainly include: time domain simulation analysis, small signal frequency domain analysis, energy function analysis and state space analysis. These methods can conduct a relatively comprehensive analysis of transient interaction characteristics, but there are still some shortcomings. Specifically, 1) The existing time domain simulation algorithm usually adopts serial calculation method. Due to the high-order mathematical model of PV-storage-DC-flexible system, the time cost of serial calculation limits the scale and accuracy of the simulation model, and it is difficult to meet the precise analysis of high-order models and complex systems; 2) The energy function method often gives a conservative stability judgment by establishing the energy function of the equivalent model, which leads to the stability domain of the system operation being too small, thus affecting the economy of the system; 3) The small signal frequency domain analysis method is based on the linearization of the system, assuming that the response of the system under small disturbances is linear, but there are a large number of nonlinear elements in the PV-storage-DC-flexible system, and the linearization model cannot effectively reflect the nonlinear characteristics of power electronic equipment; 4) The PV-storage-DC-flexible system contains a large number of devices and components, and each device may require multiple state variables to describe. The state space analysis method may cause the entire state space system to have "dimensionality disaster" and other factors that are not conducive to transient interaction analysis.

[0005] The defects of the above methods will make it difficult to accurately predict the operating performance and stability of the system under extreme conditions such as high temperature and high humidity, thereby affecting the design, optimization and safe operation of the system.

[0006] With the rapid development of new energy power generation technology, the application of photovoltaic and energy storage systems in modern power systems has gradually expanded. However, these new energy power generation equipment inevitably face severe challenges of extreme environmental conditions during operation, especially under climatic conditions such as high temperature and high humidity, which puts higher requirements on the operational stability and reliability of the system. Under such extreme conditions, the dynamic interaction characteristics of each component in the photovoltaic storage direct-flexible system are more complex, and traditional analysis methods are difficult to deal with effectively.

[0007] Traditional power system transient analysis methods, such as time domain simulation, small signal frequency domain analysis, energy function analysis, and state space analysis, play an important role in system stability and dynamic behavior modeling, but they are often insufficient when dealing with high-order complex systems. These methods usually assume that the system model is linear and the parameters are fixed, which makes it difficult to ensure the accuracy and efficiency of the analysis in actual nonlinear and rapidly changing high temperature and high humidity environments, especially in terms of real-time performance.

[0008] Some existing improvement schemes, such as convolutional neural network (CNN) for transient analysis of renewable energy multi-stations and frequency domain-based simulation methods, have improved the accuracy of analysis to a certain extent, but these methods rely on large-scale data sets and complex training processes, and are relatively poorly adaptable to environmental changes. When faced with extreme environmental changes, such as significant fluctuations in temperature and humidity, traditional linear models and data-driven methods are difficult to fully capture the complex nonlinear interaction characteristics between devices within the system. In addition, the dynamic coupling relationship between components in the power system becomes more complex under extreme environments, which further exacerbates the difficulty of analysis. Summary of the invention

[0009] The present invention provides a method for analyzing transient interaction characteristics of a photovoltaic storage direct-flexible system under a high temperature and high humidity environment, so as to solve the existing technical problems.

[0010] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0011] A method for analyzing transient interaction characteristics of a solar-storage direct-flexible system under a high temperature and high humidity environment comprises the following steps:

[0012] S1. Establish a system model, abstract the dynamic behavior of the optical storage direct-flexible system into a differential algebraic model; then, initialize the state and parameters, including initial conditions and simulation time, wherein the initial conditions include determining the initial state vector;

[0013] S2. Use SAS calculation method to construct approximate solution, use power series expansion to represent dynamic state variables and algebraic state variables; then, dynamically adjust model parameters according to real-time temperature and humidity changes in high temperature and high humidity environment;

[0014] S3. Establish a linear equation that describes the coupling relationship between coefficients and convert the equation into a coefficient polynomial; then, starting from the zero-order coefficient, recursively solve the higher-order coefficients step by step, and then calculate the residual after substitution into the equation to evaluate the accuracy of the approximate solution; then use parallel computing technology to decompose and solve the high-order nonlinear model of the system;

[0015] S4. Construct a local RLC topology, set the dynamic component parameters according to the electrical topology in the actual application, run the transient simulation, record the results of the system state variables changing over time, and perform multiple iterations to accurately describe the transient interaction behavior within the system; then compare the simulation results with the ideal waveform to analyze the coupling effects between the components;

[0016] S5. Use adaptive control algorithms to adjust key variables during system operation.

