Site selection and sizing method and device for flexible interconnection device and electronic equipment

Abstract

The invention discloses a locating and sizing method and device for a flexible interconnection device and electronic equipment, and relates to the technical field of electric power, and the method comprises the steps: obtaining P initial schemes corresponding to a power distribution network; the P initial schemes are iteratively simulated on the basis of a preset algorithm, performance indexes, corresponding to the initial schemes, of the power distribution network are obtained, and the performance indexes comprise at least one of the maximum load rate, the node safety level and the power supply capacity level; under the condition that the total simulation frequency is greater than or equal to the preset global simulation frequency, screening at least one initial scheme from the P initial schemes as a target scheme based on the performance index corresponding to each initial scheme; and performing addressing and sizing operation on the K flexible interconnection devices based on the target scheme. According to the method and the device, the technical problem of low efficiency of locating and sizing the flexible interconnection device needing to be deployed in the power distribution network based on the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of power technology, and more specifically, to a method, apparatus, and electronic equipment for the location and capacity determination of a flexible interconnection device. Background Technology

[0002] With the large-scale integration of distributed energy sources (such as photovoltaic power generation and wind power generation) into the distribution network, and the rapid growth of new load technologies such as electric vehicles and distributed energy storage, the operating characteristics of traditional distribution networks are facing significant changes. On the one hand, the large-scale integration of power sources with randomness and intermittency makes the power flow distribution of the distribution network increasingly complex, which can easily lead to problems such as voltage exceeding limits and power quality degradation. On the other hand, the uncertainty of grid load demand and the uneven distribution in time and space also exacerbate the power supply pressure on the distribution network, which may reduce the reliability and security of power supply.

[0003] To ensure the safe and stable operation of the power grid while fully utilizing clean energy and enhancing the control capabilities of the distribution network, flexible interconnection devices, as a new generation of power electronic equipment, can achieve rapid power exchange and flexible power flow regulation between different feeders and even different substations, providing an effective means to improve the flexibility and controllability of the distribution network. Through the rational deployment of flexible interconnection devices, multiple objectives can be achieved in power grid operation, including peak shaving and valley filling, suppressing voltage fluctuations, and improving power supply reliability and power quality.

[0004] Therefore, how to scientifically plan the installation location (site selection) and rated capacity (capacity) of flexible interconnection devices in the distribution network to give full play to their economic and technical advantages has become an important research direction and technical challenge in the field of distribution network planning and optimization design.

[0005] Existing site selection and capacity determination methods are mainly divided into traditional mathematical programming methods and heuristic intelligent algorithms. Traditional methods (such as mixed integer programming) are often too simplified or have huge computational loads when dealing with complex high-dimensional and nonlinear power grid models, making them difficult to solve. Heuristic algorithms (such as genetic algorithms and particle swarm optimization algorithms) are widely used, but they are prone to getting trapped in local optima and require a lot of repetitive simulation calculations and safety verifications, resulting in a very long optimization process and low efficiency.

[0006] There is currently no effective solution to the above problems. Summary of the Invention

[0007] This application provides a method, apparatus, and electronic device for site selection and capacity determination of flexible interconnection devices, so as to at least solve the technical problem of low efficiency in site selection and capacity determination of flexible interconnection devices to be deployed in distribution networks based on existing technologies.

[0008] According to one aspect of this application, a method for site selection and capacity determination of flexible interconnection devices is provided, comprising: obtaining P initial schemes corresponding to a distribution network, wherein each initial scheme includes the installation locations and maximum capacity of K flexible interconnection devices to be deployed, and P and K are both positive integers; performing iterative simulation operations on the P initial schemes based on a preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme, wherein the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indicators include at least one of the following: maximum load rate, node security level, and power supply capacity level; when the total number of simulations is greater than or equal to the preset global number of simulations, selecting at least one initial scheme as a target scheme from the P initial schemes based on the performance indicators corresponding to each initial scheme, wherein the total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration of the preset algorithm; and performing site selection and capacity determination operations on the K flexible interconnection devices based on the target scheme.

[0009] Optionally, obtaining P initial schemes corresponding to the distribution network includes: collecting first data and second data of the distribution network, wherein the first data is used to characterize the connection method and spatial layout of the electrical equipment included in the distribution network, and the second data is used to characterize the operating constraints of the electrical equipment included in the distribution network; and generating P initial schemes based on the first data and the second data.

[0010] Optionally, simulation operations are performed iteratively on P initial schemes based on a preset algorithm, including: in the first round of execution of the preset algorithm, initialization operations are performed on the P initial schemes based on the preset algorithm, wherein the initialization operations are used to determine the initial number of simulations for each initial scheme, and the initial number of simulations is the number of simulation operations that each initial scheme needs to perform in the first round of execution; based on the initial number of simulations for each initial scheme, power flow calculations are performed on each initial scheme R times, where R is equal to the initial number of simulations; based on the R sets of performance indicators obtained from the R power flow calculations, the mean and variance of the indicators corresponding to each initial scheme are determined; based on the mean and variance of the indicators corresponding to each initial scheme, the target number of simulations is determined for each initial scheme, wherein the target number of simulations is the number of simulation operations that each initial scheme needs to perform in the next round of execution of the preset algorithm.

[0011] Optionally, simulation operations are performed iteratively on P initial schemes based on a preset algorithm, including: during the j-th execution of the preset algorithm, S power flow calculations are performed on each initial scheme based on the target number of simulations, where S equals the target number of simulations and j is an integer greater than or equal to 2; based on the S sets of performance indicators obtained from the S power flow calculations, the mean and variance of the indicators corresponding to each initial scheme are updated; based on the mean and variance of all new indicators corresponding to the P initial schemes, the target number of simulations is updated.

[0012] Optionally, based on the mean and variance of the indicators corresponding to each initial scheme, the target number of simulations for each initial scheme is determined, including: based on the mean and variance of the indicators corresponding to each initial scheme, a target update strategy for each initial scheme is determined, wherein the target update strategy is one of the following: a first update strategy, used to increase the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; a second update strategy, used to reduce the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; and based on the preset increment number and the target update strategy for each initial scheme, the target number of simulations for each initial scheme is determined, wherein the preset increment number is the sum of the number of simulation operations that P initial schemes need to perform in the next round of execution of the preset algorithm.

