Optimization management method of transformer area flexible interconnection system based on fault self-healing capability

Abstract

The invention provides a transformer area flexible interconnection system optimization management method based on fault self-healing capability, and the method comprises the steps: carrying out the following self-healing strategies through a transformer area flexible interconnection system fault self-healing model: calculating the energy storage state of an energy storage system through an optimal power flow algorithm in a grid-connected mode before network disconnection, and charging the energy storage system, running in an island mode; when the fault of the main network is detected, the power supply time of the key load is maximized by using the source load storage resources, and optimal scheduling is carried out according to the current operation state; and after the transformer area flexible interconnection system enters the island mode, non-critical load removal is executed, and power supply of critical loads is guaranteed preferentially.

Description

Technical Field

[0001] The present invention belongs to the technical field of fault self-healing of a transformer area interconnection system, and in particular relates to an optimization management method of a transformer area flexible interconnection system based on fault self-healing capability. Background Art

[0002] With the adjustment of energy structure and the rapid growth of electricity demand, modern power systems are facing unprecedented challenges. Due to its single power structure, the traditional AC power grid has limited recovery ability when encountering faults, and it is difficult to respond quickly and restore power supply. In recent years, with the widespread application of new energy technologies such as renewable energy and electric vehicles, the flexible interconnection system of substations has gradually become a key solution to improve the stability of the power grid and the reliability of power supply.

[0003] However, the existing technology still has some significant deficiencies in practical applications. First, although the flexible interconnection system of the substation area can maintain partial power supply by cutting off non-critical loads in the event of a fault, due to the uncertainty of renewable energy and the capacity limitation of the energy storage system, the self-healing ability of the system is still insufficient and cannot effectively cope with complex fault scenarios. The current technology lacks a systematic optimization and scheduling mechanism, which makes it difficult to fully realize the potential of energy storage equipment, especially in different energy scenarios, and it is difficult to ensure the efficient operation of the flexible interconnection system of the substation area. In addition, there are many deficiencies in the management of flexible resources. As a key flexible resource, the energy storage system has not been fully utilized, especially in the island mode. How to efficiently manage these resources to ensure the power supply of critical loads is a major challenge facing current technology. At the same time, the capacity planning and charging and discharging strategies of the energy storage system also need to be further optimized to meet the needs of island operation after a power grid failure.

[0004] The uncertainty of renewable energy is also a difficulty in existing technologies. The power generation of solar and wind energy fluctuates greatly due to environmental factors. The existing load balancing and power scheduling methods are insufficient in dealing with this volatility, which not only affects the operational efficiency in the grid-connected mode, but also increases the risk of power outages in the island mode. Therefore, how to optimize the use of renewable energy under uncertain conditions has become an urgent problem to be solved in the flexible interconnection system of the substation area.

[0005] The future flexible interconnection system of substations needs to make breakthroughs in many aspects. First, the self-healing ability of the flexible interconnection system of substations should be improved, relying on more advanced fault detection, isolation technology and load management strategies to ensure that the system can quickly restore the power supply of critical loads after a fault occurs. Secondly, the intelligent scheduling of flexible resources such as energy storage systems should be strengthened. Through intelligent charging and discharging management, the system can better cope with sudden failures and improve energy utilization efficiency while ensuring power supply stability. In addition, more accurate load prediction models and power generation optimization strategies must be developed to cope with the uncertainty of renewable energy generation, so as to maintain efficient and stable operation of the system under different energy scenarios.

[0006] In general, the development of flexible interconnection system technology requires in-depth research and improvement in self-healing capabilities, flexible resource management, and optimal utilization of renewable energy to meet the future power system's needs for more efficient and reliable power supply. Summary of the invention

[0007] In order to solve the problems existing in the above-mentioned prior art and meet higher requirements of the power system, the present invention provides an optimization management method for a flexible interconnection system of a substation based on fault self-healing capability, which has the characteristics of high power supply restoration reliability and more stable operation. It overcomes the shortcomings of poor power supply reliability, limited recovery capability and uncertainty of renewable energy power generation of existing traditional AC power grids, meets the power supply stability while improving energy utilization efficiency.

