Power grid risk assessment method and system considering access of electric vehicle

Abstract

The application relates to the new energy technology field and provides a power grid risk assessment method and system considering electric vehicle access, which comprises the following steps: determining a probability density function corresponding to a harmonic voltage in a power grid based on a maximum entropy principle; evaluating a probability harmonic power flow in the power grid according to the probability density function to obtain a first risk probability; in the case that the first risk probability does not satisfy a preset safe operation condition, detecting current harmonic components of each access vehicle in the power grid; performing demixing analysis on the current harmonic components to obtain a plurality of harmonic contribution scores, wherein the harmonic contribution scores correspond to the access vehicles respectively; determining at least one target vehicle from the access vehicles according to the harmonic contribution scores; reducing a charging power corresponding to the target vehicle, and evaluating the probability harmonic power flow in the power grid to obtain a second risk probability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy, in particular to a power grid risk assessment method and system considering electric vehicle access. BACKGROUND

[0002] The harmonic pollution problem when the automobile is charging is very important. The high-order harmonics generated by the electric vehicle charging equipment can cause resonance in the power grid. For example, medium and high-order harmonics can cause local parallel resonance or series resonance in the distribution network, amplify the harmonic content, and cause additional losses in devices such as transformers and capacitors, resulting in overheating and insulation aging of the devices, thereby shortening the service life and even causing the burning of capacitors and other devices. It will also destroy the voltage and current waveform of the power grid, affect the stability and reliability of the power grid, and even may cause power safety accidents.

[0003] However, the existing power grid risk assessment method can only analyze the harmonics currently generated, and it is difficult to predict the changes of harmonics in the power grid, resulting in a lack of prevention of the risks caused by harmonics in the power grid. How to assess the risk of the power grid to effectively prevent the dangers that harmonics in the power grid may bring has become a problem to be solved. SUMMARY

[0004] The main purpose of the present application is to provide a power grid risk assessment method and system considering electric vehicle access, aiming to effectively evaluate and manage the harmonic voltage in the power grid and improve the safety of the power grid.

[0005] In a first aspect, the present application provides a power grid risk assessment method considering electric vehicle access, the method comprising the following steps:

[0006] Based on the maximum entropy principle, determine the probability density function corresponding to the harmonic voltage in the power grid;

[0007] According to the probability density function, the probability harmonic power flow in the power grid is evaluated to obtain a first risk probability;

[0008] In the case where the first risk probability does not satisfy the preset safe operation condition, detect the current harmonic component of each access vehicle in the power grid;

[0009] Perform demixing analysis on the current harmonic component to obtain a plurality of harmonic contribution scores, and the harmonic contribution scores correspond to each access vehicle respectively;

[0010] According to each harmonic contribution score, at least one target vehicle is determined from the access vehicles;

[0011] Reduce the charging power corresponding to the target vehicle, and evaluate the probability harmonic power flow in the power grid to obtain a second risk probability.

[0012] In some embodiments, the probability density function corresponding to the harmonic voltage in the power grid is determined based on a maximum entropy principle, and the determination comprises:

[0013] based on the following formula:

[0014]

[0015] determining the time when H(v) reaches the maximum value under the preset constraint condition wherein, is the probability density function, H(v) is an entropy function, is the starting time of the probability density function, is the ending time of the probability density function.

[0016] In some embodiments, the preset constraint condition comprises:

[0017]

[0018] wherein, is a preset weight function, is a statistical characteristic of the harmonic voltage, and the statistical characteristic comprises at least one of a mean value, a variance, and a central moment.

[0019] In some embodiments, the probability harmonic current in the power grid is evaluated according to the probability density function to obtain a first risk probability, and the evaluation comprises:

[0020]

[0021] wherein, is a preset threshold value, is a first risk probability of the harmonic voltage being greater than the preset threshold value.

