A method for analyzing transient interaction characteristics of a light storage direct flexible system in a high-temperature and high-humidity environment

Abstract

The application discloses a kind of high temperature and high humidity environment under light storage straight flexible system transient interaction characteristic analysis method, first establish the differential algebraic model of dynamic behavior, initialization state and parameter;Then, approximate solution is constructed using SAS method, and model parameters are dynamically adjusted according to real-time temperature and humidity;Linear equation of coupling relationship is established, high-order coefficient is recursively solved, and residual error is calculated to evaluate accuracy;High-order nonlinear model is solved using parallel computing technology, local RLC topology is constructed for transient simulation, system state change with time is recorded, and coupling effect of each component is analyzed;Finally, adaptive control algorithm is used to adjust key variables.The application is based on SAS calculation method, for the dynamic response of light storage straight flexible system under high temperature and high humidity environment, efficient transient analysis is realized, and the operation reliability and control ability of the system are significantly improved.The application is applied to power system online monitoring and control platform, and real-time optimization is realized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of dynamic analysis of power systems, and particularly relates to a method for analyzing transient interaction characteristics of a photovoltaic energy storage direct flexible system in a high-temperature and high-humidity environment. BACKGROUND

[0002] Shanghai and East China have the weather feature of "rain and heat in the same period", and hot and humid weather often occurs in summer. Such extreme weather not only causes large-scale fluctuations in power load levels, but also affects the operation efficiency of various elements such as sources, networks, loads and storages in the power system, reduces the capacity of peak regulation resources, and increases the difficulty of peak regulation. 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 network side, high humidity increases the difficulty of equipment heat dissipation and the short-circuit risk of transmission lines; on the load side, high-temperature weather significantly increases the usage rate and average power of air conditioners and refrigeration equipment, leading to a sharp rise in power 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 photovoltaic energy storage direct flexible technology is a solution that comprehensively utilizes various resources through photovoltaic, energy storage, direct current transmission and flexible operation technology, and its advantages are as follows: 1) high photovoltaic power generation efficiency in summer with abundant sunlight; 2) energy storage system plays a role in peak shaving and valley filling to smooth the power demand curve; 3) low loss and high efficiency of direct current transmission system, which can effectively transmit long-distance power; and 4) flexible interaction technology can improve the reliability and response capability of the power grid under extreme weather conditions.

[0004] However, the current analysis methods for the transient interaction characteristics of photovoltaic energy storage direct flexible systems mainly include time-domain simulation analysis, small-signal frequency-domain analysis, energy function analysis and state space analysis, etc. These methods can comprehensively analyze the transient interaction characteristics, but still have some shortcomings. Specifically, 1) the existing time-domain simulation algorithm usually adopts a serial calculation method, and due to the high-order mathematical model of the photovoltaic energy storage direct flexible system, the time cost of serial calculation limits the size and accuracy of the simulation model, making it difficult to meet the accurate 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, resulting in a too small stability domain of the system operation, thereby 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 perturbations is linear, but there are a large number of nonlinear elements in the photovoltaic energy storage direct flexible system, and the linearization model cannot effectively reflect the nonlinear characteristics of power electronic equipment; 4) the photovoltaic energy storage direct flexible system contains a large number of devices and components, each of which may need multiple state variables for description, and the state space analysis method may cause the "dimension disaster" of the entire state space system, which is not conducive to transient interaction analysis.

[0005] The defects of the above method will lead to the difficulty in accurately predicting the operation 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 generation technology, photovoltaic and energy storage systems are gradually expanding in modern power systems. However, these new energy generation devices inevitably face severe challenges from extreme environmental conditions during operation, especially under high temperature and high humidity conditions, which puts higher requirements on the operation stability and reliability of the system. Under such extreme conditions, the dynamic interaction characteristics of each component in the photovoltaic and energy storage system are more complex, and the traditional analysis method is difficult to effectively cope with it.

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

[0008] Some existing improvement schemes, such as convolutional neural network (CNN) for new energy multi-station transient analysis and simulation method based on frequency domain, although to some extent, improve the accuracy of the analysis, but these methods rely on large-scale data sets and complex training process, and the adaptability to environmental changes is relatively poor. When facing 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 internal devices of the system. In addition, the dynamic coupling relationship between components in the power system becomes more complex under extreme environment, which further aggravates the difficulty of analysis. SUMMARY

[0009] The present application provides a photovoltaic and energy storage system transient interaction characteristic analysis method under high temperature and high humidity environment, to solve the existing technical problems.