[0008] The scheme of the present invention is constructed by acquiring historical power data of distributed photovoltaic, wind turbine and energy storage systems of the flexible interconnected system of the substation, building a power model, generating a normal operation scenario library based on the m-ISODATA method through Monte Carlo simulation, and then selecting fault scenarios through random number comparison to extract the fault scenario library; traversing the fault scenario library, building a self-healing model of the flexible interconnected system of the substation, using CPLEX to solve the model, and obtaining input parameters such as the load recovery rate under each fault scenario, thereby realizing the power scheduling of loads and distributed power sources under various fault scenarios of the flexible interconnected system of the substation.

[0009] The present invention further obtains the power dispatch results of the flexible interconnection system in the fault scenario, calculates various self-healing indicators, and evaluates the self-healing ability of the system to prove the effect and advantages of this solution. The present invention is applicable to the flexible interconnection system in the substation area, which can ensure the power supply of key loads when the power grid is out of power, and provide an efficient and intelligent self-healing management solution for the flexible interconnection system in the future substation area.

[0010] The technical solution specifically adopted by the present invention to solve the technical problem is:

[0011] An optimization management method for a flexible interconnection system in a transformer area based on fault self-healing capability:

[0012] The following self-healing strategies are implemented through the fault self-healing model of the flexible interconnection system in the substation area:

[0013] In the grid-connected mode before the grid is disconnected, the energy storage system's energy storage status is calculated through the optimal power flow algorithm, and the energy storage system is charged to prepare for operation in the island mode. When a main grid fault is detected, the source-load-storage resources are used to maximize the power supply time of key loads, and optimal scheduling is performed according to the current operating status.

[0014] When the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to give priority to power supply to critical loads.

[0015] The above critical loads and non-critical loads are set and marked through the power grid system.

[0016] Furthermore, the goal of the fault self-healing model of the flexible interconnected system in the substation is to maximize the power supply time of the critical load; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of the source, load and storage resources after the power outage;

[0017] The fault self-healing model satisfies both power balance constraints and energy storage system constraints;

[0018] The power balance constraint is:

[0019]

[0020] Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time;

[0021] The energy storage system constraints are:

[0022]

[0023] Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system;

[0024] The energy storage system should also meet the non-simultaneity of charging and discharging operations:

[0025]

[0026] In the formula, and Indicates the charging and discharging status of the energy storage system.

[0027] Furthermore, the method for generating the optimal scheduling solution comprises the following steps:

[0028] Firstly, the historical operating power data of the distributed photovoltaic, wind turbine and energy storage system connected to the flexible interconnection system of the substation are obtained, and the operating power model is constructed. The power generation probability models of photovoltaic and wind turbine are fitted based on the normal distribution function and Weibull distribution respectively. Through Monte Carlo simulation random sampling, the normal operation scenario library of the flexible interconnection system of the substation based on the m-ISODATA method is generated. On this basis, the fault scenarios are selected by random number comparison method to extract the fault scenario library. Then, the fault scenarios at each moment in the fault scenario library are traversed to construct the fault self-healing model of the flexible interconnection system of the substation. The fault self-healing model is solved by the CPLEX solver to obtain the optimal power curve of the flexible load and distributed power source, and the input parameters including the load recovery rate and the power data of photovoltaic and wind turbine under each fault scenario of the flexible interconnection system of the substation, as well as the charging and discharging status of the energy storage system are obtained to execute the power dispatch of the load and distributed power source under each fault scenario of the flexible interconnection system of the substation.