[0022] In some embodiments, the current harmonic component is subjected to an unmixing analysis to obtain a plurality of harmonic contribution scores, and each harmonic contribution score corresponds to each access vehicle, and the unmixing analysis comprises:

[0023] preprocessing the current harmonic component to obtain a to-be-unmixed component, and obtaining a preset initial unmixing matrix;

[0024] iterating the initial unmixing matrix according to the to-be-unmixed component to obtain a target unmixing matrix;

[0025] determining the harmonic contribution score corresponding to each current harmonic component according to the target unmixing matrix.

[0026] In some embodiments, the current harmonic component is subjected to preprocessing to obtain a to-be-unmixed component, and a preset initial unmixing matrix is obtained, and the preprocessing comprises:

[0027] ​​​determining a center harmonic component according to a difference between an average harmonic component of the current harmonic components and each of the current harmonic components;

[0028] whitening each of the center harmonic components according to the following formula to obtain the to-be-unmixed component:

[0029]

[0030] wherein, V and Λ are eigenvectors and eigenvalues of a covariance matrix of the current harmonic components, respectively.

[0031] In some embodiments, the iteration of the initial unmixed matrix according to the to-be-unmixed component to obtain a target unmixed matrix comprises:

[0032] unmixing the to-be-unmixed component based on the initial unmixed matrix to obtain a plurality of to-be-verified components;

[0033] mixing each of the to-be-verified components to obtain a to-be-verified total amount;

[0034] adjusting the initial unmixed matrix according to the to-be-verified total amount and a current harmonic total amount in the power grid until the target unmixed matrix is obtained.

[0035] In some embodiments, the determination of a harmonic contribution score corresponding to each current harmonic component according to the target unmixed matrix comprises:

[0036] unmixing analysis of the current harmonic component to obtain an independent component matrix corresponding to the current harmonic component;

[0037] determination of the harmonic contribution score of the access vehicle according to the independent component matrix.

[0038] In some embodiments, the determination of at least one target vehicle from the access vehicles according to each of the harmonic contribution scores comprises:

[0039] ranking each of the access vehicles according to the harmonic contribution score, and determining the access vehicles ranked in the top n positions as the target vehicles;

[0040] the reduction of the charging power corresponding to the target vehicles comprises:

[0041] detection of a remaining amount of electricity of each of the target vehicles, and ranking of the target vehicles according to the remaining amount of electricity;

[0042] determination of an electricity level corresponding to each target vehicle according to a ranking order of the target vehicles;

[0043] ​​Determine a charging power reduction amount of each target vehicle according to the power level.

[0044] In a second aspect, the present application also provides a power grid risk assessment system considering electric vehicle access, comprising:

[0045] A probability density function determination module is configured to determine a probability density function corresponding to harmonic voltage in the power grid based on the maximum entropy principle.

[0046] A first risk assessment module is configured to assess the probabilistic harmonic power flow in the power grid according to the probability density function, and obtain a first risk probability.

[0047] A harmonic component detection module is configured to detect the current harmonic component of each access vehicle in the power grid if the first risk probability does not meet the preset safe operation condition.

[0048] A contribution score calculation module is configured to perform unmixing analysis on the current harmonic component, and obtain a plurality of harmonic contribution scores, each of which corresponds to an access vehicle.

[0049] A target vehicle determination module is configured to determine at least one target vehicle from the access vehicles according to each harmonic contribution score.

[0050] A second risk assessment module is configured to reduce the charging power corresponding to the target vehicle, and assess the probabilistic harmonic power flow in the power grid, and obtain a second risk probability.