[0017] As a further improvement of the above technical solution:

[0018] In S1, the differential algebraic model is:

[0019]

[0020] 0=g(x(t),y(t),p(t))

[0021] Where t is time, x is the dynamic state variable, y is the algebraic state variable, p is the system parameter, and f and g are equations that describe the system behavior.

[0022] In S2, the initial state vector is: x(0)=x0 and y(0)=y0.

[0023] In S3, the expressions of the approximate solution and model parameters are:

[0024]

[0025] Where x^(t) is the dynamic state variable, y^(t) is the algebraic state variable, and p^(t) is the time-dependent approximate solution of the system parameters, which is expressed as a combination of various order coefficients x[k], y[k] and p[k] through power series expansion, where t is the time variable.

[0026] In S5, by substituting the approximate solution into the time-domain differential algebraic model of the power system, a linear equation describing the coupling relationship between the coefficients is established.

[0027] A transient interaction characteristics analysis method for a photovoltaic-storage direct-flexible system under high temperature and high humidity environment is applied to the online monitoring and control platform of the power system.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. Traditional time-domain simulation analysis methods usually use serial calculation methods. Faced with high-order mathematical models of photovoltaic storage direct-flexible systems, the calculation time is long and it is difficult to meet the requirements of real-time and high precision. The present invention uses the SAS calculation method to decompose complex nonlinear equations into easy-to-solve parts, avoid global numerical integration, and combine parallel computing technology to significantly improve the calculation efficiency. This makes it suitable for accurate analysis of large-scale, high-order models and meets the needs of real-time monitoring and online analysis.

[0030] 2. The traditional small signal frequency domain analysis method is based on linearization processing and is mainly used to study the stability of the system under small disturbances. Although it can effectively handle linear problems, for systems with strong nonlinearity and large disturbances, the small signal analysis method cannot accurately reflect the true dynamic behavior of the system. The present invention uses the SAS calculation method to decompose complex nonlinear differential equations and gradually approach the exact solution of the system. It can directly handle nonlinear systems without linearization and is suitable for analyzing obvious nonlinear behaviors such as photovoltaics, energy storage and power electronic equipment.

[0031] 3. The traditional energy function method is difficult to construct a suitable energy function for highly nonlinear power systems. At the same time, because it is based on a fixed parameter model, it is also difficult to handle the situation where parameters in system operation change dynamically with external conditions under extreme weather conditions. The SAS calculation method adopted in the present invention can handle system uncertainty factors such as environmental impacts and equipment status changes by refining the time interval when facing system parameter changes under high temperature and high humidity conditions, and is more flexible and adaptable.

[0032] 4. The model dimension of the traditional state-space method will grow rapidly as the complexity and scale of the system increase, resulting in an excessively large dimension of the state vector, which increases the difficulty of analysis and calculation. When dealing with large and complex systems, the computational and storage costs of the state-space method will increase significantly. The SAS calculation method used in the present invention can solve complex dynamic problems at a lower computational cost by gradually decomposing the problem when dealing with complex systems. It is more adaptable to the scale and complexity of the system, especially when dealing with multiple dynamic subsystems and complex interactions, the decomposition process of the semi-analytical method can avoid a large amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 This is a diagram showing the ideal transient operation results of the local RLC topology of the PV-storage direct-flexible system in an embodiment of the present invention.

[0035] Figure 2 This is a graph showing the results of testing the local RLC topology of the PV-storage direct-flexible system using a semi-analytical method in an embodiment of the present invention.

[0036] Figure 3 This is a diagram showing the results of testing the local RLC topology / trapezoidal algorithm of the PV-storage direct-flexible system in an embodiment of the present invention.

[0037] Figure 4 This is a diagram showing the results of testing the local RLC topology / improved Euler method of the PV-storage direct-flexible system in an embodiment of the present invention.

[0038] Figure 5 This is a graph showing the results of testing the local RLC topology / 4th-order Runge-Kutta method of the PV-storage direct-flexible system in an embodiment of the present invention.

[0039] Figure 6 This is the algorithm flow chart. DETAILED DESCRIPTION

[0040] In order to facilitate the understanding of the present invention, the present invention will be described more comprehensively and meticulously below in conjunction with the accompanying drawings and preferred embodiments of the present invention, but the protection scope of the present invention is not limited to the following specific embodiments.

[0041] Unless otherwise defined, all professional terms used below have the same meanings as those generally understood by those skilled in the art. The professional terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the scope of protection of the present invention.