[0029] Furthermore, the specific steps of generating the normal operation scenario library of the substation flexible interconnection system based on the m-ISODATA method are as follows:

[0030] Acquire data including at least: photovoltaic and wind turbine power generation, load demand, fault information, and charging and discharging status of energy storage systems; represent historical data as a multidimensional data set X, where each row corresponds to the status at a moment, and contains multiple different dimensions;

[0031]

[0032] Among them, x i represents the data point at the i-th time point, and d is the dimension of the data;

[0033] Then the following iterative process is performed:

[0034] a. Perform clustering according to the Euclidean distance formula and assign each data point to the nearest cluster centroid:

[0035] d(x i ,μ c )=||x i -μ c ||

[0036] Among them, μ c is the centroid of the cth cluster, x iis an arbitrary data point;

[0037] Data points are assigned to the nearest centroid:

[0038]

[0039] b. When the centroid is updated, the centroid is recalculated based on the data points newly assigned to the cluster:

[0040]

[0041] c. If the standard deviation of a cluster exceeds the preset σ max , then perform the split operation:

[0042] λ δ,δ is the eigenvalue of the covariance matrix of cluster c

[0043] When σ c >σ max When , the centroids are split along the principal axes of the covariance matrix:

[0044]

[0045] where λ c It is the largest eigenvector in the covariance matrix, indicating the main expansion direction of the data;

[0046] d. If the distance between the two cluster centroids is less than the preset minimum distance d min , then merge these two clusters:

[0047] d(μ a ,μ b )=||μ a -μ b ||<d min

[0048] The new centroid position after merging is:

[0049]

[0050] e. The iteration terminates when any of the following conditions is met: the preset maximum number of iterations is reached, the split and merge operations no longer change the clusters, or the number of clusters oscillates between two values;

[0051] f. Each cluster centroid finally represents an operation scenario, and the probability of occurrence corresponding to each scenario is the proportion of data points in the cluster:

[0052]

[0053] where |X c| is the number of data points belonging to scene S, and n is the total number of data points.

[0054] Furthermore, the construction process of the fault self-healing model of the substation flexible interconnection system specifically includes:

[0055] The goal of the fault self-healing model is to maximize the power supply time of critical loads; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of source, load and storage resources after power outage;

[0056] The fault self-healing model satisfies both power balance constraints and energy storage system constraints;

[0057] The power balance constraint is:

[0058]

[0059] Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time;

[0060] The energy storage system constraints are:

[0061]

[0062] Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system;

[0063] The energy storage system should also meet the non-simultaneity of charging and discharging operations:

[0064]

[0065] In the formula, and Indicates the charging and discharging status of the energy storage system;

[0066] The self-healing strategy is set as follows: when the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to prioritize the power supply of critical loads; in the grid-connected mode before the grid disconnection, the model calculates the energy storage state of the energy storage system through the optimal power flow algorithm, and charges the energy storage system in preparation for operation in the island mode; when a main grid fault is detected, the system uses source-load-storage resources to maximize the power supply time of critical loads and performs optimal scheduling based on the current operating status.

[0067] Furthermore, the fault self-healing model of the flexible interconnection system in the substation area is evaluated and optimized through the following evaluation indicators:

[0068] 1) Self-healing frequency

[0069] Calculate the proportion of samples in which the flexible interconnection system in the substation area successfully supplies power to the critical load in the island mode, which reflects the resilience of the flexible interconnection system in the substation area;

[0070]

[0071] Where N s represents the number of samples that have been successfully recovered under all fault scenario samples, and N represents the number of all scenario samples generated in the island mode;

[0072] 2) Load expected interruption time

[0073] Evaluate the number of days that the flexible interconnection system in the substation area cannot meet the critical load demand in the island mode. The lower the expected load interruption time, the higher the reliability of the flexible interconnection system in the substation area when a fault occurs.

[0074] LOLE=(1-RFR)×365

[0075] 3) Duration

[0076] Calculate the ratio of the continuous power supply time of the flexible interconnection system in the island mode to the fault time. The higher the duration value, the longer the self-healing duration of the flexible interconnection system in the area.

