Method and system for comprehensively evaluating grid-connected performance of electric vehicle charging and discharging station

Abstract

The invention provides a comprehensive evaluation method and system for grid-connected performance of an electric vehicle charging and discharging station, and relates to the technical field of electric vehicle charging and discharging stations, and the method comprises the steps: obtaining real-time power grid performance parameters and electric vehicle charging and discharging station performance parameters; establishing a power interaction coupling model between the power grid and the electric vehicle charging and discharging station; extracting a nonlinear coupling term; establishing a coupling state matrix for describing the interaction state of the power grid and the electric vehicle charging and discharging station; calculating a characteristic value of the coupling state matrix, and calculating a characteristic value information entropy; determining a characteristic value information entropy stable threshold value based on a Hopf bifurcation theory; and judging whether the power grid performance parameter, the electric vehicle charging and discharging station performance parameter and the characteristic value information entropy meet a joint stability condition, if so, outputting that the grid-connected performance of the electric vehicle charging and discharging station is qualified, otherwise, outputting that the grid-connected performance of the electric vehicle charging and discharging station is unqualified. The accuracy and reliability of the evaluation result are improved, and the potential power grid fluctuation risk is effectively avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging and discharging stations, and in particular to a method and system for comprehensively evaluating the grid-connected performance of electric vehicle charging and discharging stations. Background Art

[0002] An electric vehicle charging and discharging station is a facility dedicated to providing charging and discharging services for electric vehicles. It consists of multiple charging stations, an energy management system, energy storage equipment, and equipment connected to the power grid. Charging stations not only provide charging services for electric vehicles but also transfer stored energy back to the grid as needed, participating in energy regulation and demand response.

[0003] As the number of electric vehicles increases, electric vehicle charging and discharging stations, as important energy input and output nodes, have a direct impact on the stability and security of the power grid. If a charging and discharging station's grid-connection performance fails to meet standards, it can lead to problems such as load imbalance and frequency fluctuations, impacting the grid's normal operation. By evaluating its grid-connection performance, we can ensure that the grid does not become unstable during the electric vehicle charging and discharging process. This can also promote coordinated interaction between electric vehicles and the power grid, helping to improve the overall efficiency and reliability of the power grid.

[0004] However, the existing comprehensive evaluation process for the grid-connected performance of electric vehicle charging and discharging stations usually only focuses on whether the operating parameters of the power station and the power grid are normal during the charging or discharging process, ignoring the coupling state between the power station and the power grid during the charging and discharging interaction process. As a result, it is impossible to accurately assess the actual impact of the power station on the stability of the power grid after grid connection, which in turn leads to possible potential electricity consumption risks. Summary of the Invention

[0005] In view of the above-mentioned deficiencies in the prior art, the purpose of the embodiments of the present invention is to provide a comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station, which can solve the technical problem that the existing comprehensive evaluation process of the grid-connected performance of an electric vehicle charging and discharging station in the prior art usually only focuses on whether the working parameters of the power station and the power grid during the charging or discharging process are normal, and ignores the coupling state between the power station and the power grid during the charging and discharging interaction process, resulting in the inability to accurately evaluate the actual impact of the power station on the stability of the power grid after grid connection, and thus leading to possible potential electricity consumption risks.

[0006] A first aspect of an embodiment of the present invention provides a comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station, comprising:

[0007] S1: Obtain real-time grid performance parameters and electric vehicle charging and discharging station performance parameters;

[0008] S2: Based on the performance parameters of the power grid and the performance parameters of the electric vehicle charging and discharging station, a power interaction coupling model between the power grid and the electric vehicle charging and discharging station is established;

[0009] S3: Extracting nonlinear coupling terms from the power interaction coupling model. The nonlinear coupling terms are used to quantify the second-order nonlinear effects of performance parameter disturbances of electric vehicle charging and discharging stations on the power grid.