[0013] Optionally, based on the mean and variance of the indicators corresponding to each initial scheme, a target update strategy for each initial scheme is determined, including: performing a non-dominated sorting operation on P initial schemes based on the mean and variance of the indicators corresponding to each initial scheme to obtain a target scheme, wherein the target scheme is the non-dominated scheme in the beat order result corresponding to the non-dominated sorting operation; if the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is less than a preset difference / the variance corresponding to the z-th initial scheme is greater than or equal to a preset variance, the first update strategy is used as the target update strategy for the z-th initial scheme; if the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is greater than or equal to a preset difference, the second update strategy is used as the target update strategy for the z-th initial scheme.

[0014] Optionally, based on the preset number of increments and the target update strategy for each initial scheme, the target number of simulations for each initial scheme is determined, including: determining the number of simulations increase ratio for each initial scheme based on the target update strategy for each initial scheme; and determining the target number of simulations for each initial scheme based on the product of the number of simulations increase ratio for each initial scheme and the preset number of increments.

[0015] According to another aspect of this application, a site selection and capacity determination device for flexible interconnection devices is also provided, comprising: an initial scheme acquisition unit, configured to acquire P initial schemes corresponding to a distribution network, wherein each initial scheme includes the installation locations and maximum capacity of K flexible interconnection devices to be deployed, and P and K are both positive integers; an iterative simulation unit, configured to perform iterative simulation operations on the P initial schemes based on a preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme, wherein the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indicators include at least one of the following: maximum load rate, node security level, and power supply capacity level; a target scheme determination unit, configured to select at least one initial scheme as a target scheme from the P initial schemes based on the performance indicators corresponding to each initial scheme, provided that the total number of simulations is greater than or equal to the preset global simulation number, wherein the total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration process of the preset algorithm; and a site selection and capacity determination unit, configured to perform site selection and capacity determination operations on the K flexible interconnection devices based on the target schemes.

[0016] According to another aspect of this application, a computer program product is also provided, which stores a computer program, wherein, when the computer program is running, the addressing and sizing method of the flexible interconnection device that controls the computer program product to execute any of the above-mentioned methods is provided.

[0017] According to another aspect of this application, an electronic device is also provided, wherein the electronic device includes one or more processors and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the addressing and sizing method of the flexible interconnect device described above.

[0018] In this application, P initial schemes corresponding to the distribution network are first obtained, wherein each initial scheme includes the installation locations and maximum capacity of K flexible interconnection devices to be deployed, where P and K are both positive integers. Then, this application iteratively simulates the P initial schemes based on a preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme. The preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indicators include at least one of the following: maximum load rate, node security level, and power supply capacity level. If the total number of simulations is greater than or equal to the preset global simulation number, this application selects at least one initial scheme as the target scheme from the P initial schemes based on the performance indicators corresponding to each initial scheme. The total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration of the preset algorithm. Subsequently, this application performs site selection and capacity determination operations on the K flexible interconnection devices based on the target scheme.

[0019] As can be seen from the above, this application constructs a multi-objective (i.e., multi-dimensional performance indexes corresponding to the distribution network) optimization framework for the location and capacity determination problem of flexible interconnection devices, and adopts a method of dynamically allocating simulation resources for P initial schemes. This achieves the goal of accurately evaluating the location and capacity determination schemes of flexible interconnection devices within a limited number of simulations, thereby improving the technical effect of improving the location and capacity determination efficiency of flexible interconnection devices. In turn, it solves the technical problem of low efficiency in the location and capacity determination of flexible interconnection devices that need to be deployed in the distribution network based on existing technologies. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0021] Figure 1 This is a flowchart of an optional addressing and sizing method for a flexible interconnect device according to an embodiment of this application;

[0022] Figure 2 This is an optional addressing and sizing method for flexible interconnect devices based on the OCBA algorithm according to an embodiment of this application;

[0023] Figure 3 This is a schematic diagram of an optional addressing and sizing device for a flexible interconnect device according to an embodiment of this application;

[0024] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It should also be noted that all relevant information (including but not limited to information related to user flight segments) and data (including but not limited to data used for display and analysis) involved in this application are information and data authorized by the user or fully authorized by all parties. For example, if there is an interface between this system and the relevant user or organization, before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain the relevant information only after receiving consent from the aforementioned user or organization.

[0028] Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of relevant information and data involved in this application all comply with the relevant laws, regulations, and standards of the relevant regions, and necessary confidentiality measures have been taken. This application does not violate public order and good morals. In addition, this application provides a corresponding operation entry point for users to choose to agree to or refuse authorization. If the user chooses to refuse authorization, the corresponding expert decision-making process will be initiated.

[0029] In one alternative embodiment, a method for addressing and sizing flexible interconnect devices based on mathematical programming methods / heuristic intelligent algorithms is provided. The problem with this method is as follows:

[0030] Evaluating the performance of each candidate scheme (i.e., a specific combination of location and capacity) requires at least one costly power system simulation calculation. When considering load fluctuations, uncertainties in renewable energy output, and the randomness of grid faults, numerous simulations of random scenarios are needed, employing methods such as Monte Carlo simulations, to obtain stable and reliable performance indicators for a scheme. When the number of candidate schemes is large, applying the same numerous simulations (i.e., "equal allocation" or "brute-force calculation") to all schemes will result in a significant waste of computational resources, as a large portion of the computational budget will be consumed on schemes with poor performance indicators.

[0031] Specifically, assuming the total simulation computing resources, i.e. the total number of simulations, are M, if an equal allocation strategy is adopted, the number of simulations allocated to each candidate scheme is... They are all the same, that is , where N is the total number of candidate solutions, and i is a positive integer less than or equal to N.

[0032] The strategies in the above embodiments ignore the potential differences in the performance evaluation of different schemes and fail to concentrate more computing resources on more promising high-quality schemes, resulting in low optimization efficiency.

[0033] Another embodiment is based on a brute-force algorithm, which accurately evaluates the performance of each solution by exhaustively enumerating all possible scenario combinations. That is, it performs a large number of full-scenario, full-time accurate simulations on each candidate solution. In real-world systems, this solution is often infeasible due to the excessive computational resources required.

[0034] Therefore, there is an urgent need for a new method that can allocate computing resources more intelligently and efficiently within a limited computing time, thereby determining the optimal addressing and occupancy scheme with higher confidence.