[0051] The present application provides a power grid risk assessment method and system considering electric vehicle access. The present application determines a probability density function corresponding to harmonic voltage in the power grid based on the maximum entropy principle, assesses the probabilistic harmonic power flow in the power grid according to the probability density function, and obtains a first risk probability. If the first risk probability does not meet the preset safe operation condition, the current harmonic component of each access vehicle in the power grid is detected. Unmixing analysis is performed on the current harmonic component, and a plurality of harmonic contribution scores are obtained, each of which corresponds to an access vehicle. At least one target vehicle is determined from the access vehicles according to each harmonic contribution score. The charging power corresponding to the target vehicle is reduced, and the probabilistic harmonic power flow in the power grid is assessed, and a second risk probability is obtained. The harmonic voltage in the power grid can be effectively evaluated and managed, and the safety of the power grid is improved. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed in the embodiment description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 A flowchart of a power grid risk assessment method considering access of electric vehicles is provided for an embodiment of the present application.

[0054] Figure 2 A schematic block diagram of a power grid risk assessment system considering access of electric vehicles is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0056] The flowchart shown in the drawings is only an example and does not necessarily include all the contents and operations / steps, nor does it necessarily execute in the order described. For example, some operations / steps can be decomposed, combined or partially merged, so the actual execution order may be changed according to the actual situation.

[0057] The embodiments of the present application provide a power grid risk assessment method and system considering access of electric vehicles.

[0058] The following will describe some embodiments of the present application in detail with reference to the drawings. In the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0059] Please refer to Figure 1 , Figure 1 A flowchart of a power grid risk assessment method considering access of electric vehicles is provided for an embodiment of the present application. The power grid risk assessment method considering access of electric vehicles can be used in a terminal or a server. The terminal can be an electronic device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant and a wearable device. The server can be a standalone server, a server cluster, a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0060] As Figure 1 shown, the power grid risk assessment method and system considering access of electric vehicles includes steps S101 to S106.

[0061] Step S101, based on the maximum entropy principle, determine the probability density function corresponding to the harmonic voltage in the power grid.

[0062] The harmonic voltage in the power grid will change due to the existence of nonlinear loads such as frequency converters, rectifiers, UPS, etc., and environmental factors and load changes will also cause changes in harmonic voltage. However, the change of harmonic voltage has a certain probability distribution. In order to avoid subjective assumptions about the probability distribution of harmonic voltage, and to obtain a more objective and accurate probability density function, the probability density function corresponding to the harmonic voltage in the power grid can be determined based on the maximum entropy principle.

[0063] In some embodiments, the probability density function corresponding to the harmonic voltage in the power grid is determined based on the maximum entropy principle, including:

[0064] Based on the following formula:

[0065]

[0066] Determine the probability density function when the entropy function H(v) reaches the maximum value under the preset constraint condition , wherein is the probability density function, H(v) is the entropy function, is the starting time of the probability density function, is the end time of the probability density function.

[0067] For example, the core of the maximum entropy principle is to maximize the information entropy of the random variable under the condition of satisfying the known information constraint, so as to obtain the probability distribution most consistent with the actual situation. Therefore, the probability density function when the entropy function H(v) reaches the maximum value under the preset constraint condition is determined , to obtain the probability density function of the harmonic voltage most consistent with the actual situation, wherein v represents the voltage size in the power grid.

[0068] For example, the probability density function can be divided into several time windows, is the starting time of the probability density function corresponding to the time window, is the end time of the probability density function corresponding to the time window.

[0069] Among them, the maximum value of the function can be determined by solving the Lagrange function, of course, not limited to this, not limited here.

[0070] In some embodiments, the preset constraint condition comprises:

[0071]

[0072] wherein is a preset weight function, is a statistical feature of the harmonic voltage, the statistical feature comprising at least one of a mean, a variance, and a central moment.

[0073] For example, the weight function can be so as to describe the statistical features such as the mean, the variance, and the central moment; or the weight function can also be so as to correspond to the frequency characteristics of the harmonic voltage. respectively represent statistical features of 1, 2, …, m historical harmonic voltage data.

[0074] For example, the historical harmonic voltage data comprises at least one of a voltage actually detected in the power grid at a historical time and a harmonic voltage in the power grid at a corresponding time.