[0010] S4: Integrate the power interaction coupling model and nonlinear coupling terms to establish a coupling state matrix that describes the interaction state between the power grid and the electric vehicle charging and discharging station;

[0011] S5: Calculate the eigenvalues of the coupling state matrix and calculate the eigenvalue information entropy;

[0012] S6: Determine the eigenvalue information entropy stability threshold based on Hopf bifurcation theory;

[0013] S7: Combined with the eigenvalue information entropy stability threshold, determine whether the power grid performance parameters, the electric vehicle charging and discharging station performance parameters and the eigenvalue information entropy meet the joint stability conditions. If so, output that the electric vehicle charging and discharging station grid-connected performance is qualified; otherwise, output that the electric vehicle charging and discharging station grid-connected performance is unqualified.

[0014] A second aspect of an embodiment of the present invention provides a comprehensive evaluation system for grid-connected performance of an electric vehicle charging and discharging station, comprising: a processor and a memory;

[0015] The memory stores programs or instructions that can be run on the processor. When the programs or instructions are executed by the processor, the steps of the comprehensive evaluation method for the grid-connected performance of electric vehicle charging and discharging stations as described in the first aspect are implemented.

[0016] According to a third aspect of an embodiment of the present invention, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station as described in the first aspect are implemented.

[0017] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0018] In an embodiment of the present invention, the comprehensive evaluation method for the grid-connected performance of electric vehicle charging and discharging stations not only considers the normality of the operating parameters of the power station and the power grid, but also comprehensively quantifies the nonlinear coupling effects during the power station's charging and discharging process by establishing a power interaction coupling model between the power grid and the charging and discharging station, thereby accurately assessing the actual impact of the power station's grid connection on grid stability. In particular, the introduction of Hopf bifurcation theory and the concept of eigenvalue information entropy thresholds into the evaluation process enables the method to dynamically, comprehensively, and objectively reflect the stability and potential risks associated with the grid-connected electric vehicle charging and discharging station, thereby improving the accuracy and reliability of the evaluation results and effectively avoiding potential grid fluctuation risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are only for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. Throughout the drawings, the same reference symbols represent the same components. Obviously, the drawings described below are only some embodiments of the present invention. It is clear that those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0020] Figure 1 This is a flow chart of a comprehensive evaluation method for grid-connected performance of an electric vehicle charging and discharging station provided by an embodiment of the present invention;

[0021] Figure 2 The present invention provides a schematic structural diagram of a comprehensive evaluation system for the grid-connected performance of an electric vehicle charging and discharging station. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are part of the embodiments of the present invention, rather than all of the embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work should fall within the scope of protection of the present invention.

[0023] The method for comprehensively evaluating the grid-connected performance of an electric vehicle charging and discharging station provided by the embodiment of the present invention will be described in detail below with reference to the accompanying drawings through specific embodiments and application scenarios.

[0024] Reference Manual Figure 1 , which shows a flow chart of a comprehensive evaluation method for grid-connected performance of an electric vehicle charging and discharging station provided by an embodiment of the present invention.

[0025] An embodiment of the present invention provides a method for comprehensively evaluating the grid-connected performance of an electric vehicle charging and discharging station, which may include the following steps:

[0026] S1: Obtain real-time grid performance parameters and electric vehicle charging and discharging station performance parameters.

[0027] It is understandable that by obtaining the performance parameters of the power grid and electric vehicle charging and discharging stations in real time, we can better understand the dynamic relationship between the power grid and the charging and discharging stations, and provide a data basis for evaluating their grid-connected performance.

[0028] In one possible implementation, the grid performance parameters include grid frequency deviation and grid voltage deviation. The electric vehicle charging and discharging station performance parameters include charging and discharging power, battery state of charge in the electric vehicle charging and discharging station energy storage system, and battery temperature.

[0029] Grid frequency deviation refers to the difference between the grid frequency and the ideal frequency. Grid voltage deviation refers to the difference between the grid voltage and the target voltage. An electric vehicle charging and discharging station energy storage system refers to the energy storage equipment used in electric vehicle charging and discharging stations to store and release electrical energy. This system typically includes batteries or other types of energy storage devices that store electrical energy during charging and release it when needed.