[0035] To address the problems existing in the above embodiments, this application adopts a preset algorithm (such as OCBA (Optimal Computing Budget Allocation) algorithm) to avoid performing a large number of simulations on all candidate schemes. This application intelligently concentrates computing resources on the most promising preferred scheme, while eliminating obviously poor schemes with only a small number of simulations. Thus, within the same total computing time, more accurate and reliable optimization results can be obtained, significantly improving the optimization efficiency of site selection and capacity determination.

[0036] The location and capacity determination method provided in this application can handle a large set of candidate schemes. No matter how many initial candidate schemes there are, the OCBA algorithm can adaptively and efficiently screen them. At the same time, this method is also applicable to arbitrarily complex power grid simulation models without the need to simplify the model.

[0037] This application combines the efficient screening capabilities of OCBA with the Pareto frontier concept, achieving efficient solution while taking into account multiple objectives such as economy, security, and reliability. Ultimately, it outputs a set of balanced Pareto optimal solutions, providing power system decision-makers with clear and quantitative decision-making basis.

[0038] The present invention will now be described in detail with reference to various embodiments.

[0039] Example 1

[0040] According to an embodiment of this application, an embodiment of a method for addressing and calibrating a flexible interconnect device is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0041] This application provides a location and capacity determination system (hereinafter referred to as the location and capacity determination system) for implementing the location and capacity determination method for the flexible interconnection device in this application. Figure 1 This is a flowchart of an optional addressing and sizing method for a flexible interconnect device according to an embodiment of this application, such as... Figure 1 As shown, the method includes the following steps:

[0042] Step S101: Obtain P initial schemes corresponding to the distribution network, wherein each initial scheme includes the installation location and maximum capacity of K flexible interconnection devices to be deployed, and P and K are both positive integers.

[0043] Optionally, the location and capacity determination system generates a set of candidate schemes under a given distribution network topology and operating constraints, wherein the set of candidate schemes includes P initial schemes.

[0044] Optionally, each of the P initial schemes is represented as: Where K is the total number of flexible interconnect devices.

[0045] Optionally, each flexible interconnect device is represented as a triple, i.e. The triple represents from the node and nodes The maximum capacity for installation between is Flexible interconnected devices.

[0046] Optionally, the location and capacity determination system provides a variety of starting points for subsequent iterations of simulation operations by systematically generating multiple initial schemes, and provides data support for discovering the optimal or suboptimal solution.

[0047] Step S102: Simulate the P initial schemes iteratively based on the preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme. The preset algorithm is used to dynamically allocate simulation resources for each initial scheme. The performance indicators include at least one of the following: maximum load rate, node safety level, and power supply capacity level.

[0048] Optionally, the location and capacity determination system calculates the performance indicators of the distribution network corresponding to each initial scheme by setting a multi-objective performance index function. This function is set as follows: ,in, The m-th dimension represents the evaluation index. The above evaluation index includes, but is not limited to, maximum load rate, node security level, and power supply capacity level. These objective functions are the expected values ​​of the performance indicators of each scheme under the power system operation scenario, which need to be determined by multiple simulation operations.

[0049] Optionally, the preset algorithm is preferably set to the OCBA algorithm, which provides a dynamic strategy for allocating simulation resources to determine how many simulation operations should be performed on each scheme.

[0050] Optionally, the preset algorithm can intelligently identify "potential" solutions and allocate more simulation resources to these solutions, while reducing the simulation resources allocated to poorly performing solutions. In this way, the site selection and capacity allocation system can efficiently evaluate the performance of multiple solutions with a limited number of simulations, avoiding the waste of resources caused by performing equal and high-cost simulations on all solutions. By iteratively performing simulation operations and updating performance indicators, the site selection and capacity allocation system can gradually focus on the optimal solution, improving the efficiency and accuracy of the optimization process.

[0051] Step S103: If the total number of simulations is greater than or equal to the preset global number of simulations, select at least one initial scheme as the target scheme from the P initial schemes based on the performance index corresponding to each initial scheme. The total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration process of the preset algorithm.

[0052] Optionally, the preset global simulation count refers to the upper limit of the sum of the number of simulation operations that can be performed by all initial schemes set in the entire simulation operation. When the total number of simulations reaches this preset upper limit, it means that the input of computing resources has reached the predetermined level. At this time, the iteration of the preset algorithm is stopped, and the addressing and sizing system selects the best performing scheme based on the accumulated performance index evaluation results.

[0053] Optionally, the location and capacity system can help control computational costs and time by setting a preset number of global simulations, thus avoiding an indefinite simulation process.

[0054] Optionally, the location and capacity system filters target solutions by comparing the performance indicators of all solutions, eliminating obviously suboptimal solutions (i.e., dominated solutions), and focusing on the best-performing solutions (i.e., non-dominated solutions). This not only improves computational efficiency but also ensures the high quality of the final solution.

[0055] Step S104: Perform site selection and capacity determination operations on the K flexible interconnect devices based on the target scheme.

[0056] Optionally, after the site selection and capacity determination system locates the target scheme, the site selection and capacity determination operation is performed on the K flexible interconnection devices, that is, the specific installation location and maximum capacity of each device in the distribution network are determined. Based on the target scheme, the operation can ensure that the deployment of flexible interconnection devices achieves the optimal balance in multiple aspects such as economy, security and power supply capacity, effectively improving the operating efficiency and reliability of the distribution network.

[0057] As can be seen from the above, in this application, by utilizing the dynamic simulation resource allocation strategy corresponding to the preset algorithm, the goal of efficiently selecting the best configuration scheme within limited computing resources is achieved. The preset algorithm can intelligently allocate more simulation times for schemes with near-optimal performance or high uncertainty, while reducing the simulation computation input for obviously inferior schemes. Thus, it achieves the technical effect of significantly improving the efficiency of the simulation optimization process while ensuring the accuracy and robustness of the optimization results. This solves the technical problem of low efficiency in site selection and capacity determination of flexible interconnection devices that need to be deployed in the distribution network based on existing technologies.

[0058] In summary, the flexible interconnection device location and capacity determination method provided in the above embodiments overcomes the bottlenecks of high computational cost, low optimization efficiency, and difficulty in quickly locating the optimal solution among a large number of schemes in traditional technologies by introducing a preset algorithm to optimize the allocation of computational budget. While achieving multi-objective optimization, it improves the reliability and economy of location and capacity determination decisions.