[0042] Unless otherwise specified, various raw materials, reagents, instruments and equipment used in the present invention can be purchased from the market or prepared by existing methods.

[0043] The present invention proposes an efficient analysis scheme based on the SAS (semi-analytical solution) calculation method. The SAS calculation method can significantly improve the modeling accuracy and calculation efficiency of the system by combining analytical solution with numerical solution while retaining the nonlinear characteristics of the system. Compared with the traditional time-domain simulation based on numerical integration, the SAS calculation method avoids the accumulation of calculation errors when dealing with complex nonlinear systems, and is particularly suitable for the dynamic response analysis of various devices in the photovoltaic storage direct-flexible system under high temperature and high humidity environment.

[0044] In addition, the present invention introduces parallel processing technology to further improve the efficiency and accuracy of the analysis of the transient interaction characteristics of the system. By combining the state-space analysis method, the high-order nonlinear model of the photovoltaic storage direct-flexible system can be converted into a form that is more suitable for calculation, and parallel computing can be used to accelerate the solution process to meet the needs of online monitoring and real-time analysis of the system. This method not only improves the operational stability of the system, but also provides strong support for power dispatching and operation optimization in complex and extreme environments.

[0045] In summary, the present invention effectively overcomes the shortcomings of traditional transient analysis methods by combining SAS calculation methods, state space analysis and parallel computing processing. It can accurately analyze the dynamic interaction characteristics within the solar-storage direct-flexible system under extreme climatic conditions such as high temperature and high humidity, and significantly improve the system's operating reliability and regulation capabilities.

[0046] Embodiment: The state equation of the solar-storage direct-flexible system is abstracted into the following mathematical model:

[0047]

[0048] 0=g(x(t),y(t),p(t))#(2)

[0049] Where y is time, x is the dynamic state variable, y is the algebraic state variable, p is the system parameter, and f and g are equations describing the system behavior. In practical power system applications, both f and g are holomorphic functions, which means that they are locally infinitely differentiable in complex space and are equal to their Taylor expansions.

[0050] Let x0 and y0 represent the initial values ​​of some x and y state vectors, i.e., x(0) = x0 and y(0) = y0, let T be the total time of transient interaction simulation, and given the system parameter p(t) in [0, T], find x(t), y(t) that satisfy equations (1) and (2) in the time window [0, T].

[0051] When calculating the state quantity of the transient interaction analysis process of the solar-storage direct-flexible system in a high temperature and high humidity environment, due to the nonlinearity of the power electronic devices in the system, the analytical solutions of the equations (1) and (2) cannot be expressed in explicit expressions, so it is necessary to use simulation methods to approximate the solution. However, the essence of the traditional numerical integration method for solving the initial value problem is to use a series of discrete approximate solutions to accurately fit the exact solution. For example, assuming that the duration of a time step is denoted as Δt, find a sequence where k = 0, ..., [T / Δt] 2 and is an approximate solution. In order to give an approximate approximation to the continuous variable x(t) in [0,T], the entire sequence uses sub-steps to calculate each sequence However, these simulation methods usually introduce a simulation error, which can lead to a significant increase in the value of the variables at each time step, as well as convergence problems caused by the algebraic equations.

[0052] Different from the traditional numerical integration method, the semi-analytical method used in the present invention first finds the continuous approximate solution of the differential algebraic equation. The entire approximate solution is a set of pre-set semi-analytical expressions determined by high-order numbers, and its general mathematical expression is as follows:

[0053]

[0054] Among them, t is the independent variable of the time-domain differential-algebraic model, and h is the augmented time-domain model of the semi-analytical method.

[0055] The solar-storage direct-flexible system model (i.e., the system of equations formed by equations (1) and (2)) is usually a holomorphic function of events. Therefore, we will construct an approximate solution in the form of time t. The format of the approximate solution and parameters is as follows:

[0056]

[0057] in, Represents the approximate solution. For computational feasibility and based on accuracy requirements, the approximate order of these power series is customized when the algorithm is running. Substitute the semi-analytical approximate solutions of (4) to (6) into the power system time-domain differential algebraic model (1) to (2), and a series of equations describing the coupling relationship between the coefficients are obtained. These equations are converted into polynomials of coefficients according to the rules summarized in Table 1.

[0058] Table 1 Conversion rules of mathematical models

[0059]

[0060]

[0061] The basic principle of semi-analytical analysis of transient interaction characteristics: After the conversion of the above table, the following linear equation is obtained by combining similar terms:

[0062] A(x[0])x[k]=b(x[0],…,x[k-1])#(7)

[0063] In this case, x[k] contains all the coefficients of the kth order, A(x[0]) is a constant matrix that only depends on the initial conditions, and b(x[0],…,x[k-1]) is a function of all lower-order coefficients.