[0030] It should be noted that by simultaneously considering multiple key performance parameters such as grid frequency deviation, grid voltage deviation, and the charging and discharging power, battery state of charge and temperature of the electric vehicle charging and discharging station, it is possible to more comprehensively and accurately evaluate the actual impact of the grid connection of the electric vehicle charging and discharging station on the grid, ensure the stable interaction between the grid and the charging and discharging station, and thus improve the accuracy and reliability of the grid connection assessment.

[0031] S2: Based on the performance parameters of the power grid and the performance parameters of the electric vehicle charging and discharging station, a power interaction coupling model between the power grid and the electric vehicle charging and discharging station is established.

[0032] The power interaction coupling model is a mathematical model that describes the interaction between electric vehicle charging and discharging stations and the power grid. By considering the performance parameters of the power grid and the electric vehicle charging and discharging stations, the model describes how the two interact and couple during the charging and discharging process.

[0033] It is important to note that by integrating the performance parameters of the power grid and EV charging and discharging stations, a mutually coupled model is established that accurately reflects the mutual influence between the two. This model captures the energy flow and dynamic response between EV charging and discharging stations and the grid, providing a detailed assessment of grid stability. By quantifying the complex coupling effects between the two from a global perspective, it avoids the limitations of evaluating grid-connected performance from a single perspective, thereby improving the accuracy and reliability of the assessment.

[0034] In a possible implementation, the power interaction coupling model is specifically:

[0035]

[0036]

[0037]

[0038] in, Indicates the grid frequency deviation, Indicates the grid voltage deviation, represents the grid load damping coefficient, represents the equivalent inertia time constant of the power grid, The active-voltage coupling coefficient that quantifies the indirect effect of active power on the grid voltage, represents the reactive-voltage regulation gain that controls the dynamic process of grid voltage recovery, represents the grid voltage regulation time constant, represents the random noise of the grid frequency at time t, represents the random noise of the grid voltage at time t, It represents the active power exchanged between the electric vehicle charging and discharging station and the power grid at time t, i.e., the charging and discharging power. Indicates the battery charge status of the electric vehicle charging and discharging station. Indicates the battery temperature of the electric vehicle charging and discharging station, It indicates the charging and discharging efficiency of electric vehicle charging and discharging station, that is, the ratio of actual power to nominal power. Indicates the rated capacity of the battery in the electric vehicle charging and discharging station. Indicates the thermal capacity of the battery in the electric vehicle charging and discharging station, Indicates the internal resistance of the battery in the electric vehicle charging and discharging station. Indicates the battery current of the electric vehicle charging and discharging station, The thermal time constant of the electric vehicle charging and discharging station that controls the temperature response speed, Indicates the ambient temperature, represents the active power exchanged between the internal grid interface of the electric vehicle charging and discharging station and the energy storage system of the electric vehicle charging and discharging station at time t, It represents the power conversion efficiency coefficient of the grid-connected inverter in discharge mode, Indicates the power conversion factor of the grid-connected inverter in charging mode.

[0039] The grid load damping coefficient measures the grid load's response to frequency changes and reflects the grid's inertial characteristics. The active-voltage coupling coefficient describes the indirect impact of active power on voltage in the grid. Active power changes in the power system typically affect voltage, so this coefficient is used to quantify this effect. The reactive-voltage regulation gain represents the regulatory effect of reactive power on the grid voltage in the power system and is used to quantify the impact of reactive power changes on the grid voltage recovery process. The grid voltage regulation time constant measures the time it takes for the grid voltage to recover from a deviation from its normal value. It describes the time it takes for the grid voltage to return to a stable state through the grid's regulation mechanism after a disturbance. The battery state of charge indicates the battery's current charge level, typically expressed as a percentage. The charge and discharge power refers to the power exchanged between the electric vehicle charging and discharging station and the grid, which differs in charging and discharging modes. The inverter power conversion efficiency coefficient indicates the inverter's power conversion efficiency in both discharging and charging modes.