[0059] In one optional embodiment, in order to obtain P initial schemes corresponding to the distribution network, the site selection and capacity determination system first collects first data and second data of the distribution network, wherein the first data is used to characterize the connection method and spatial layout of the electrical equipment included in the distribution network, and the second data is used to characterize the operating constraints of the electrical equipment included in the distribution network; then, the site selection and capacity determination system generates P initial schemes based on the first data and the second data.

[0060] Optionally, the first data refers to the topology information of the distribution network, that is, the connection method and spatial layout between electrical equipment (such as transformers, lines, switches, etc.), which describes the basic architecture and physical connection status of the power network.

[0061] Optionally, the second data refers to various constraints that must be followed when the distribution network is in operation, such as equipment capacity limits, voltage level variation range, current limits, frequency stability, etc.

[0062] Optionally, by collecting the above two types of data, the location and capacity determination system can gain a more comprehensive understanding of the current status and operational boundaries of the power distribution network, ensuring that the candidate schemes generated subsequently not only conform to the actual physical connection, but also meet the requirements of operational safety and efficiency, thereby avoiding the generation of initial schemes that are not feasible in practical applications and reducing the burden of subsequent simulation calculations.

[0063] Optionally, the location and capacity determination system generates an initial scheme set based on the first and second data, which ensures that subsequent simulation operations can fully explore location and capacity determination. At the same time, the P initial schemes provide a rich data starting point for the preset algorithm, which helps the algorithm converge to the optimal solution more efficiently. Especially when dealing with multi-objective optimization problems, different starting points can better discover the diversity in the non-dominated solution set.

[0064] In one optional embodiment, during the first round of execution of the preset algorithm, the addressing and sizing system first performs initialization operations on P initial schemes based on the preset algorithm. The initialization operations determine the initial number of simulations for each initial scheme, which is the number of simulation operations each initial scheme needs to perform during the first round of execution. Then, based on the initial number of simulations for each initial scheme, the addressing and sizing system performs R power flow calculations for each initial scheme, where R equals the initial number of simulations. Subsequently, based on the R sets of performance indicators obtained from the R power flow calculations, the addressing and sizing system determines the mean and variance of the indicators corresponding to each initial scheme. Finally, based on the mean and variance of the indicators corresponding to each initial scheme, the addressing and sizing system determines the target number of simulations for each initial scheme, where the target number of simulations is the number of simulation operations each initial scheme needs to perform during the next round of execution of the preset algorithm.

[0065] Optionally, the initial number of simulations refers to the basic number of calculations set by the OCBA algorithm for each initial scheme at the beginning, that is, the number of simulation operations performed in order to initially estimate the performance index corresponding to each scheme.

[0066] Optionally, the site selection and sizing system can quickly collect basic performance data for each initial scheme through initialization operations, providing an initial performance evaluation basis for subsequent OCBA algorithm iterations, avoiding blind calculations, initially filtering out obviously suboptimal schemes, and improving the efficiency of the overall optimization process.

[0067] Optionally, power flow calculation refers to analyzing the steady-state operation of a power system to determine parameters such as power flow, voltage distribution, and losses in the power network.

[0068] Optionally, each performance index in the R group refers to multiple specific values ​​reflecting the performance of the scheme obtained through power flow calculation, such as maximum load rate, N-1 static security (i.e., node security level), and power supply capacity level.

[0069] Optionally, the location and capacity determination system can perform R power flow calculations during the first iteration of the preset algorithm to comprehensively evaluate the performance indicators of each initial scheme. Subsequently, based on the obtained performance indicators, the advantages and disadvantages of each scheme can be further analyzed, thereby providing a data basis for subsequent simulation operation decisions.

[0070] Optionally, the mean index refers to the average performance level of each initial scheme on the index, obtained by averaging the performance indices of the R groups.

[0071] Optionally, the variance of the index reflects the degree of fluctuation of the index of the same scheme under different simulation scenarios, that is, a quantitative indicator of the stability of the scheme.

[0072] Optionally, the location and capacity system can help quantify the performance stability and reliability of each scheme by calculating the mean and variance of the indicators. This makes it easier for the subsequent OCBA algorithm to allocate computing resources more accurately based on the differences in the performance and stability of the schemes, and to prioritize the simulation of schemes with excellent performance and high stability for more runs, so as to enhance the exploration of the optimal solution.

[0073] Optionally, the target number of simulations refers to the number of simulation operations that each initial scheme should perform in the next round, calculated by the OCBA algorithm based on the currently obtained mean and variance of the indicators. Through this step, the preset algorithm can allocate resources more effectively within a limited computational budget, ensuring that high-potential schemes can be fully evaluated, while low-potential schemes can have their number of simulations reduced appropriately.

[0074] Optionally, the site selection and capacity determination system can significantly improve the utilization of computing resources by dynamically adjusting the number of target simulations. By reducing the calculation of low-potential solutions, it accelerates the process of finding the optimal solution and improves the speed and accuracy of optimizing site selection and capacity determination decisions.

[0075] In one optional embodiment, during the j-th execution of the preset algorithm, the addressing and sizing system first performs S power flow calculations on each initial scheme based on the target number of simulations for each initial scheme, where S equals the target number of simulations and j is an integer greater than or equal to 2; then, based on the S sets of performance indicators obtained from the S power flow calculations, the addressing and sizing system updates the mean and variance of the indicators corresponding to each initial scheme; then, based on the mean and variance of all new indicators corresponding to P initial schemes, the addressing and sizing system updates the target number of simulations for each initial scheme.

[0076] Optionally, during the j-th execution of the preset algorithm, the preset algorithm can gradually refine the evaluation of the performance of each initial scheme through multiple rounds of iterative execution. In the early iteration stage of the algorithm, the addressing and sizing system can quickly eliminate schemes with obviously poor performance. In the later iteration stage, the addressing and sizing system allocates more resources to schemes with potential, thereby approaching the optimal solution in a more efficient way under the condition of limited computing resources.

[0077] Optionally, the location and capacity grading system performs S power flow calculations on each initial scheme based on the target number of simulations for each initial scheme, avoiding the resource waste problem in the traditional "equal allocation" or "brute force calculation" strategies. This method can ensure a more thorough evaluation of promising schemes, while eliminating poor schemes with only a few simulations, thereby achieving efficient utilization of computing resources.