[0075] In step S102, the probabilistic harmonic power flow in the power grid is evaluated according to the probability density function, to obtain a first risk probability.

[0076] For example, the probabilistic harmonic power flow in the power grid can be evaluated according to the probability density function to obtain the first risk probability, the probabilistic harmonic power flow being greater than a certain preset threshold. The size of the preset threshold can be set according to actual requirements. Specifically, different preset thresholds, such as a high-risk threshold and a low-risk threshold, can be set to respectively give early warnings of different degrees of risk.

[0077] In some embodiments, the evaluating the probabilistic harmonic power flow in the power grid according to the probability density function to obtain the first risk probability comprises:

[0078]

[0079] wherein is a preset threshold, is a first risk probability of the harmonic voltage being greater than the preset threshold.

[0080] For example, the probability of the harmonic voltage being greater than the preset threshold can be determined by integrating the probability density function of the harmonic voltage within a certain integral range. Specifically, the preset threshold is taken as the starting point of integration, and the integral value of the probability density function of the harmonic voltage within the range from to infinity is determined.

[0081] Step S103, in the case that the first risk probability does not satisfy the preset safe operation condition, detecting a current harmonic component of each access vehicle in the power grid.

[0082] For example, the preset safe operation condition can be that the first risk probability is less than or equal to a preset probability threshold, which can be 95% for example.

[0083] In the case that the first risk probability does not satisfy the preset safe operation condition, the harmonic voltage in the power grid needs to be reduced by reducing the charging power of the access vehicle to avoid damage to the power grid and the equipment in the power grid caused by the harmonic. In order to determine which access vehicle to reduce the charging power, the current harmonic component of each access vehicle needs to be detected.

[0084] Step S104, performing demixing analysis on the current harmonic component to obtain a plurality of harmonic contribution scores, the harmonic contribution scores corresponding to each access vehicle respectively.

[0085] For example, however, since the current harmonic component detected in the power grid has been affected by the background harmonic in the power grid and other access vehicles, further demixing analysis needs to be performed on the current harmonic component to determine the contribution size of each access vehicle to the harmonic voltage in the power grid.

[0086] In some embodiments, the demixing analysis on the current harmonic component to obtain a plurality of harmonic contribution scores, the harmonic contribution scores corresponding to each access vehicle respectively, comprises:

[0087] preprocessing the current harmonic component to obtain a to-be-demixed component, and obtaining a preset initial demixing matrix;

[0088] iterating the initial demixing matrix according to the to-be-demixed component to obtain a target demixing matrix;

[0089] determining the harmonic contribution score corresponding to each current harmonic component according to the target demixing matrix.

[0090] For example, the demixing matrix can be used to demix each current harmonic component to determine the harmonic contribution score corresponding to each current harmonic component. The target demixing matrix used to determine the harmonic contribution score can be determined by iteration. Specifically, the to-be-demixed component is demixed according to the preset initial demixing matrix, and then the initial demixing matrix is iterated according to the demixing result until the target demixing matrix is obtained.

[0091] In some embodiments, the preprocessing of the current harmonic component to obtain a to-be-demixed component, and obtaining a preset initial demixing matrix, comprises:

[0092] determining a center harmonic component according to a difference between the average harmonic component and each of the current harmonic components;

[0093] whitening each of the center harmonic components according to the following formula to obtain the to-be-unmixed component:

[0094]

[0095] wherein, the center harmonic component, V and Λ are eigenvectors and eigenvalues of a covariance matrix of the current harmonic component, respectively.

[0096] Exemplarily, before determining the target unmixed matrix, the current harmonic component needs to be pre-processed, including centering and whitening, to improve the convergence speed of the unmixed matrix iteration.

[0097] subtracting the average harmonic component from each of the current harmonic components to center the current harmonic component to obtain the center harmonic component , and then whitening the center harmonic component according to the eigenvectors and eigenvalues of the covariance matrix of the current harmonic component to obtain the whitened to-be-unmixed component .