[0010] To solve the above technical problems, the technical solution provided by the present application is:

[0011] A photovoltaic and energy storage system transient interaction characteristic analysis method under high temperature and high humidity environment, comprising the following steps:

[0012] S1. Establish a system model to abstract the dynamic behavior of the photovoltaic and energy storage system as a differential algebraic model; then, initialize the state and parameters, including initial conditions and simulation time, the initial conditions including determining the initial state vector;

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

[0014] S3. By substituting the approximate solution into the power system time-domain differential-algebraic model, a linear equation describing the coupling relationship between the coefficients is established, and the equation is converted into a coefficient polynomial; then, starting from the zero-order coefficient, the high-order coefficients are recursively solved, and then the residual of the substituted equation is calculated to evaluate the accuracy of the approximate solution; and the parallel computing technology is used to decompose and solve the high-order nonlinear model of the system;

[0015] S4. Construct a local RLC topology structure, set the dynamic element parameters according to the electrical topology structure in actual application, run the transient simulation, record the results of the change of the system state variables with time, and perform multiple iteration analysis to accurately describe the transient interaction behavior inside the system; then, compare the simulation results with the ideal waveform, and analyze the coupling effect between components;

[0016] S5. Adopt an adaptive control algorithm to adjust the key variables in the system operation process.

[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] In the formula, t is time, x is a dynamic state variable, y is an algebraic state variable, p is a system parameter, and f and g are equations describing system behavior.

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

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

[0024]

[0025] In the formula, x^(t) is a time-dependent approximate solution of a dynamic state variable, y^(t) is a time-dependent approximate solution of an algebraic state variable, and p^(t) is a time-dependent approximate solution of a system parameter, and is expressed by a power series expansion form as a combination of coefficients x[k], y[k] and p[k] of each order, wherein t is a time variable.

[0026] A kind of high temperature and high humidity environment under light storage direct flexible system transient interaction characteristic analysis method, applied to the online monitoring and control platform of power system.

[0027] Compared with prior art, the beneficial effects of the present application are:

[0028] 1, the traditional time-domain simulation analysis method usually adopts serial computing mode, in the face of high-order mathematical model of light storage direct flexible system, long calculation time, it is difficult to meet the requirements of real-time and high precision.The SAS calculation method is used in the present application, the complex nonlinear equation is decomposed into easy-to-solve part, the global numerical integration is avoided, combined with parallel computing technology, the calculation efficiency is significantly improved.This makes it suitable for accurate analysis of large-scale, high-order model, meets the needs of real-time monitoring and online analysis.

[0029] 2, the traditional small signal frequency domain analysis method is based on linearization process, mainly used to study the stability of system under small disturbance.Although it can effectively deal with linear problems, for the system under strong nonlinearity and large disturbance, small signal analysis method cannot accurately reflect the real dynamic behavior of the system.The SAS calculation method is used in the present application to decompose complex nonlinear differential equations, and the accurate solution of the system is gradually approached, which can directly process nonlinear systems without linearization, and is suitable for analyzing the obvious nonlinear behavior of photovoltaic, energy storage and power electronic equipment.

[0030] 3, the traditional energy function method is difficult to construct a suitable energy function for highly nonlinear power systems, and it is also difficult to deal with the situation that the system parameters change dynamically with external conditions during system operation under extreme weather conditions.The SAS calculation method used in the present application can handle the uncertainty factors of the system, such as environmental impact and equipment state change, by refining the decomposition time interval when facing the parameter change of the system under high temperature and high humidity conditions, and is more flexible and adaptable.

[0031] 4, the model dimension of the traditional state space method will increase rapidly with the complexity and size of the system, resulting in too large state vector dimension, increasing the difficulty of analysis and calculation.When dealing with large complex systems, the calculation and storage cost of state space method will be significantly improved.The SAS calculation method used in the present application can solve complex dynamic problems at lower computational cost by gradually decomposing the problem when dealing with complex systems.It is more adaptable to the size and complexity of the system, especially when dealing with multiple dynamic subsystems and complex interactions, the decomposition process of semi-analytical method can avoid a large amount of calculation. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0033] Figure 1 For the ideal transient operation result diagram of the local RLC topology of the optical storage direct flexible system in the embodiment of the present application.