[0078] Optionally, the location and capacity determination system updates the mean and variance of the indicators corresponding to each initial scheme by using S sets of performance indicators obtained from S power flow calculations. This not only updates the quantitative description of the performance indicators corresponding to each initial scheme during the algorithm iteration process, but also updates the mean and variance of the indicators corresponding to each initial scheme, which can better guide the allocation of subsequent simulation times and thus improve the accuracy of the subsequent evaluation process.

[0079] Optionally, the site selection and capacity determination system can dynamically adjust the allocation of simulation computing resources for the next round by updating the target number of simulations for each initial scheme based on the mean and variance of all new indicators corresponding to P initial schemes. This means that the algorithm can intelligently identify which schemes need more simulations to further evaluate their performance and which schemes can be determined as non-optimal and have their number of simulations reduced. Thus, within a limited time and computing budget, the optimal site selection and capacity determination strategy for flexible interconnect devices can be determined as accurately as possible.

[0080] In one optional embodiment, the site selection and capacity determination system first determines a target update strategy for each initial scheme based on the mean and variance of the indicators corresponding to each initial scheme, wherein the target update strategy is one of the following:

[0081] The first update strategy is used to increase the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm;

[0082] The second update strategy is used to reduce the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm.

[0083] Optionally, the first update strategy is used to increase the number of simulations for candidate solutions whose average performance index is close to the optimal solution and whose variance is relatively large. The purpose is to reduce the uncertainty of the evaluation and better identify their true performance. By increasing the number of simulations for solutions that are close to the optimal solution, the location and capacity system can more accurately evaluate the true performance of these solutions and reduce the evaluation bias caused by too few initial simulations. The advantage of the first update strategy is that it can approach the best solution to the greatest extent with limited resources and improve the accuracy of decision-making.

[0084] Optionally, the second update strategy is used to reduce or stop subsequent simulations for candidate solutions whose average performance metrics differ significantly from the optimal solution, thereby avoiding the waste of valuable computational resources. For solutions whose initial evaluation results are clearly unsatisfactory, the site selection and sizing system adopts a strategy of reducing the number of simulations or even stopping simulations altogether, avoiding over-investment in known poor solutions, saving a significant amount of computation time, and thus concentrating resources on more valuable explorations.

[0085] Subsequently, the location and capacity determination system determines the target number of simulations for each initial scheme based on the preset number of increments and the target update strategy for each initial scheme. The preset number of increments is the sum of the number of simulation operations that need to be performed by the P initial schemes in the next round of execution of the preset algorithm.

[0086] Optionally, the preset number of increments refers to the sum of the number of simulation operations allowed for the addressing and sizing system in the next iteration of the OCBA algorithm. This preset number of increments will be dynamically adjusted according to the current computing resource status and optimization progress.

[0087] Optionally, the location and capacity determination system determines the target update strategy based on the mean and variance of the indicators. This strategy allows the algorithm to intelligently adjust the number of simulations according to the current evaluation of each scheme, prioritizing schemes with high potential (mean close to optimal) and high uncertainty (large variance). This allows for faster filtering out schemes with obviously poor performance indicators, while deepening the understanding of competitive schemes. Its advantages include improved utilization of computing resources, reduced unnecessary simulations, and a more focused and efficient optimization process.

[0088] Optionally, the location and capacity system ensures the gradual and controlled investment of computing resources by setting a preset number of increments and adjusting the target number of simulations for each scheme accordingly. This avoids efficiency problems caused by allocating too many or too few resources at once, thus maintaining the flexibility of budget allocation during the iteration process. This ensures the effective use of resources and prevents optimization stagnation caused by resource depletion.

[0089] In one optional embodiment, the location and capacity determination system first performs a non-dominated sorting operation on P initial schemes based on the mean and variance of the indicators corresponding to each initial scheme to obtain a target scheme, wherein the target scheme is the non-dominated scheme in the beat order result corresponding to the non-dominated sorting operation; if the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is less than a preset difference / the variance corresponding to the z-th initial scheme is greater than or equal to a preset variance, the location and capacity determination system adopts a first update strategy as the target update strategy for the z-th initial scheme; if the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is greater than or equal to a preset difference, the location and capacity determination system adopts a second update strategy as the target update strategy for the z-th initial scheme.

[0090] Optionally, non-dominated sorting operation refers to a sorting method commonly used in multi-objective optimization problems. It is used to select from multiple solutions with different performance indices a solution that is not inferior to any other solution in all indices and is superior to other solutions in at least one indice. This selection method can ensure that the selected solution is balanced among multiple objectives and is suitable for handling optimization problems with multiple objective functions.

[0091] Optionally, the location and capacity determination system selects non-dominated solutions in multi-objective optimization through non-dominated sorting operations. The non-dominated solutions perform well in at least one performance optimization objective, and at the same time, they perform no worse than dominated solutions in other performance optimization objectives. This step ensures the diversity and balance of the final solutions, provides decision-makers with multiple possible optimal choices, and improves the flexibility and scientific nature of decision-making.

[0092] Optionally, the site selection and capacity determination system, by determining the target update strategy corresponding to the initial scheme and dynamically adjusting the allocation of simulation times, can intelligently identify which schemes require further evaluation and which schemes can have their evaluation reduced. This not only improves the efficiency of computing resource utilization and ensures the effective use of the computing budget, but also improves the accuracy of evaluation by increasing the number of simulations for uncertain schemes, avoiding decision-making errors caused by evaluation errors. At the same time, reducing the number of simulations for poor schemes significantly shortens the total time of the optimization process and improves optimization efficiency.

[0093] In summary, the site selection and capacity determination system achieves efficient solutions to the site selection and capacity determination optimization problem of flexible interconnect devices by intelligently allocating computing resources. It can quickly focus on the most promising solution when dealing with a large set of candidate solutions, while maintaining the accuracy and comprehensiveness of solution evaluation.

[0094] In one optional embodiment, the addressing and sizing system first determines the number of simulations increment for each initial scheme based on the target update strategy for each initial scheme; then, the addressing and sizing system determines the target number of simulations for each initial scheme based on the product of the number of simulations increment for each initial scheme and the preset incremental number of simulations.