[0098] In some embodiments, the iteration of the initial unmixed matrix according to the to-be-unmixed component to obtain the target unmixed matrix comprises:

[0099] unmixing the to-be-unmixed component based on the initial unmixed matrix to obtain a plurality of to-be-verified components;

[0100] mixing each of the to-be-verified components to obtain a to-be-verified total amount;

[0101] adjusting the initial unmixed matrix according to the to-be-verified total amount and the current harmonic total amount in the power grid until the target unmixed matrix is obtained.

[0102] Exemplarily, the to-be-unmixed component is unmixed by the initial unmixed matrix, and then the plurality of to-be-verified components obtained are mixed to obtain the to-be-verified total amount. The to-be-verified total amount is compared with the current harmonic total amount actually detected in the power grid, and the initial unmixed matrix is adjusted according to the comparison result, so as to iterate the initial unmixed matrix until the target unmixed matrix capable of effectively unmixing the to-be-unmixed component is obtained.

[0103] In some embodiments, the determination of the harmonic contribution score corresponding to each of the current harmonic components according to the target unmixed matrix comprises:

[0104] unmixing analysis of the current harmonic component to obtain an independent component matrix corresponding to the current harmonic component;

[0105] determining a harmonic contribution score of the access vehicle according to the independent component matrix.

[0106] Exemplarily, the voltage of the independent component matrix is divided by the voltage of the current total harmonic, to obtain the harmonic contribution score of the access vehicle corresponding to the independent component matrix, so as to quantify the contribution of each access vehicle to the harmonic voltage, so as to reduce the charging power of the access vehicle with a large harmonic contribution score.

[0107] Step S105, determining at least one target vehicle from the access vehicles according to the harmonic contribution scores.

[0108] Exemplarily, the access vehicle with a large harmonic contribution score is determined as the target vehicle which needs to reduce the charging power.

[0109] In some embodiments, the determining at least one target vehicle from the access vehicles according to the harmonic contribution scores comprises:

[0110] sequencing the access vehicles according to the harmonic contribution scores, and determining the access vehicles ranked in the top n positions as the target vehicles.

[0111] Exemplarily, the access vehicle with a harmonic contribution score greater than a preset score can be determined as the target vehicle, or the access vehicle ranked in the top n positions can be determined as the target vehicle.

[0112] Step S106, reducing the charging power corresponding to the target vehicle, and evaluating the probabilistic harmonic power flow in the power grid to obtain a second risk probability.

[0113] Exemplarily, after reducing the charging power of the target vehicle, the probabilistic harmonic power flow is evaluated again to ensure that the second risk probability is reduced to a safe level.

[0114] In some embodiments, the reducing the charging power corresponding to the target vehicle comprises:

[0115] detecting the remaining power of each target vehicle, and sequencing the target vehicles according to the remaining power;

[0116] determining the power level corresponding to each target vehicle according to the sequencing order of the target vehicles;

[0117] determining the charging power reduction amount of each target vehicle according to the power level.

[0118] For example, as the vehicle power increases during the charging process, in order to increase the battery life, the charging power can be reduced when the battery power is relatively high. Therefore, in the target vehicle, the charging power of the vehicle with more remaining power is preferentially reduced. The target vehicles can be sorted according to the remaining power, and the power level of each target vehicle is determined according to the sorting order.

[0119] For example, if the number of target vehicles is 50, the top 10 target vehicles in the order can be determined as the first level, the target vehicles ranked 10-20 can be determined as the second level, and so on, and the charging power of the target vehicles in the first level is reduced by 60%, the charging power of the target vehicles in the second level is reduced by 50%, and so on.