[0040] It's important to note that the power interaction coupling model comprehensively and accurately describes the complex interactions between the power grid and EV charging and discharging stations. This model not only considers key parameters such as grid frequency and voltage, but also factors like battery state of charge and temperature, quantifying the impact of power station charging and discharging on the grid. Through this multi-dimensional coupling, the model can effectively predict the potential impact of EV charging and discharging stations on grid stability after integration, thereby improving the accuracy and reliability of performance assessments of the grid and charging and discharging stations.

[0041] S3: Extract nonlinear coupling terms from the power interaction coupling model, where the nonlinear coupling terms are used to quantify the second-order nonlinear impact of performance parameter disturbances of electric vehicle charging and discharging stations on the power grid.

[0042] Nonlinear coupling terms are features extracted from the power interaction coupling model and are used to quantify the second-order nonlinear effects of performance parameter perturbations in electric vehicle charging and discharging stations on the power grid. These nonlinear coupling terms account for the complex interactions between the power station and the power grid. In particular, parameter changes during the charging and discharging process can have non-linear effects on the power grid, such as voltage and frequency fluctuations. These effects need to be quantified using nonlinear coupling terms.

[0043] It should be noted that extracting nonlinear terms allows for a more accurate description of the complex impact of EV charging and discharging stations on the grid during dynamic charging and discharging, particularly considering fluctuations and instabilities in the charging and discharging process. Capturing the nonlinear interactions between the grid and power stations improves the accuracy and reliability of grid-connected performance assessments.

[0044] In a possible implementation, S3 specifically includes:

[0045] S301: Expand the power interaction coupling model into an infinite series using the Volterra series.

[0046] The Volterra series is a mathematical tool for describing nonlinear systems. It expresses the output of a system as a function expansion of its input, taking into account the nonlinear effects of the input signal. An infinite series consists of an infinite number of terms, representing a value approximated by the cumulative sum of these terms. For a Volterra series, each term in the expansion can be viewed as a contribution at a different level to the interaction between the input signal and the system. Infinite series help us more accurately describe the nonlinear behavior of a system by gradually adding terms.

[0047] S302: Extract the second-order term, i.e., the nonlinear coupling term, from the infinite series.

[0048] In the Volterra series expansion, the second-order term represents the portion of the system response that is caused by the quadratic interaction between the input signals. Simply put, the second-order term reflects the nonlinear effect of the interaction of the input signal changes on the system output.

[0049] The nonlinear coupling term is specifically:

[0050]

[0051] in, represents the integration time window, It means to find the second-order partial derivative, Represents the grid state vector The norm of represents the state vector of the electric vehicle charging and discharging station, represents the nonlinear coupling matrix.

[0052] Optionally, the integration time window may be the duration of the transient process (eg, 10 s, covering the critical period of power mutation and temperature response).

[0053] It should be noted that the Volterra series expansion, which represents the power interaction coupling model as an infinite series, accurately captures the nonlinear coupling effects between the power grid and the EV charging and discharging stations. Second-order terms (i.e., nonlinear coupling terms) quantify the complex interactions between the grid and the charging and discharging stations by calculating the second-order partial derivatives between their states. These nonlinear coupling terms help more accurately describe the impact of fluctuations in the dynamic charging and discharging processes of EV charging and discharging stations on grid stability. By introducing second-order terms, the risk of overlooking higher-order nonlinear effects in the system can be effectively avoided, thereby improving the accuracy of grid-connected performance assessments, particularly in situations with large grid frequency and voltage fluctuations.

[0054] S4: Integrate the power interaction coupling model and nonlinear coupling terms to establish a coupling state matrix that describes the interaction state between the power grid and the electric vehicle charging and discharging station.

[0055] The coupling state matrix is a mathematical model used to describe the interaction between the power grid and EV charging and discharging stations. By integrating the power interaction coupling model with nonlinear coupling terms, the coupling state matrix effectively reflects the energy flow, dynamic changes, and interactions between the power grid and charging and discharging stations. Each element of the matrix represents the coupling relationship between the performance parameters of the power grid and the charging and discharging station.