[0095] Optionally, the location and capacity determination system determines the target number of simulations for each initial scheme based on the product of the increase ratio of the number of simulations for each initial scheme and the preset incremental number of simulations, which has the following functions:

[0096] (1) Accelerate the search process: Compared with increasing the number of simulations equally for all schemes, this method can identify the optimal or near-optimal solution more quickly, which greatly accelerates the search process of the entire location and capacity decision support system.

[0097] (2) Optimize budget allocation: The product of the preset incremental number of times and the increase ratio of each scheme ensures that the overall computing budget is allocated more precisely and reasonably, avoiding resource waste. Especially when computing resources are limited, the best optimization results can be obtained at the lowest cost.

[0098] As can be seen from the above, this application constructs a multi-objective (i.e., multi-dimensional performance indexes corresponding to the distribution network) optimization framework for the location and capacity determination problem of flexible interconnection devices, and adopts a method of dynamically allocating simulation resources for P initial schemes. This achieves the goal of accurately evaluating the location and capacity determination schemes of flexible interconnection devices within a limited number of simulations, thereby improving the technical effect of improving the location and capacity determination efficiency of flexible interconnection devices. In turn, it solves the technical problem of low efficiency in the location and capacity determination of flexible interconnection devices that need to be deployed in the distribution network based on existing technologies.

[0099] In one alternative embodiment, Figure 2 This is an optional addressing and sizing method for flexible interconnect devices based on the OCBA algorithm according to an embodiment of this application, such as... Figure 2 As shown, the method includes the following steps:

[0100] (1) Define the set of flexible interconnection device configuration schemes:

[0101] Defined as a collection of one or more devices Where K is the number of devices, and each flexible interconnect device is represented as a triple, i.e. The triple represents from the node and nodes The maximum capacity for installation between is Flexible interconnected devices.

[0102] (2) Define the multidimensional performance objective function:

[0103] The multidimensional performance objective function is ,in, These objective functions, representing the m-th dimension of the evaluation index, are the expected values ​​of the performance indicators of each scheme under the power system operation scenario, and need to be determined through multiple simulation operations.

[0104] (3) Initialization:

[0105] Assign initial simulation counts to each candidate scheme Power flow calculations are performed under random operation scenarios to obtain the mean of each target sample. With variance And record the total number of simulations. Set the global simulation budget T (i.e., the preset number of global simulations).

[0106] (4) Termination condition check:

[0107] Calculate the total number of simulations completed. If the budget limit T is reached or the performance evaluation converges, the iteration stops and proceeds to step (10); otherwise, the loop continues.

[0108] (5) Preset increment count setting:

[0109] Set preset increment count As for the additional simulation attempts that need to be allocated in this round, we will ensure that computing resources are gradually invested.

[0110] (6) OCBA allocation rule calculation:

[0111] Based on the OCBA principle, considering the performance gap and evaluation variance of each candidate solution, the allocation ratio is determined according to the following strategy: First, allocate more simulation times to candidate solutions with a mean close to the optimal solution; second, increase the number of simulation times to reduce evaluation uncertainty for candidate solutions with a large variance; finally, reduce or stop the allocation for solutions with a mean far from the optimal solution.

[0112] (7) OCBA allocation application:

[0113] Based on the three strategies in step (6), calculate the allocation ratio of the newly added simulation times (i.e., the increase ratio of the number of times) to determine the total number of simulation times that each scheme should achieve in this round. .

[0114] (8) Simulation execution and result update:

[0115] Execute for each plan Each additional simulation operation updates the corresponding mean and variance of the indicators, and updates the total number of simulations reached.

[0116] (9) Iterative loop:

[0117] Repeat steps (4)-(8) to optimize the budget allocation round by round, so that the limited computing resources are concentrated on the most promising scheme until the convergence condition is met.

[0118] (10) After the OCBA iteration is completed, the final mean vector of each candidate solution is obtained. As a basis for performance estimation, all candidate schemes are ranked in a non-dominated manner. That is, if scheme A is not inferior to scheme B in all objectives and is strictly superior to scheme B in at least one indicator, then A dominates B, and all dominated candidate schemes are eliminated.

[0119] (11) Combine all non-dominated solutions into a set to obtain the final Pareto front solution set, and output it as the final alternative configuration scheme.

[0120] Example 2

[0121] This application embodiment can also provide a site selection and capacity determination device for a flexible interconnect device. It should be noted that the site selection and capacity determination device for a flexible interconnect device in this application embodiment can be used to execute the site selection and capacity determination method for a flexible interconnect device provided in this application embodiment. The site selection and capacity determination device for a flexible interconnect device provided in this application embodiment is described below.

[0122] According to embodiments of this application, an apparatus for implementing the above-described addressing and sizing method for flexible interconnect devices is also provided. Figure 3 This is a schematic diagram of an optional addressing and sizing device for a flexible interconnect device according to an embodiment of this application, as shown below. Figure 3 As shown, the device includes: an initial scheme acquisition unit 301, an iterative simulation unit 302, a target scheme determination unit 303, and a location and capacity selection unit 304.

[0123] Optionally, the initial scheme acquisition unit 301 is used to acquire P initial schemes corresponding to the distribution network, wherein each initial scheme includes the installation location and maximum capacity of K flexible interconnection devices to be deployed, and P and K are both positive integers; the iterative simulation unit 302 is used to perform iterative simulation operations on the P initial schemes based on a preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme, wherein the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indicators include at least one of the following: maximum load rate, node security level, and power supply capacity level; the target scheme determination unit 303 is used to select at least one initial scheme as the target scheme from the P initial schemes based on the performance indicators corresponding to each initial scheme, provided that the total number of simulations is greater than or equal to the preset global simulation number, wherein the total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration process of the preset algorithm; and the site selection and capacity determination unit 304 is used to perform site selection and capacity determination operations on the K flexible interconnection devices based on the target scheme.

[0124] In an optional embodiment, the initial scheme acquisition unit 301 includes a data acquisition subunit and an initial scheme generation subunit.

[0125] Optionally, a data acquisition subunit is used to acquire first data and second data of the distribution network, wherein the first data is used to characterize the connection method and spatial layout of the electrical equipment included in the distribution network, and the second data is used to characterize the operating constraints of the electrical equipment included in the distribution network; an initial scheme generation subunit is used to generate P initial schemes based on the first data and the second data.