[0034] Figure 2 For the result diagram of the local RLC topology of the optical storage direct flexible system in the embodiment of the present application, the semi-analytical method is adopted.

[0035] Figure 3 For the result diagram of the local RLC topology of the optical storage direct flexible system in the embodiment of the present application, the trapezoidal algorithm is adopted.

[0036] Figure 4 For the result diagram of the local RLC topology of the optical storage direct flexible system in the embodiment of the present application, the improved Euler method is adopted.

[0037] Figure 5 For the result diagram of the local RLC topology of the optical storage direct flexible system in the embodiment of the present application, the 4th order-Runge-Kutta method is adopted.

[0038] Figure 6 For the algorithm flowchart. DETAILED DESCRIPTION

[0039] In order to facilitate the understanding of the present application, the following will make a more comprehensive and detailed description of the present application in combination with the drawings of the specification and the preferred embodiments, but the protection scope of the present application is not limited to the following specific embodiments.

[0040] Unless otherwise defined, all the professional terms used in the following have the same meaning as that generally understood by those skilled in the art. The professional terms used in the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the protection scope of the present application.

[0041] Unless otherwise specified, various raw materials, reagents, instruments and equipment, etc. used in the present application can be purchased from the market or can be prepared by the existing method.

[0042] The application proposes an efficient analysis scheme based on a 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 and numerical solution on the basis of preserving the nonlinear characteristics of the system. Compared with 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 dynamic response analysis of various devices in the optical storage direct flexible system under high temperature and high humidity environment.

[0043] In addition, the application introduces parallel processing technology, further improving the analysis efficiency and accuracy of the transient interaction characteristics of the system. By combining the state space analysis method, the high-order nonlinear model of the optical storage direct flexible system can be converted into a more suitable form for calculation, and parallel computing is 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 stability of the system, but also provides strong support for power scheduling and operation optimization in complex extreme environments.

[0044] In summary, by combining the SAS calculation method, state space analysis and parallel computing processing, the application effectively overcomes the shortcomings of traditional transient analysis methods, and can accurately analyze the dynamic interaction characteristics inside the optical storage direct flexible system under extreme climate conditions such as high temperature and high humidity, significantly improving the operation reliability and control ability of the system.

[0045] Embodiment: The state equation of the optical storage direct flexible system is abstracted as the following mathematical model:

[0046]

[0047] 0=g(x(t),y(t),p(t)) (2)

[0048] Where t is time, x is dynamic state variable, y is algebraic state variable, p is system parameter, f and g are equations describing system behavior. In practical application of power system, f and g are holomorphic functions, which means they are locally infinitely differentiable in complex space and equal to their Taylor expansion.

[0049] 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 give 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].

[0050] When calculating the state variables of the optical storage direct flexible system in the process of transient interaction analysis in high temperature and high humidity environment, due to the nonlinearity of the power electronic device in the system, the analytical solution of equations (1) and (2) cannot be obtained. Therefore, it is necessary to use simulation method to approximate solution. However, the essence of solving initial value problem by traditional numerical integration method is to use a series of discrete approximate solutions to accurately fit the exact solution. For example, suppose the duration of a time step is Δt, find a sequence Where k = 0, …, [T / Δt] 2 And Is the approximate solution. The entire sequence uses sub steps to calculate each sequence However, these simulation methods usually introduce a simulation error, which will lead to a great increase in the value of the variable at each time step, and the convergence problem caused by algebraic equation.

[0051] Unlike traditional numerical integration method, the semi-analytical method used in the present application first finds the continuous approximate solution of the differential algebraic equation. The entire approximate solution is a set of semi-analytical expressions determined by high order series, and its general mathematical expression is as follows:

[0052]

[0053] Where 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.

[0054] The optical storage direct flexible system model (i.e. the equation group composed of equations (1) and (2)) is usually a holomorphic function about the event. Therefore, we will construct the approximate solution in the form of time t, and the format of the approximate solution and parameters is as follows:

[0055]

[0056] Where, The approximate solution represents the approximate solution. In order to ensure the feasibility of calculation, based on the accuracy requirement, the approximate order of the power series is customized during the algorithm running, and the semi-analytical approximate solution of (4) ~ (6) is substituted into the time domain differential algebraic model (1) ~ (2) of the power system to obtain a series of equations describing the coupling relationship between the coefficients. These equations are converted into polynomials of coefficients according to the rules summarized in table 1.