[0120] The above embodiment provides a power grid risk assessment method considering electric vehicle access. The probability density function corresponding to the harmonic voltage in the power grid is determined based on the maximum entropy principle. The first risk probability is obtained by evaluating the probabilistic harmonic power flow in the power grid according to the probability density function. In the case that the first risk probability does not satisfy the preset safe operation condition, the current harmonic component of each access vehicle in the power grid is detected. The harmonic contribution score is obtained by demixing analysis of the current harmonic component. The harmonic contribution score corresponds to each access vehicle. At least one target vehicle is determined from the access vehicles according to the harmonic contribution score. The charging power corresponding to the target vehicle is reduced, and the second risk probability is obtained by evaluating the probabilistic harmonic power flow in the power grid. The harmonic voltage in the power grid can be effectively evaluated and managed, and the safety of the power grid is improved.

[0121] Please refer to Figure 2 , Figure 2 The embodiment of the present application provides a power grid risk assessment system considering electric vehicle access. The power grid risk assessment system considering electric vehicle access can be configured in a server or a terminal, and is used for executing the power grid risk assessment method considering electric vehicle access.

[0122] As Figure 2 shown, the power grid risk assessment device considering electric vehicle access includes a probability density function determination module 110, a first risk assessment module 120, a harmonic component detection module 130, a contribution score calculation module 140, a target vehicle determination module 150, and a second risk assessment module 160.

[0123] The probability density function determination module 110 is configured to determine the probability density function corresponding to the harmonic voltage in the power grid based on the maximum entropy principle.

[0124] The first risk assessment module 120 is configured to evaluate the probabilistic harmonic power flow in the power grid according to the probability density function, and obtain the first risk probability.

[0125] The harmonic component detection module 130 is used to detect the current harmonic components of each connected vehicle in the power grid when the first risk probability does not meet the preset safe operation conditions.

[0126] The contribution score calculation module 140 is used to perform unmixing analysis on the current harmonic component to obtain multiple harmonic contribution scores, which are respectively associated with each access vehicle.

[0127] The target vehicle determination module 150 is used to determine at least one target vehicle from the access vehicles based on the harmonic contribution scores of each of the aforementioned vehicles.

[0128] The second risk assessment module 160 is used to reduce the charging power corresponding to the target vehicle and assess the probabilistic harmonic power flow in the power grid to obtain a second risk probability.

[0129] In some embodiments, the probability density function determination module 110, in the process of determining the probability density function corresponding to the harmonic voltage in the power grid based on the maximum entropy principle, is used to:

[0130] Based on the following formula:

[0131]

[0132] Determine when H(v) reaches its maximum value under preset constraints. ,in, Let H(v) be the probability density function, and H(v) be the entropy function. At the starting time of the probability density function, The endpoint of the probability density function is given.

[0133] In some embodiments, the preset constraints include:

[0134]

[0135] in For the pre-defined weight function, The statistical characteristics of harmonic voltage include at least one of mean, variance, and central moment.

[0136] In some embodiments, the first risk assessment module 120, in the process of assessing the probabilistic harmonic power flow in the power grid according to the probability density function to obtain the first risk probability, is used to:

[0137]

[0138] in, For the preset threshold, a first risk probability that the harmonic voltage is greater than the preset threshold value.

[0139] In some embodiments, the contribution score calculation module 140, in implementing the demixing analysis on the current harmonic component, obtains a plurality of harmonic contribution scores corresponding to respective access vehicles, for implementing:

[0140] preprocessing the current harmonic component to obtain a to-be-demixed component, and obtaining a preset initial demixing matrix;

[0141] iterating the initial demixing matrix according to the to-be-demixed component to obtain a target demixing matrix;

[0142] determining a harmonic contribution score corresponding to each current harmonic component according to the target demixing matrix.

[0143] In some embodiments, the contribution score calculation module 140, in implementing the preprocessing of the current harmonic component to obtain a to-be-demixed component, and obtaining a preset initial demixing matrix, is configured to implement:

[0144] determining a center harmonic component according to a difference between an average harmonic component of the current harmonic component and each of the current harmonic components;

[0145] whitening each of the center harmonic components according to the following formula to obtain the to-be-demixed component:

[0146]

[0147] wherein, the center harmonic component, V and Λ are respectively an eigenvector and an eigenvalue of a covariance matrix of the current harmonic component.