[0126] In one optional embodiment, the iterative simulation unit 302 includes: an initialization subunit, an initial power flow calculation subunit, an index parameter determination subunit, and a target simulation number determination subunit.

[0127] Optionally, an initialization subunit is used to perform initialization operations on P initial schemes based on the preset algorithm during the first round of execution of the preset algorithm. The initialization operation is used to determine the initial number of simulations for each initial scheme, which is the number of simulation operations that each initial scheme needs to perform during the first round of execution. An initial power flow calculation subunit is used to perform R power flow calculations on each initial scheme based on the initial number of simulations for each initial scheme, where R is equal to the initial number of simulations. An index parameter determination subunit is used to determine the mean and variance of the indexes corresponding to each initial scheme based on the R sets of performance indexes obtained from the R power flow calculations. A target simulation number determination subunit is used to determine the target number of simulations for each initial scheme based on the mean and variance of the indexes corresponding to each initial scheme, where the target simulation number is the number of simulation operations that each initial scheme needs to perform during the next round of execution of the preset algorithm.

[0128] In an optional embodiment, the iterative simulation unit 302 further includes: an iterative power flow calculation subunit, an index parameter update subunit, and a target simulation number update subunit.

[0129] Optionally, the iterative power flow calculation subunit is used to perform S power flow calculations on each initial scheme based on the target number of simulations for each initial scheme during the j-th execution of the preset algorithm, where S equals the target number of simulations and j is an integer greater than or equal to 2; the index parameter update subunit is used to update the index mean and index variance corresponding to each initial scheme based on the S sets of performance indices obtained from the S power flow calculations; and the target simulation number update subunit is used to update the target number of simulations for each initial scheme based on the new index mean and all new index variances corresponding to the P initial schemes.

[0130] In one optional embodiment, the target simulation number determination subunit includes: a target update strategy determination module and a target simulation number determination module.

[0131] Optionally, the target update strategy determination module is used to determine the target update strategy for each initial scheme based on the mean and variance of the index corresponding to each initial scheme. The target update strategy is one of the following: a first update strategy, used to increase the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; a second update strategy, used to decrease the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm. The target simulation count determination module is used to determine the target simulation count for each initial scheme based on a preset increment count and the target update strategy for each initial scheme. The preset increment count is the sum of the number of simulation operations that P initial schemes need to perform in the next round of execution of the preset algorithm.

[0132] In one optional embodiment, the target update strategy determination module includes: a non-dominated sorting submodule, a first strategy determination submodule, and a second strategy determination submodule.

[0133] Optionally, the non-dominated sorting submodule is used to perform a non-dominated sorting operation on P initial schemes based on the mean and variance of the indicators corresponding to each initial scheme to obtain the target scheme, wherein the target scheme is the non-dominated scheme in the beat order result corresponding to the non-dominated sorting operation; the first strategy determination submodule is used to take the first update strategy as the target update strategy of the z-th initial scheme when the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is less than a preset difference / the variance corresponding to the z-th initial scheme is greater than or equal to a preset variance; the second strategy determination submodule is used to take the second update strategy as the target update strategy of the z-th initial scheme when the difference between the mean of the indicators corresponding to the z-th initial scheme and the target scheme is greater than or equal to a preset difference.

[0134] In one optional embodiment, the target simulation number determination module includes: a number increase ratio determination submodule and a target simulation number determination submodule.

[0135] Optionally, the number of simulations increment determination submodule is used to determine the number of simulations increment for each initial scheme based on the target update strategy for each initial scheme; the target simulation number determination submodule is used to determine the target simulation number for each initial scheme based on the product of the number of simulations increment for each initial scheme and the preset incremental number of simulations.

[0136] It should be noted that the initial scheme acquisition unit 301, iterative simulation unit 302, target scheme determination unit 303 and addressing and sizing unit 304 mentioned above correspond to steps S101 to S104 in the method embodiment. The instances and application scenarios implemented by the above units and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment.

[0137] Example 3

[0138] Embodiments of this application can also provide an electronic device. Figure 4 This is a structural block diagram of an electronic device according to an embodiment of this application, such as... Figure 4 As shown, the electronic device includes: one or more ( Figure 4 (Only one is shown) Processor 402, memory 404, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0139] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and devices in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the above-mentioned addressing and sizing method for flexible interconnection devices.

[0140] The memory may include high-speed random access memory (RAM), and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks (LANs), mobile communication networks, and combinations thereof.

[0141] The processor can access information and applications stored in memory via a transmission device to execute the following steps: Obtain P initial schemes corresponding to the distribution network, where each initial scheme includes the installation locations and maximum capacity of K flexible interconnection devices to be deployed, and P and K are both positive integers; perform iterative simulation operations on the P initial schemes based on a preset algorithm to obtain the performance indicators of the distribution network corresponding to each initial scheme, where the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indicators include at least one of the following: maximum load rate, node security level, and power supply capacity level; when the total number of simulations is greater than or equal to the preset global simulation number, select at least one initial scheme as the target scheme from the P initial schemes based on the performance indicators corresponding to each initial scheme, where the total number of simulations is the sum of the number of simulation operations performed by the P initial schemes during the iteration of the preset algorithm; and perform site selection and capacity determination operations on the K flexible interconnection devices based on the target scheme.

[0142] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: collect first data and second data of the distribution network, wherein the first data is used to characterize the connection mode and spatial layout of the electrical equipment included in the distribution network, and the second data is used to characterize the operating constraints of the electrical equipment included in the distribution network; and generate P initial schemes based on the first data and the second data.

[0143] The processor can access information and application programs stored in memory via a transmission device to execute the following steps: In the first round of execution of the preset algorithm, initialization operations are performed on P initial schemes based on the preset algorithm. These initialization operations determine the initial number of simulations for each initial scheme, which is the number of simulation operations required for each initial scheme in the first round of execution. Based on the initial number of simulations for each initial scheme, R power flow calculations are performed on each initial scheme, where R equals the initial number of simulations. Based on the R sets of performance indicators obtained from the R power flow calculations, the mean and variance of the indicators corresponding to each initial scheme are determined. Based on the mean and variance of the indicators corresponding to each initial scheme, the target number of simulations for each initial scheme is determined, where the target number of simulations is the number of simulation operations required for each initial scheme in the next round of execution of the preset algorithm.