[0056] Specifically, the coupling state matrix is:

[0057]

[0058] in, Represents the block splicing symbol.

[0059] It is important to note that this coupling state matrix fully integrates the grid's inherent stability characteristics with the nonlinear perturbations introduced by power plants within a single matrix. By integrating the power interaction coupling model and the nonlinear coupling terms, the coupling state matrix accurately describes the dynamic interaction between the grid and the EV charging and discharging station. This matrix couples the various performance parameters of the grid and the charging and discharging station, providing a comprehensive and accurate mathematical foundation for subsequent stability analysis and performance evaluation, enabling the evaluation results to better reflect the complexities of actual system operation.

[0060] S5: Calculate the eigenvalues of the coupling state matrix and calculate the eigenvalue information entropy.

[0061] It should be noted that calculating the eigenvalues and eigenvalue information entropy of the coupling state matrix helps analyze system stability. The magnitude and sign of the eigenvalues reveal the stability of the system during the interaction between the power grid and the charging and discharging stations, while the eigenvalue information entropy quantifies the system's dynamic complexity. This allows for the quantification and assessment of the complex dynamic behavior and stability risks that may occur during the interaction between the power grid and the charging and discharging stations.

[0062] In a possible implementation, S5 specifically includes:

[0063] S501: Establishing a characteristic equation of the coupling state matrix.

[0064] The characteristic equation is specifically:

[0065]

[0066]

[0067] Where M represents the coupling state matrix, represents the determinant, Represents Identity matrix of the same dimensions.

[0068] S502: Solve the characteristic equation to obtain the characteristic value.

[0069] S503: Calculate the eigenvalue information entropy using an information entropy algorithm.

[0070] The calculation formula of eigenvalue information entropy is as follows:

[0071]

[0072] in, represents the eigenvalue information entropy, represents the characteristic value of the i-th dimension in the power grid performance parameters, represents the natural exponential function.

[0073] Specifically, the interaction between the power grid and the EV charging and discharging stations is first analyzed by establishing the characteristic equation of the coupling state matrix. Solving the characteristic equation yields the system's eigenvalues, which provide crucial information about system stability. Then, using an information entropy algorithm, the eigenvalue information entropy is calculated. This metric quantifies the complexity and uncertainty of the system. The calculated entropy value can be used to determine system stability. The combination of eigenvalues and information entropy effectively captures the nonlinear effects and dynamic characteristics of the interaction between the power grid and the charging and discharging stations, enhancing the accuracy and reliability of the assessment and helping to identify potential stability issues in advance.

[0074] S6: Determine the eigenvalue information entropy stability threshold based on Hopf bifurcation theory.

[0075] Among them, the Hopf bifurcation theory is a mathematical theory used to describe the transition of a system from a stable state to an unstable state. When the system reaches a critical point, the eigenvalue changes from a real number to a pure imaginary number, which indicates that the system has entered a periodic oscillation state from a stable state. The Hopf bifurcation point is a key turning point in the dynamic behavior of the system and is usually used to analyze the stability of nonlinear dynamic systems. The eigenvalue information entropy stability threshold refers to the maximum stable entropy value determined by calculating the eigenvalue information entropy of the system within the framework of the Hopf bifurcation theory. When this threshold is exceeded, the system may become unstable. The eigenvalue information entropy stability threshold helps determine the critical point of the system's stability during the charging and discharging process. Once the entropy value exceeds this threshold, it may cause instability in the power grid and electric vehicle charging and discharging stations.

[0076] It's understandable that using Hopf bifurcation theory combined with eigenvalue information entropy to determine the critical threshold for system stability can accurately and objectively predict the stability boundary of the grid and electric vehicle charging and discharging station when connected. This avoids inaccurate grid performance assessments caused by artificially defined stability thresholds and provides a theoretical basis for taking proactive measures to prevent system instability. This approach not only accounts for the nonlinear dynamic behavior of the system but also provides a clear instability warning through entropy thresholds, helping to improve the reliability and stability of the grid-connected system.