[0057] Table 1 conversion rules of mathematical model

[0058]

[0059]

[0060] Basic principle of semi-analytical method for analyzing transient interaction characteristics: After the conversion of the above table, the linear equations are obtained as follows by using the same item merging:

[0061] A(x[0])x[k]=b(x[0],…,x[k-1]) (7)

[0062] Where x[k] contains all the coefficients of the kth order, A(x[0]) is a constant matrix related only to the initial condition, and b(x[0],…,x[k-1]) is a function of all lower order coefficients.

[0063] Each x[k] is constructed as a classic "Ax=b" problem. In solving an initial value problem, the initial condition x[0] is known, so the zeroth order coefficient is known. Therefore, a recursive solution algorithm is designed to find the coefficients from the first order to the required order, and the algorithm flow chart is as shown in Figure 6 The residual error is the numerical value obtained by substituting the Nth order series solution into the time domain differential algebraic equation, and the residual error tolerance is defined based on the trade-off between calculation accuracy and efficiency to determine the termination condition of the simulation stage.

[0064] In the RLC simulation test, the equivalent circuit is set up by MATLAB, the iteration step is 5e-5 seconds / step, the transient running time is 1 second, the equivalent power, 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 using MATLAB code, and the effect diagrams of different algorithms are detected and compared with the theoretical analysis results, as shown in Figures 1-5 The test results show that the algorithm for transient interaction operation under the same simulation accuracy condition is obviously better than other traditional calculation methods.

[0065] A method for analyzing the transient interaction characteristics of a light storage direct flexible system in a high temperature and high humidity environment based on a SAS calculation method, which uses the SAS (semi-analytical solution) calculation method to efficiently analyze the transient characteristics of the light storage direct flexible system to improve the stability of the system in complex environments. The SAS calculation method adjusts the model parameters adaptively to realize the optimization of the steady-state and transient characteristics of the system in high temperature and high humidity environments. Parallel computing technology is used to decompose and solve the high-order nonlinear model of the system, thereby improving the calculation efficiency and real-time response capability. This method is used for joint transient analysis of photovoltaic power generation, energy storage systems, direct current transmission and flexible scheduling equipment. The SAS calculation method can dynamically adjust the model parameters according to the changes of environmental temperature and humidity to improve the adaptability of the model, and based on multiple iterative analysis of the dynamic characteristics of the system, the transient interaction behavior inside the system is accurately described.

[0066] In combination with the characteristics of the optical storage direct flexible system, a model optimization strategy for high temperature and high humidity conditions is proposed. The method improves the overall stability of the system by analyzing the coupling effect between each component. The adaptive control algorithm is used to adjust the key variables in real time during the operation of the system. The method can be integrated into the online monitoring and control platform of the power system to realize real-time operation optimization of the optical storage direct flexible system.

[0067] 1. Establish a nonlinear dynamic model of the optical storage direct flexible system, including photovoltaic power generation, energy storage system, direct current transmission and flexible scheduling equipment.

[0068] 2. The SAS calculation method is used to model the system, and the analytical solution is combined with the numerical solution to improve the accuracy of the model.

[0069] 3. Parallel computing technology is introduced to decompose the high-order nonlinear model into multiple sub-modules, and parallel computing is used to speed up the solution, significantly improving the calculation efficiency.

[0070] 4. According to the high temperature and high humidity conditions of the environment, the model parameters are adaptively adjusted to improve the dynamic response ability and adaptability of the system in complex environments.

[0071] The state space analysis method is used to simplify the complex nonlinear dynamic model into a state space form suitable for parallel solution, thereby improving the efficiency and accuracy of the calculation. Preferably, parallel processing combines multi-core processors or distributed computing resources, which can monitor the dynamic state of the system in real time, meeting the online analysis requirements. Preferably, this method is particularly suitable for photovoltaic and energy storage system joint operation scenarios, especially in high temperature and high humidity extreme environments, to improve the system's regulation efficiency and operation stability.