[0077]

[0078] Where, T r Indicates the continuous power supply time in island mode, T f Failure time in island mode

[0079] 4) No energy supply

[0080] Measures the total amount of energy that fails to meet load demand, used to reflect the power supply gap of the system under different energy scenarios;

[0081]

[0082] Where P l Indicates the load of the flexible interconnection system in the substation area;

[0083] 5) Renewable energy utilization rate calculates the proportion of power supply accounted for by renewable energy in island mode, which is used to analyze the power supply of renewable energy in island mode

[0084] contribute;

[0085]

[0086] In the formula, It represents the power supply of renewable energy in island mode in one year. Indicates the total amount of electricity consumed by critical loads in a year;

[0087] 6) Flexible resource utilization

[0088] Used to measure the energy contribution of the energy storage system in island mode;

[0089]

[0090] In the formula, Indicates the power supply of the energy storage system in island mode within one year.

[0091] And, an optimization management system of a flexible interconnection system of a substation based on fault self-healing capability, based on a flexible interconnection system of a substation with an energy storage system, comprising:

[0092] The fault self-healing model of the flexible interconnection system in the substation area is used to implement the following self-healing strategies:

[0093] In the grid-connected mode before the grid is disconnected, the energy storage system's energy storage status is calculated through the optimal power flow algorithm, and the energy storage system is charged to prepare for operation in the island mode. When a main grid fault is detected, the source-load-storage resources are used to maximize the power supply time of key loads, and optimal scheduling is performed according to the current operating status.

[0094] When the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to give priority to power supply to critical loads.

[0095] Furthermore, the goal of the fault self-healing model of the flexible interconnected system in the substation is to maximize the power supply time of the critical load; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of the source, load and storage resources after the power outage;

[0096] The fault self-healing model satisfies both power balance constraints and energy storage system constraints;

[0097] The power balance constraint is:

[0098]

[0099] Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time;

[0100] The energy storage system constraints are:

[0101]

[0102] Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system;

[0103] The energy storage system should also meet the non-simultaneity of charging and discharging operations:

[0104]

[0105] In the formula, and Indicates the charging and discharging status of the energy storage system.

[0106] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the optimization management method of a flexible interconnection system of a substation based on fault self-healing capability as described above are implemented.

[0107] A non-transitory computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned optimization management method for a flexible interconnection system of a substation based on fault self-healing capability.

[0108] Compared with the prior art, the present invention and its preferred embodiments include at least the following beneficial effects:

[0109] 1) By introducing fault self-healing capabilities, it can automatically switch to island mode when the main power grid fails, ensuring continuous power supply to critical loads and significantly improving power supply stability; it overcomes the defects of traditional technologies that rely on manual intervention and have limited fault recovery capabilities.

[0110] 2) Optimizes the energy storage system and load scheduling to maximize the power supply time of key loads; overcomes the defects of traditional systems that lack optimized scheduling methods and are difficult to fully utilize energy storage resources, and ensures the power supply time of key loads.

[0111] 3) The use of photovoltaic and wind power generation models and intelligent energy storage scheduling has greatly improved the utilization rate of renewable energy and overall energy efficiency; it overcomes the shortcomings of traditional technologies due to insufficient scheduling of renewable energy generation and ensures energy utilization efficiency.

[0112] 4) It can maximize the energy contribution in the island mode and improve the system's ability to cope with complex fault scenarios by intelligently scheduling the charging and discharging of the energy storage system. It can also avoid the extensive resource management mode of traditional technologies, give full play to the potential of the energy storage system, and enhance the flexibility of the flexible interconnection system of the substation area. BRIEF DESCRIPTION OF THE DRAWINGS

[0113] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0114] Figure 1 It is a flowchart of the overall implementation scheme of the embodiment of the present invention.

[0115] Figure 2 It is a flow chart of a method for evaluating the self-healing capability of a flexible interconnection system in an area provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0116] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are specifically described in detail as follows:

[0117] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0118] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0119] like Figure 1 As shown, an embodiment of the present invention provides an optimization management method for a flexible interconnection system of a substation based on fault self-healing capability, and the construction process of the overall solution specifically includes the following steps:

[0120] S1. Obtain the historical operating power data of the distributed photovoltaic, wind turbine and energy storage systems connected to the flexible interconnection system in the substation area, build an operating power model, and fit the power generation probability models of photovoltaic and wind turbines based on the normal distribution function and Weibull distribution respectively; generate a normal operating scenario library of the flexible interconnection system in the substation area based on the m-ISODATA method through Monte Carlo simulation random sampling; on this basis, select fault scenarios through the random number comparison method and extract the fault scenario library; specifically:

[0121] The first step is to prepare the input data. The data dimensions include but are not limited to the following variables: photovoltaic and wind turbine power generation, load demand, fault information, and the charging and discharging status of the energy storage system. Historical data can be represented as a multidimensional data set X, where each row corresponds to the status at a moment and contains multiple different dimensions, such as wind power generation, load demand, etc.

[0122]

[0123] Among them, x i Represents the data point at the i-th time point, and d is the dimension of the data.

[0124] The iteration process is as follows:

[0125] a. Perform clustering according to the Euclidean distance formula and assign each data point to the nearest cluster centroid:

[0126] d(x i ,μ c )=||x i -μ c || (2)

[0127] Among them, μ c is the centroid of the cth cluster, x i is an arbitrary data point.

[0128] Data points are assigned to the nearest centroid:

[0129]

[0130] b. When the centroid is updated, the centroid will be recalculated based on the data points newly assigned to the cluster:

[0131]

[0132] c. If the standard deviation of a cluster exceeds the preset σ max , then perform the split operation:

[0133] λ δ,δ is the eigenvalue of the covariance matrix of cluster c (5)

[0134] When σ c >σ max When , the centroids are split along the principal axes of the covariance matrix:

[0135]

[0136] where λ c It is the largest eigenvector in the covariance matrix and indicates the main expansion direction of the data.

[0137] d. If the distance between the two cluster centroids is less than the preset minimum distance d min , then merge these two clusters:

[0138] d(μ a ,μ b )=||μ a -μ b ||<d min (7)

[0139] The new centroid position after merging is:

[0140]

[0141] e. The algorithm terminates when any of the following conditions is met: the preset maximum number of iterations is reached, the split and merge operations no longer change the clusters, or the number of clusters oscillates between two values.

[0142] f. Each cluster centroid finally represents an operation scenario, and the probability of occurrence corresponding to each scenario is the proportion of data points in the cluster:

[0143]

[0144] where |X c | is the number of data points belonging to scene S, and n is the total number of data points.

[0145] The generated scenarios can be used for subsequent optimization analysis of the flexible interconnection system in the substation area, such as optimal power flow problems or Monte Carlo simulations, to evaluate the operating performance of the flexible interconnection system in the substation area under different scenarios. For example, these scenarios can be used to analyze the self-healing ability and load response of the flexible interconnection system in the island mode and grid-connected mode.

[0146] S2. Traverse the fault scenarios at each moment in the fault scenario library to build a fault self-healing model for the flexible interconnection system in the substation area; solve the fault self-healing model through the commercial solver CPLEX to obtain the optimal power curve of the flexible load and distributed power source, obtain the load recovery rate and power data of photovoltaic and wind turbines under each fault scenario of the flexible interconnection system in the substation area, and the input parameters such as the charging and discharging status of the energy storage system; specifically:

[0147] S2-1. The core goal of building this fault self-healing model is to maximize the power supply time of critical loads; the power distribution of each energy unit in the system is analyzed and optimized through optimal power flow, including the optimal power operation curve of source, load and storage resources after power outage.

[0148] S2-2. The model must satisfy both the power balance constraints and the energy storage system constraints.

[0149] The power balance condition is:

[0150]

[0151] Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand.

[0152] The constraints satisfied by the energy storage system are:

[0153]

[0154] Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and They respectively represent the current charging and discharging power of the energy storage system.

[0155] In addition, the energy storage system should also satisfy the non-simultaneity of charging and discharging operations expressed by this formula:

[0156]

[0157] In the formula, and Indicates the charging and discharging status of the energy storage system.