[0077] In a possible implementation, S6 specifically includes:

[0078] S601: Substitute the pure imaginary eigenvalue that satisfies the Hopf bifurcation critical point in the characteristic equation into the characteristic equation to obtain the critical characteristic equation.

[0079] The critical characteristic equation is specifically:

[0080]

[0081] Where j represents the imaginary unit, Represents the angular frequency.

[0082] S602: Separation of the real and imaginary parts of the critical characteristic equation:

[0083] The real and imaginary parts separated are:

[0084]

[0085] in, and represent the real and imaginary parts of the critical characteristic equation, respectively.

[0086] S603: Combine the real part and the imaginary part to obtain the critical eigenvalue.

[0087] S604: Calculate the information entropy under the critical eigenvalue to obtain the eigenvalue information entropy stability threshold.

[0088] The calculation formula of the eigenvalue information entropy stability threshold is as follows:

[0089]

[0090]

[0091] in, represents the critical eigenvalue of the i-th dimension in the power grid performance parameters, represents the eigenvalue information entropy stability threshold, express The module length, and Respectively The real and imaginary parts of .

[0092] It should be noted that by substituting the purely imaginary eigenvalues at the Hopf bifurcation critical point into the characteristic equation, the critical characteristic equation is obtained, and its real and imaginary parts are further separated. By solving the critical eigenvalues, the turning point from stability to instability of the system can be identified. Next, by calculating the information entropy stability threshold of these critical eigenvalues, the critical value of system stability is derived. The calculation of the eigenvalue modulus and information entropy helps quantify the complexity and uncertainty of the system, thereby providing an objective threshold for evaluating the stability of the grid-connected electric vehicle charging and discharging station. Through Hopf bifurcation theory and eigenvalue analysis, the critical stability state of the system can be accurately identified, and the potential instability risk after the grid-connected charging and discharging station is predicted in advance, thereby enhancing the accuracy and reliability of system stability assessment.

[0093] S7: Combined with the eigenvalue information entropy stability threshold, determine whether the power grid performance parameters, the electric vehicle charging and discharging station performance parameters and the eigenvalue information entropy meet the joint stability conditions. If so, output that the electric vehicle charging and discharging station grid-connected performance is qualified; otherwise, output that the electric vehicle charging and discharging station grid-connected performance is unqualified.

[0094] It should be noted that by comprehensively considering grid performance parameters, EV charging and discharging station performance parameters, and eigenvalue information entropy, a multi-dimensional assessment method is provided to comprehensively determine the stability of the grid-connected system. This method not only ensures that the interaction between the grid and charging and discharging stations does not cause instability, but also promptly identifies potential risks, thereby avoiding system instability or failure, and improving the accuracy and reliability of grid-connected performance assessments.

[0095] In one possible implementation, the combined stability condition specifically includes:

[0096] The grid frequency deviation is less than the preset grid frequency deviation. The grid voltage deviation is less than the preset grid voltage deviation. The charge / discharge power is greater than the preset charge / discharge power. The battery temperature is less than the preset battery temperature. The eigenvalue information entropy is less than or equal to the eigenvalue information entropy stability threshold.

[0097] It should be noted that the combined stability condition comprehensively considers multiple key factors, including grid frequency, voltage, charge and discharge power, battery temperature, and eigenvalue information entropy. This allows for a comprehensive assessment of the stability of both the electric vehicle charging and discharging station and the grid, ensuring that the system does not exceed a preset safety threshold during operation, thereby effectively avoiding potential stability issues. Specifically, those skilled in the art may set the preset grid frequency deviation, preset grid voltage deviation, preset charge and discharge power, and preset battery temperature as needed, and this is not a limitation of the present invention.

[0098] In a possible implementation manner, after S7, the method further includes:

[0099] In the event that the grid connection performance of the electric vehicle charging and discharging station fails to meet the standards, an early warning will be issued.

[0100] It is understandable that in the event that the grid-connected performance of an electric vehicle charging and discharging station is unsatisfactory, timely early warning can help relevant personnel quickly identify and address potential problems, thereby preventing system instability or accidents and improving the safety and reliability of the power grid and charging and discharging stations.