[0072] The method combines SAS (semi-analytical solution) calculation technology and parallel processing technology to improve the operation stability and peak regulation capacity of the system in extreme environmental conditions. It belongs to the field of dynamic analysis technology of power systems. The system adaptively adjusts the model parameters through the SAS (semi-analytical solution) calculation method to improve the operation stability and peak regulation capacity in complex environments. The complex nonlinear model inside the system is analyzed efficiently through the parallel SAS calculation method, greatly improving the calculation efficiency and real-time response performance. Compared with traditional methods, the present invention has higher flexibility and can effectively adapt to extreme environments such as high temperature and high humidity, and is suitable for the joint operation of photovoltaic power generation, energy storage systems and direct current transmission, with wide application prospects.

[0073] The proposed method 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 of the system, 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 the traditional analysis method cannot accurately reflect the influence of high temperature and high humidity environment on the transient characteristics of photovoltaic storage direct flexible system, an analysis scheme based on SAS (Semi-Analytical Solution) calculation method is proposed, which couples the dynamic change characteristics of equipment model parameters and environmental temperature and humidity, and proposes a high-precision transient analysis model to realize the in-depth study of the dynamic interaction between the components in the system, so as to optimize the system design and control strategy.

[0074] In view of the low efficiency of traditional serial calculation method and the difficulty in meeting the real-time requirements, a parallel SAS calculation method is proposed to improve the calculation efficiency and meet the real-time analysis and online monitoring requirements. In addition, in view of the fixed model parameters and the difficulty in adapting to environmental changes, the proposed scheme can adaptively adjust the model parameters according to the changes of equipment parameters under high temperature and high humidity environment, thereby improving the analysis accuracy and model adaptability. Under the climate background of high temperature and high humidity in summer, the proposed scheme greatly improves the transient analysis and prediction ability of photovoltaic storage direct flexible system, and provides a strong guarantee for the safe and stable operation of power grid under extreme environment.

Claims

1. A method for analyzing the transient interaction characteristics of a photovoltaic-storage-direct-drive-flexible system under high temperature and high humidity conditions, characterized in that, Includes the following steps: S1. Establish a system model and 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. An approximate solution is constructed using the SAS calculation method, and power series expansion is used to represent dynamic and algebraic state variables. Then, the model parameters are dynamically adjusted according to the real-time temperature and humidity changes under high temperature and humidity conditions. S3. 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, and the equation is transformed into a coefficient polynomial. Then, starting from the zero-order coefficients, the higher-order coefficients are solved recursively step by step, and the residuals of the equation after substitution are calculated to evaluate the accuracy of the approximate solution. Then, parallel computing techniques are used to decompose and solve the high-order nonlinear model of the system; S4. Construct a local RLC topology, set dynamic component parameters according to the electrical topology in the actual application, run transient simulation, record the results of system state variables changing over time, and perform multiple iterative analyses to accurately describe the transient interaction behavior inside the system; then compare the simulation results with the ideal waveform to analyze the coupling effect between components. S5. Adaptive control algorithms are used to adjust key variables during system operation; In S1, the differential algebraic model is: In the formula, t is time, x is a dynamic state variable, y is an algebraic state variable, p is a system parameter, and f and g are equations describing the behavior of the system.

2. The method for analyzing transient interaction characteristics of a photovoltaic-storage-direct-flexible system under high temperature and high humidity conditions according to claim 1, characterized in that, In S1, the initial state vectors are: x(0) = x0 and y(0) = y0, where x0 represents the initial value of the x state vector and y0 represents the initial value of the y state vector.

3. The method for analyzing transient interaction characteristics of a photovoltaic-storage-direct-flexible system under high temperature and high humidity conditions according to claim 2, characterized in that, In S3, the expressions for the approximate solution and model parameters are: In the formula, x^(t) is the time-dependent approximate solution of the dynamic state variable, y^(t) is the time-dependent approximate solution of the algebraic state variable, and p^(t) is the time-dependent approximate solution of the system parameters. It is expressed as a combination of coefficients x[k], y[k] and p[k] of each order through a power series expansion, where t is the time variable.

4. The method for analyzing transient interaction characteristics of a photovoltaic-storage-direct-drive-flexible system under high temperature and high humidity conditions according to any one of claims 1-3, characterized in that, An online monitoring and control platform for power systems.

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