[0158] S2-3. When the flexible interconnection system of the substation enters the island mode, the system automatically executes the removal of non-critical loads, giving priority to the power supply of critical loads such as medical equipment and traffic signals; then the model calculates the energy storage status of the energy storage system through the optimal power flow algorithm in the grid-connected mode before the grid disconnection, so when a main grid fault is detected, the system uses these resources to maximize the power supply time of critical loads; in short, the model will charge the energy storage system in normal grid-connected mode to prepare for operation in island mode. When a fault occurs, the model performs optimal scheduling based on the current operating status.

[0159] Through the first two steps, the embodiment of the present invention realizes the power scheduling of loads and distributed power sources under various fault scenarios of the flexible interconnection system of the substation area.

[0160] In order to further evaluate and demonstrate the effects and advantages of the embodiments of the present invention, S3 is added to the design example to obtain the power dispatch results of the load and distributed power supply under various fault scenarios of the flexible interconnection system in the substation area, calculate the self-healing frequency index, the expected load interruption time index, the self-healing duration index and the unsupplied energy index; output the annual reliability index of the flexible interconnection system in the target substation area to evaluate the self-healing ability of the system, such as Figure 2 Specifically:

[0161] Define each evaluation indicator:

[0162] 1) Self-healing frequency

[0163] Calculating the proportion of samples in which the flexible interconnection system in the substation area successfully supplies power to critical loads in island mode reflects the recovery capability of the flexible interconnection system in the substation area. The high self-healing frequency value means that the flexible interconnection system in the substation area can effectively protect critical loads in most cases.

[0164]

[0165] Where N s It represents the number of samples that are successfully recovered under all fault scenario samples, and N represents the number of all scenario samples generated in the island mode.

[0166] 2) Load expected interruption time

[0167] Evaluate the number of days that the flexible interconnection system in the substation area cannot meet the critical load demand in the island mode. The lower the expected load interruption time, the higher the reliability of the flexible interconnection system in the substation area when a fault occurs.

[0168] LOLE=(1-RFR)×365 (14)

[0169] 3) Duration

[0170] The ratio of the continuous power supply time of the flexible interconnection system in the island mode to the fault time is calculated. The higher the duration value, the longer the self-healing duration of the flexible interconnection system in the substation area.

[0171]

[0172] Where, T r Indicates the continuous power supply time in island mode, T f Failure time in island mode

[0173] 4) No energy supply

[0174] Measures the total amount of energy that fails to meet load demand. It is used to reflect the power supply gap of the system under different energy scenarios. The lower the unsupplied energy, the better the system can ensure stable power supply.

[0175]

[0176] Where P l Represents the load of the flexible interconnection system in the substation.

[0177] 5) Utilization rate of renewable energy

[0178] Calculates the proportion of power supply from renewable energy in island mode. This indicator is used to analyze the power supply contribution of renewable energy in island mode.

[0179]

[0180] In the formula, It represents the power supply of renewable energy in island mode in one year. Indicates the total amount of electricity consumed by key loads in a year

[0181] 6) Flexible resource utilization

[0182] Measures the energy contribution of energy storage systems in island mode.

[0183]

[0184] In the formula, Indicates the power supply of the energy storage system in island mode within one year.

[0185] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0186] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0187] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0188] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0189] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0190] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

[0191] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive other various forms of optimization management methods for flexible interconnection systems of substations based on fault self-healing capabilities under the inspiration of the present invention. All equivalent changes and modifications made within the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. An optimization management method for a flexible interconnection system in a substation area based on fault self-healing capability, characterized in that: The following self-healing strategies are implemented through the fault self-healing model of the flexible interconnection system in the substation area: In the grid-connected mode before the grid is disconnected, the energy storage system's energy storage status is calculated through the optimal power flow algorithm, and the energy storage system is charged to prepare for operation in the island mode. When a main grid fault is detected, the source-load-storage resources are used to maximize the power supply time of key loads, and optimal scheduling is performed according to the current operating status. When the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to give priority to power supply to critical loads.