[0064] Finding each x[k] is constructed as a classic "Ax = b" problem. When solving an initial value problem, the initial condition x[0] is known, so the zero-order coefficients are known. Therefore, a recursive solution algorithm is designed to find the coefficients from the first order to the required order. The algorithm flowchart is as follows Figure 6 As shown, the residual is the value obtained by substituting the N-order numerical solution into the time-domain differential algebraic equation. The residual tolerance size is customized based on the trade-off between calculation accuracy and efficiency to determine the termination condition of the simulation stage.

[0065] In the RLC simulation test, the equivalent circuit is set by MATLAB, the iteration step is 5e-5 seconds / step, the transient operation time is 1 second, the equivalent power supply, resistance, inductance, and capacitance are set to 1V, 0.1Ω, 10mH, and 1000uF respectively. The effect of the equivalent circuit test algorithm is tested by MATLAB code, and the effect diagrams of different algorithms are detected and compared with the theoretical analysis results, such as Figure 1-5 As shown in the figure, after testing, it can be seen that the algorithm has significantly better test results than other traditional calculation methods for transient interaction under the same simulation accuracy conditions.

[0066] A transient interaction characteristics analysis method for a photovoltaic, energy storage, direct current and flexible system under high temperature and high humidity environment based on the SAS calculation method. The SAS (semi-analytical solution) calculation method is used to efficiently analyze the transient characteristics of the photovoltaic, energy storage, direct current and flexible system to improve the system stability in complex environments. The SAS calculation method optimizes the steady-state and transient characteristics of the system in a high temperature and high humidity environment by adaptively adjusting the model parameters. The high-order nonlinear model of the system is decomposed and solved by parallel computing technology to improve the computing efficiency and real-time response capability. This method is used for joint transient analysis of photovoltaic power generation, energy storage system, direct current transmission and flexible dispatching equipment. The SAS calculation method can dynamically adjust the model parameters according to the changes in ambient temperature and humidity to improve the adaptability of the model, and accurately describe the transient interaction behavior within the system based on multiple iterative analyses of the system's dynamic characteristics.

[0067] Combined with the characteristics of the PV-storage-direct-flexible system, a model optimization strategy for high temperature and high humidity conditions is proposed. This method improves the overall stability of the system by analyzing the coupling effect between components. An adaptive control algorithm is used to adjust the key variables in the system operation process in real time. This method can be integrated into the online monitoring and control platform of the power system to achieve real-time operation optimization of the PV-storage-direct-flexible system.

[0068] 1. Establish a nonlinear dynamic model of the photovoltaic-storage-direct-current-flexible system, including photovoltaic power generation, energy storage system, direct current transmission and flexible scheduling equipment.

[0069] 2. Use SAS calculation method to model the system semi-analytically, and improve the accuracy of the model by combining analytical solution with numerical solution.

[0070] 3. Introducing parallel computing technology, the high-order nonlinear model is decomposed into multiple sub-modules, and parallel computing is performed to accelerate the solution, which significantly improves the computing efficiency.

[0071] 4. According to the high temperature and high humidity conditions of the environment, the model parameters are adaptively adjusted to improve the dynamic response capability and adaptability of the system in complex environments.

[0072] The state space analysis method is used to simplify complex nonlinear dynamic models into a state space form suitable for parallel solution, thereby improving the efficiency and accuracy of the calculation. Preferably, the parallel processing is combined with a multi-core processor or distributed computing resources, which can monitor the dynamic state of the system in real time and meet the needs of online analysis. Preferably, the method is particularly suitable for scenarios where photovoltaic and energy storage systems are jointly operated, especially in extreme environments of high temperature and high humidity, to improve the control efficiency and operation stability of the system.

[0073] This method aims to improve the operating stability and peak-shaving capability of the system under extreme environmental conditions by combining SAS (semi-analytical solution) computing technology with parallel processing technology. It belongs to the field of power system dynamic analysis technology. The system adaptively adjusts the model parameters through the SAS (semi-analytical solution) calculation method to improve the operating stability and peak-shaving capability in complex environments. The complex nonlinear models within the system are efficiently analyzed through the parallelized SAS calculation method, which greatly improves the computing efficiency and real-time response performance. Compared with traditional methods, the present invention has higher flexibility, can effectively adapt to extreme environments such as high temperature and high humidity, is suitable for the joint operation of photovoltaic power generation, energy storage systems and direct current transmission, and has broad application prospects.