[0148] In some embodiments, the contribution score calculation module 140, in implementing the iteration of the initial demixing matrix according to the to-be-demixed component to obtain a target demixing matrix, is configured to implement:

[0149] demixing the to-be-demixed component based on the initial demixing matrix to obtain a plurality of to-be-verified components;

[0150] mixing each of the to-be-verified components to obtain a to-be-verified total amount;

[0151] adjusting the initial demixing matrix according to the to-be-verified total amount and a current harmonic total amount in the power grid until the target demixing matrix is obtained.

[0152] In some embodiments, the contribution score calculation module 140, in implementing the process of determining the harmonic contribution score corresponding to each current harmonic component according to the target demixing matrix, is configured to:

[0153] performing demixing analysis on the current harmonic component to obtain an independent component matrix corresponding to the current harmonic component;

[0154] determining the harmonic contribution score of the access vehicle according to the independent component matrix.

[0155] In some embodiments, the target vehicle determination module, in implementing the process of determining at least one target vehicle from the access vehicles according to the harmonic contribution scores, is configured to:

[0156] ranking the access vehicles according to the harmonic contribution scores, and determining the top n access vehicles as the target vehicles.

[0157] In some embodiments, the second risk assessment module 160, in implementing the process of reducing the charging power corresponding to the target vehicles, is configured to:

[0158] detecting the residual power of each target vehicle, and ranking the target vehicles according to the residual power;

[0159] determining the power level corresponding to each target vehicle according to the ranking order of the target vehicles;

[0160] determining the charging power reduction amount of each target vehicle according to the power level.

[0161] It should be noted that, for the convenience and brevity of description, the above description considers the specific working process of the power grid risk assessment system for electric vehicle access, which can be referred to the corresponding process in the foregoing embodiments of the power grid risk assessment method for electric vehicle access, and will not be described here.

[0162] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program, and the computer program includes program instructions. The method implemented by the program instructions can refer to the embodiments of the power grid risk assessment method for electric vehicle access.

[0163] The computer readable storage medium can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like.

[0164] It should be understood that the terminology used herein in the specification and the appended claims is for the purpose of describing particular embodiments only and is not intended to be limiting, as the scope of the present application will be limited only by the appended claims. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0165] It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items, and that the term "at least one of" followed by a list of two or more items means any single one of the items in the list, and that the term "one or more of" followed by a list of two or more items means any single one or plurality of the items in the list. It should be further understood that the terms "comprise" "include" or "comprising" or "including" when used in this specification and in the following claims, specify the presence of stated features, integers, steps, operations, elements, or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or groups thereof.

[0166] The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent advantages or disadvantages of the embodiments. The above describes only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for risk assessment of a power grid considering access of electric vehicles, characterized in that, The method comprises: determining a probability density function corresponding to a harmonic voltage in a power grid based on a maximum entropy principle; evaluating a probabilistic harmonic power flow in the power grid according to the probability density function to obtain a first risk probability; in a case where the first risk probability does not satisfy a preset safe operation condition, detecting current harmonic components of each vehicle accessing the power grid; preprocessing the current harmonic components to obtain to-be-unmixed components, and obtaining a preset initial unmixed matrix; iteratively processing the to-be-unmixed components on the initial unmixed matrix to obtain a target unmixed matrix; determining a harmonic contribution score corresponding to each current harmonic component according to the target unmixed matrix; performing unmixed analysis on the current harmonic components to obtain an independent component matrix corresponding to the current harmonic components; and determining a harmonic contribution score of the vehicle accessing the power grid according to the independent component matrix, the harmonic contribution score corresponding to each vehicle accessing the power grid; determining at least one target vehicle from the vehicles accessing the power grid according to the harmonic contribution scores; reducing a charging power corresponding to the target vehicle, and evaluating the probabilistic harmonic power flow in the power grid to obtain a second risk probability.