2. The optimization management method of a flexible interconnection system based on fault self-healing capability according to claim 1 is characterized in that: The goal of the fault self-healing model of the flexible interconnected system in the substation area is to maximize the power supply time of key loads; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of source, load and storage resources after power outage; The fault self-healing model satisfies both power balance constraints and energy storage system constraints; The power balance constraint is: Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time; The energy storage system constraints are: Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system; The energy storage system should also meet the non-simultaneity of charging and discharging operations: In the formula, and Indicates the charging and discharging status of the energy storage system.

3. The optimization management method of the flexible interconnection system of the substation area based on the fault self-healing capability according to claim 1 is characterized by: The method for generating the optimal scheduling solution comprises the following steps: Firstly, the historical operating power data of the distributed photovoltaic, wind turbine and energy storage system connected to the flexible interconnection system of the substation are obtained, and the operating power model is constructed. The power generation probability models of photovoltaic and wind turbine are fitted based on the normal distribution function and Weibull distribution respectively. Through Monte Carlo simulation random sampling, the normal operation scenario library of the flexible interconnection system of the substation based on the m-ISODATA method is generated. On this basis, the fault scenarios are selected by random number comparison method to extract the fault scenario library. Then, the fault scenarios at each moment in the fault scenario library are traversed to construct the fault self-healing model of the flexible interconnection system of the substation. The fault self-healing model is solved by the CPLEX solver to obtain the optimal power curve of the flexible load and distributed power source, and the input parameters including the load recovery rate and the power data of photovoltaic and wind turbine under each fault scenario of the flexible interconnection system of the substation, as well as the charging and discharging status of the energy storage system are obtained to execute the power dispatch of the load and distributed power source under each fault scenario of the flexible interconnection system of the substation.

4. The optimization management method of the flexible interconnection system of the substation area based on the fault self-healing capability according to claim 3 is characterized by: The specific steps of generating the normal operation scenario library of the flexible interconnection system of the substation area based on the m-ISODATA method are as follows: Acquire data including at least: photovoltaic and wind turbine power generation, load demand, fault information, and charging and discharging status of energy storage systems; represent historical data as a multidimensional data set X, where each row corresponds to the status at a moment, and contains multiple different dimensions; Among them, x i represents the data point at the i-th time point, and d is the dimension of the data; Then the following iterative process is performed: a. Perform clustering according to the Euclidean distance formula and assign each data point to the nearest cluster centroid: d(x i ,m c )=‖x i -m c ‖ Among them, μ c is the centroid of the cth cluster, x i is an arbitrary data point; Data points are assigned to the nearest centroid: b. When the centroid is updated, the centroid is recalculated based on the data points newly assigned to the cluster: c. If the standard deviation of a cluster exceeds the preset σ max , then perform the split operation: λ δ,δ is the eigenvalue of the covariance matrix of cluster c When σ c >σ max When , the centroids are split along the principal axes of the covariance matrix: where λ c It is the largest eigenvector in the covariance matrix, indicating the main expansion direction of the data; d. If the distance between the two cluster centroids is less than the preset minimum distance d min , then merge these two clusters: d(μ a ,m b )=||μ a -m b ||<d min The new centroid position after merging is: e. The iteration terminates when any of the following conditions is met: the preset maximum number of iterations is reached, the split and merge operations no longer change the clusters, or the number of clusters oscillates between two values; f. Each cluster centroid finally represents an operation scenario, and the probability of occurrence corresponding to each scenario is the proportion of data points in the cluster: where |X c | is the number of data points belonging to scene S, and n is the total number of data points.

5. The optimization management method of the flexible interconnection system of the substation area based on the fault self-healing capability according to claim 3 is characterized by: The construction process of the fault self-healing model of the flexible interconnection system in the substation area specifically includes: The goal of the fault self-healing model is to maximize the power supply time of critical loads; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of source, load and storage resources after power outage; The fault self-healing model satisfies both power balance constraints and energy storage system constraints; The power balance constraint is: Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time; The energy storage system constraints are: Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system; The energy storage system should also meet the non-simultaneity of charging and discharging operations: In the formula, and Indicates the charging and discharging status of the energy storage system; The self-healing strategy is set as follows: when the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to prioritize the power supply of critical loads; in the grid-connected mode before the grid disconnection, the model calculates the energy storage state of the energy storage system through the optimal power flow algorithm, and charges the energy storage system in preparation for operation in the island mode; when a main grid fault is detected, the system uses source-load-storage resources to maximize the power supply time of critical loads and performs optimal scheduling based on the current operating status.