[0074] The proposed method adopted in this patent can be applied to the photovoltaic storage direct-flexible system under high temperature and high humidity conditions, and can effectively realize the accurate analysis of the transient interaction characteristics within the system, so as to improve the operation stability and peak-shaving efficiency of the power grid in Shanghai and other East China regions under extreme weather conditions. In view of the fact that traditional analysis methods cannot accurately reflect the impact of high temperature and high humidity environment on the internal transient characteristics of the photovoltaic storage direct-flexible system, an analysis scheme based on the SAS (semi-analytical solution) calculation method is proposed, coupling the dynamic change characteristics of the equipment model parameters with the ambient temperature and humidity, and proposing a high-precision transient analysis model, so as to realize in-depth research on the dynamic interaction between the components within the system, thereby optimizing the system design and control strategy.

[0075] In view of the low efficiency of traditional serial calculation methods and their difficulty in meeting real-time requirements, a parallelized SAS calculation method is proposed to improve calculation efficiency and meet the needs of real-time analysis and online monitoring. In addition, in view of the shortcomings of the existing model parameters being fixed and difficult to adapt to environmental changes, the proposed scheme can adaptively adjust the model parameters according to the changes in equipment parameters under high temperature and high humidity environments, thereby improving the analysis accuracy and model adaptability. In the context of high temperature and high humidity in summer, the proposed scheme greatly improves the transient analysis and prediction capabilities of the photovoltaic storage direct-flexible system, providing a strong guarantee for the safe and stable operation of the power grid in extreme environments.

Claims

1. A method for analyzing transient interaction characteristics of a solar-storage direct-flexible system under high temperature and high humidity environment, characterized in that: The following steps are involved: S1. Establish a system model, abstract the dynamic behavior of the optical storage direct-flexible system into a differential algebraic model; then, initialize the state and parameters, including initial conditions and simulation time, wherein the initial conditions include determining the initial state vector; S2. Use SAS calculation method to construct approximate solution, use power series expansion to represent dynamic state variables and algebraic state variables; then, dynamically adjust model parameters according to real-time temperature and humidity changes in high temperature and high humidity environment; S3. Establish a linear equation describing the coupling relationship between the coefficients and convert the equation into a coefficient polynomial; then, starting from the zero-order coefficient, recursively solve the higher-order coefficients step by step, and then calculate the residual after substitution into the equation to evaluate the accuracy of the approximate solution; Then, parallel computing technology is used to decompose and solve the high-order nonlinear model of the system; S4. Construct a local RLC topology, set the dynamic component parameters according to the electrical topology in the actual application, run the transient simulation, record the results of the system state variables changing over time, and perform multiple iterations to accurately describe the transient interaction behavior within the system; then compare the simulation results with the ideal waveform to analyze the coupling effects between the components; S5. Use adaptive control algorithms to adjust key variables during system operation.

2. The transient interaction characteristics analysis method of a solar-storage direct-flexible system under a high temperature and high humidity environment according to claim 1 is characterized in that: In S1, the differential algebraic model is: 0 = g(x(t), y(t), p(t)) Where t is time, x is the dynamic state variable, y is the algebraic state variable, p is the system parameter, and f and g are equations that describe the behavior of the system.

3. The transient interaction characteristics analysis method of a solar-storage direct-flexible system under a high temperature and high humidity environment according to claim 2 is characterized in that: In S1, the initial state vector is: x(0)=x0 and y(0)=y0.

4. The transient interaction characteristics analysis method of a solar-storage direct-flexible system under a high temperature and high humidity environment according to claim 3 is characterized in that: In S3, the expressions of the approximate solution and model parameters are: In the formula, x ^ (t) is the dynamic state variable, y ^ (t) is the algebraic state variable, p ^ (t) The time-dependent approximate solution of the system parameters is expressed in the form of a power series expansion as a combination of various order coefficients x[k], y[k] and p[k], where t is the time variable.

5. The transient interaction characteristics analysis method of a PV-storage direct-flexible system under a high temperature and high humidity environment according to claim 1 is characterized in that: In S5, by substituting the approximate solution into the time-domain differential algebraic model of the power system, a linear equation describing the coupling relationship between the coefficients is established.

6. The transient interaction characteristics analysis method of a solar-storage direct-flexible system under a high temperature and high humidity environment according to any one of claims 1 to 5, characterized in that: Online monitoring and control platform for power systems.

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