[0101] In practical applications, by acquiring real-time performance parameters of the power grid and charging and discharging stations, a power interaction coupling model between the power grid and electric vehicle charging and discharging stations is established, nonlinear coupling effects are quantified, and system stability is assessed using eigenvalue information entropy. Stability thresholds are determined using Hopf bifurcation theory, and multi-dimensional stability conditions are combined to comprehensively assess the interconnection performance of the power grid and charging and discharging stations. This method accurately identifies potential instability risks, improving the accuracy and reliability of assessments, ensuring that the system does not exceed safety thresholds during the grid connection process, avoiding system instability or failure, and ensuring the stable operation of the power grid and charging and discharging stations.

[0102] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0103] In an embodiment of the present invention, the comprehensive evaluation method for the grid-connected performance of electric vehicle charging and discharging stations not only considers the normality of the operating parameters of the power station and the power grid, but also comprehensively quantifies the nonlinear coupling effects during the power station's charging and discharging process by establishing a power interaction coupling model between the power grid and the charging and discharging station, thereby accurately assessing the actual impact of the power station's grid connection on grid stability. In particular, the introduction of Hopf bifurcation theory and the concept of eigenvalue information entropy thresholds into the evaluation process enables the method to dynamically, comprehensively, and objectively reflect the stability and potential risks associated with the grid-connected electric vehicle charging and discharging station, thereby improving the accuracy and reliability of the evaluation results and effectively avoiding potential grid fluctuation risks.

[0104] Reference Manual Figure 2 , shows a structural schematic diagram of a comprehensive evaluation system for grid-connected performance of an electric vehicle charging and discharging station provided by an embodiment of the present invention.

[0105] The embodiment of the present invention provides a comprehensive evaluation system 20 for grid-connected performance of an electric vehicle charging and discharging station, comprising: a processor 201 and a memory 202;

[0106] The memory 202 stores programs or instructions that can be run on the processor 201. When the programs or instructions are executed by the processor 201, the steps of the above-mentioned electric vehicle charging and discharging station grid-connected performance comprehensive evaluation method are implemented, and the same technical effect can be achieved. To avoid repetition, the present invention will not be repeated.

[0107] It should be understood that the processor 201 in the embodiment of the present invention may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0108] It should also be understood that the memory 202 in the embodiments of the present invention may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0109] The above embodiments can be implemented in whole or in part via software, hardware (e.g., circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present invention are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0110] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0111] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0112] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0113] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of the device or unit, which can be electrical, mechanical or other forms.

[0114] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0115] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0116] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0117] An embodiment of the present invention provides a readable storage medium including: a program or instruction is stored on the readable storage medium, and when the program or instruction is executed by the processor, the steps of the above-mentioned comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station are implemented, and the same technical effect can be achieved. To avoid repetition, the present invention will not be repeated.

[0118] Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they may still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein with equivalents; and such modifications or replacements do not deviate from the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or replacements that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.

Claims

1. A comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station, characterized in that: include: S1: Obtain real-time grid performance parameters and electric vehicle charging and discharging station performance parameters; S2: establishing a power interaction coupling model between the power grid and the electric vehicle charging and discharging station according to the power grid performance parameters and the electric vehicle charging and discharging station performance parameters; S3: extracting a nonlinear coupling term from the power interaction coupling model, wherein the nonlinear coupling term is used to quantify the second-order nonlinear impact of the electric vehicle charging and discharging station performance parameter disturbance on the power grid; S4: integrating the power interaction coupling model and the nonlinear coupling term to establish a coupling state matrix describing the interaction state between the power grid and the electric vehicle charging and discharging station; S5: Calculate the eigenvalues of the coupling state matrix and calculate the eigenvalue information entropy; S6: Determine the eigenvalue information entropy stability threshold based on Hopf bifurcation theory; S7: In combination with the eigenvalue information entropy stability threshold, determine whether the power grid performance parameters, the electric vehicle charging and discharging station performance parameters and the eigenvalue information entropy meet the joint stability conditions. If so, output that the electric vehicle charging and discharging station grid-connected performance is qualified; otherwise, output that the electric vehicle charging and discharging station grid-connected performance is unqualified.

2. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 1, characterized in that: The grid performance parameters include grid frequency deviation and grid voltage deviation; the electric vehicle charging and discharging station performance parameters include charging and discharging power, battery state of charge in the electric vehicle charging and discharging station energy storage system, and battery temperature.

3. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 1, characterized in that: The power interaction coupling model is specifically: ； ； ； in, Indicates the grid frequency deviation, Indicates the grid voltage deviation, represents the grid load damping coefficient, represents the equivalent inertia time constant of the power grid, The active-voltage coupling coefficient that quantifies the indirect effect of active power on the grid voltage, represents the reactive-voltage regulation gain that controls the dynamic process of grid voltage recovery, represents the grid voltage regulation time constant, represents the random noise of the grid frequency at time t, represents the random noise of the grid voltage at time t, It represents the active power exchanged between the electric vehicle charging and discharging station and the power grid at time t, i.e., the charging and discharging power. Indicates the battery charge status of the electric vehicle charging and discharging station. Indicates the battery temperature of the electric vehicle charging and discharging station, It indicates the charging and discharging efficiency of electric vehicle charging and discharging station, that is, the ratio of actual power to nominal power. Indicates the rated capacity of the battery in the electric vehicle charging and discharging station. Indicates the thermal capacity of the battery in the electric vehicle charging and discharging station, Indicates the internal resistance of the battery in the electric vehicle charging and discharging station. Indicates the battery current of the electric vehicle charging and discharging station, The thermal time constant of the electric vehicle charging and discharging station that controls the temperature response speed, Indicates the ambient temperature, represents the active power exchanged between the internal grid interface of the electric vehicle charging and discharging station and the energy storage system of the electric vehicle charging and discharging station at time t, It represents the power conversion efficiency coefficient of the grid-connected inverter in discharge mode, Indicates the power conversion factor of the grid-connected inverter in charging mode.

4. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 1, characterized in that: The S3 specifically includes: S301: Expanding the electric power interaction coupling model into an infinite series through Volterra series; S302: Extracting the second-order term, ie, the nonlinear coupling term, from the infinite series.

5. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 1, characterized in that: The S5 specifically includes: S501: Establishing a characteristic equation of the coupling state matrix; S502: Solve the characteristic equation to obtain the characteristic value; S503: Calculate the eigenvalue information entropy using an information entropy algorithm.

6. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 5, characterized in that: The S6 specifically includes: S601: Substituting the pure imaginary eigenvalue that satisfies the Hopf bifurcation critical point in the characteristic equation into the characteristic equation to obtain the critical characteristic equation; S602: Separate the real part and the imaginary part of the critical characteristic equation; S603: Combining the real part and the imaginary part, solving to obtain a critical eigenvalue; S604: Calculate the information entropy under the critical eigenvalue to obtain the eigenvalue information entropy stability threshold.

7. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 1, characterized in that: The combined stability conditions specifically include: The grid frequency deviation is less than the preset grid frequency deviation; the grid voltage deviation is less than the preset grid voltage deviation; the charge and discharge power is greater than the preset charge and discharge power; the battery temperature is less than the preset battery temperature; the eigenvalue information entropy is less than or equal to the eigenvalue information entropy stability threshold.

8. The method for comprehensive evaluation of grid-connected performance of electric vehicle charging and discharging stations according to claim 7, characterized in that: After S7, the method further includes: In the event that the grid-connected performance of the electric vehicle charging and discharging station is unqualified, an early warning is issued.

9. A comprehensive evaluation system for the grid-connected performance of an electric vehicle charging and discharging station, characterized in that: include: processor and memory; The memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station are implemented as described in any one of claims 1 to 8.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the comprehensive evaluation method for the grid-connected performance of an electric vehicle charging and discharging station are implemented as described in any one of claims 1 to 8.

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