6. The optimization management method of the flexible interconnection system of the substation area based on the fault self-healing capability according to claim 3 is characterized by: The fault self-healing model of the flexible interconnection system in the substation area is evaluated and optimized through the following evaluation indicators: 1) Self-healing frequency Calculate the proportion of samples in which the flexible interconnection system in the substation area successfully supplies power to the critical load in the island mode, which reflects the resilience of the flexible interconnection system in the substation area; Where N s represents the number of samples that have been successfully recovered under all fault scenario samples, and N represents the number of all scenario samples generated in the island mode; 2) Load expected interruption time Evaluate the number of days that the flexible interconnection system in the substation area cannot meet the critical load demand in the island mode. The lower the expected load interruption time, the higher the reliability of the flexible interconnection system in the substation area when a fault occurs. LOLE=(1-RFR)×365 3) Duration Calculate the ratio of the continuous power supply time of the flexible interconnection system in the island mode to the fault time. The higher the duration value, the longer the self-healing duration of the flexible interconnection system in the area. Where, T r Indicates the continuous power supply time in island mode, T f Failure time in island mode 4) No energy supply Measures the total amount of energy that fails to meet load demand, used to reflect the power supply gap of the system under different energy scenarios; Where P l Indicates the load of the flexible interconnection system in the substation area; 5) Renewable energy utilization rate calculates the proportion of power supply accounted for by renewable energy in the island mode, which is used to analyze the power supply contribution of renewable energy in the island mode; In the formula, It represents the power supply of renewable energy in island mode in one year. Indicates the total amount of electricity consumed by critical loads in a year; 6) Flexible resource utilization Used to measure the energy contribution of the energy storage system in island mode; In the formula, Indicates the power supply of the energy storage system in island mode within one year.

7. An optimization management system for a flexible interconnection system in a substation area based on fault self-healing capability, characterized in that: Based on the flexible interconnection system of the substation with energy storage system, including: The fault self-healing model of the flexible interconnection system in the substation area is used to implement the following self-healing strategies: In the grid-connected mode before the grid is disconnected, the energy storage system's energy storage status is calculated through the optimal power flow algorithm, and the energy storage system is charged to prepare for operation in the island mode. When a main grid fault is detected, the source-load-storage resources are used to maximize the power supply time of key loads, and optimal scheduling is performed according to the current operating status. When the flexible interconnection system in the substation enters the island mode, non-critical loads are removed to give priority to power supply to critical loads.

8. The optimization management system of the flexible interconnection system of the substation area based on the fault self-healing capability according to claim 7 is characterized by: The goal of the fault self-healing model of the flexible interconnected system in the substation area is to maximize the power supply time of key loads; optimize the power distribution of each energy unit in the system through optimal power flow analysis, including the optimal power operation curve of source, load and storage resources after power outage; The fault self-healing model satisfies both power balance constraints and energy storage system constraints; The power balance constraint is: Where P pv , P w is the output power of photovoltaic and wind power generation, is the discharge power of the energy storage system, is the charging power of the energy storage system, P l is the current load demand; s represents the state, and t represents the time; The energy storage system constraints are: Indicates the charging and discharging status of the energy storage system. Indicates the upper and lower limits of the charging power of the energy storage system, Indicates the upper and lower limits of the discharge power of the energy storage system, and Respectively represent the current charging and discharging power of the energy storage system; The energy storage system should also meet the non-simultaneity of charging and discharging operations: In the formula, and Indicates the charging and discharging status of the energy storage system.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the optimization management method of the flexible interconnection system of the substation based on the fault self-healing capability as described in any one of claims 1 to 7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for optimizing management of a flexible interconnection system of substations based on fault self-healing capability as described in any one of claims 1 to 7.

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