2. The method of risk assessment of power grid considering access of electric vehicles according to claim 1, characterized in that, The method comprises: determining a probability density function corresponding to a harmonic voltage in a power grid based on a maximum entropy principle; ， determining a time when H(v) reaches a maximum value under preset constraints wherein, is the probability density function, H(v) is an entropy function, is a start time of the probability density function, is an end time of the probability density function.

3. The method of risk assessment of power grid considering access of electric vehicles according to claim 2, characterized in that, The preset constraint condition comprises: ， wherein is a pre-set weight function, is a statistical feature of the harmonic voltage, the statistical feature comprising at least one of a mean, a variance, a central moment.

4. The method of risk assessment of power grid considering access of electric vehicles according to claim 1, characterized in that, The method comprises: ， wherein, is a predetermined threshold value, is a first risk probability that the harmonic voltage is greater than the predetermined threshold value.

5. The method for risk assessment of power grid considering access of electric vehicles according to claim 1, characterized in that, The method comprises: determining a center harmonic component according to a difference between an average harmonic component of the current harmonic components and each of the current harmonic components; performing whitening processing on each of the center harmonic components according to the following formula to obtain the to-be-unmixed components: ， wherein, denotes the central harmonic component, V and Λ are respectively the eigenvectors and eigenvalues of the covariance matrix of the current harmonic component.

6. The method of risk assessment of power grid considering access of electric vehicles according to claim 1, characterized in that, The method comprises: performing unmixed processing on the to-be-unmixed components based on the initial unmixed matrix to obtain a plurality of to-be-verified components; mixing each of the to-be-verified components to obtain a to-be-verified total amount; adjusting the initial unmixed matrix according to the to-be-verified total amount and a current harmonic total amount in the power grid until the target unmixed matrix is obtained.

7. The method of risk assessment of power grid considering access of electric vehicles according to claim 1, characterized in that, The method comprises: sorting each of the vehicles accessing the power grid according to the harmonic contribution scores, and determining the vehicles ranking in the top n positions as the target vehicles; The method comprises: detecting a residual amount of electricity of each of the target vehicles, and sorting the target vehicles according to the residual amount of electricity; determining an electricity level corresponding to each of the target vehicles according to a sorting order of the target vehicles; determining a charging power reduction amount of each of the target vehicles according to the electricity level.

8. A power grid risk assessment system considering electric vehicle access, characterized in that The system comprises: a probability density function determination module configured to determine a probability density function corresponding to a harmonic voltage in a power grid based on a maximum entropy principle; a first risk evaluation module configured to evaluate a probabilistic harmonic power flow in the power grid according to the probability density function to obtain a first risk probability; a harmonic component detection module, configured to detect current harmonic components of each of the access vehicles in the power grid when the first risk probability does not satisfy the preset safe operation condition; a contribution score calculation module, configured to: perform preprocessing on the current harmonic components to obtain to-be-unmixed components, and obtain a preset initial unmixed matrix; perform iteration on the initial unmixed matrix according to the to-be-unmixed components to obtain a target unmixed matrix; determine harmonic contribution scores corresponding to each of the current harmonic components according to the target unmixed matrix; perform unmixed analysis on the current harmonic components to obtain an independent component matrix corresponding to the current harmonic components; and determine the harmonic contribution scores of the access vehicles according to the independent component matrix, wherein the harmonic contribution scores correspond to the access vehicles respectively; a target vehicle determination module, configured to determine at least one target vehicle from the access vehicles according to the harmonic contribution scores; a second risk assessment module, configured to reduce a charging power corresponding to the target vehicle, and to assess a probabilistic harmonic power flow in the power grid to obtain a second risk probability.

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