[0144] The processor can access the information and application program stored in the memory via the transmission device to execute the following steps: During the j-th execution of the preset algorithm, based on the target number of simulations for each initial scheme, perform S power flow calculations for each initial scheme, where S equals the target number of simulations and j is an integer greater than or equal to 2; based on the S sets of performance indicators obtained from the S power flow calculations, update the mean and variance of the indicators corresponding to each initial scheme; based on the mean and variance of all new indicators corresponding to P initial schemes, update the target number of simulations for each initial scheme.

[0145] The processor can access the information and application program stored in the memory via the transmission device to execute the following steps: Based on the mean and variance of the index corresponding to each initial scheme, determine the target update strategy for each initial scheme, wherein the target update strategy is one of the following: a first update strategy, used to increase the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; a second update strategy, used to reduce the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; Based on the preset increment number and the target update strategy for each initial scheme, determine the target number of simulations for each initial scheme, wherein the preset increment number is the sum of the number of simulation operations that P initial schemes need to perform in the next round of execution of the preset algorithm.

[0146] The processor can invoke the information and application program stored in the memory through the transmission device to execute the following steps: Based on the mean and variance of the index corresponding to each initial scheme, perform a non-dominated sorting operation on P initial schemes to obtain the target scheme, wherein the target scheme is the non-dominated scheme in the beat order result corresponding to the non-dominated sorting operation; if the difference between the mean of the index corresponding to the z-th initial scheme and the target scheme is less than a preset difference / the variance corresponding to the z-th initial scheme is greater than or equal to a preset variance, the first update strategy is used as the target update strategy for the z-th initial scheme; if the difference between the mean of the index corresponding to the z-th initial scheme and the target scheme is greater than or equal to a preset difference, the second update strategy is used as the target update strategy for the z-th initial scheme.

[0147] The processor can call the information and application program stored in the memory through the transmission device to perform the following steps: determine the number of simulations for each initial scheme based on the target update strategy for each initial scheme; determine the target number of simulations for each initial scheme based on the product of the number of simulations for each initial scheme and the preset incremental number of simulations.

[0148] This application provides a scheme for the location and capacity determination of flexible interconnection devices. By constructing a multi-objective (i.e., multi-dimensional performance indicators corresponding to the distribution network) optimization framework for the location and capacity determination problem of flexible interconnection devices, and by dynamically allocating simulation resources to P initial schemes, this application achieves the goal of accurately evaluating the location and capacity determination schemes of flexible interconnection devices within a limited number of simulations. This improves the efficiency of location and capacity determination for flexible interconnection devices, thereby solving the technical problem of low efficiency in the location and capacity determination of flexible interconnection devices to be deployed in the distribution network based on existing technologies.

[0149] Those skilled in the art will understand that Figure 4 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, PDAs, mobile internet devices, PADs, and other terminal devices. Figure 4 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 4 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 4 The different configurations shown.

[0150] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0151] Example 4

[0152] Embodiments of this application may also provide a storage medium.

[0153] Optionally, in this embodiment of the application, the storage medium can be used to store the program code executed by the addressing and calibrating method of the flexible interconnect device provided in the above method embodiment.

[0154] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0155] This application also provides a computer program product, which, when executed on a data processing device, is suitable for performing the addressing and sizing method steps of a flexible interconnect device.

[0156] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0157] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0158] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0162] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for site selection and capacity determination of a flexible interconnect device, characterized in that, The method comprises the following steps: obtaining P initial schemes corresponding to a power distribution network, wherein each initial scheme comprises installation positions and maximum capacities of K flexible interconnected devices to be deployed, and P and K are positive integers; performing simulation operations on the P initial schemes iteratively based on a preset algorithm to obtain performance indexes of the power distribution network corresponding to each initial scheme, wherein the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indexes comprise at least one of the following: maximum load rate, node safety level, and power supply capacity level; in a case where a total simulation number is greater than or equal to a preset global simulation number, selecting at least one initial scheme from the P initial schemes as a target scheme based on the performance indexes corresponding to each initial scheme, wherein the total simulation number is a sum of the number of simulation operations performed by the P initial schemes in the iteration process of the preset algorithm; performing site selection and capacity determination operations on the K flexible interconnected devices based on the target scheme.

2. The method of claim 1, wherein, Obtaining P initial schemes corresponding to a power distribution network comprises: collecting first data and second data of the power distribution network, wherein the first data is used to represent connection modes and spatial layouts of electrical equipment included in the power distribution network, and the second data is used to represent operation constraint conditions of the electrical equipment included in the power distribution network; generating the P initial schemes based on the first data and the second data.

3. The method of claim 1, wherein, Performing simulation operations on the P initial schemes iteratively based on a preset algorithm comprises: in a first round of execution process of the preset algorithm, performing initialization operations on the P initial schemes based on the preset algorithm, wherein the initialization operations are used to determine initial simulation numbers of each initial scheme, and the initial simulation number is the number of simulation operations that each initial scheme needs to perform in the first round of execution process; performing R times of power flow calculation on each initial scheme based on the initial simulation number of each initial scheme, wherein R is equal to the initial simulation number; determining an index mean and an index variance corresponding to each initial scheme based on R sets of performance indexes obtained by the R times of power flow calculation; determining a target simulation number of each initial scheme based on the index mean and the index variance corresponding to each initial scheme, wherein the target simulation number is the number of simulation operations that each initial scheme needs to perform in a next round of execution process of the preset algorithm.

4. The method of claim 3, wherein, Performing simulation operations on the P initial schemes iteratively based on a preset algorithm comprises: in a jth execution process of the preset algorithm, performing S times of power flow calculation on each initial scheme based on a target simulation number of each initial scheme, wherein S is equal to the target simulation number, and j is an integer greater than or equal to 2; updating the index mean and the index variance corresponding to each initial scheme based on S sets of performance indexes obtained by the S times of power flow calculation; updating the target simulation number of each initial scheme based on all new index means and all new index variances corresponding to the P initial schemes.

5. The method of claim 3, wherein, determining a target simulation number of each initial scheme based on the mean and variance of the performance index corresponding to each initial scheme, comprising: determining a target update strategy of each initial scheme based on the mean and variance of the performance index corresponding to each initial scheme, wherein the target update strategy is one of: a first update strategy for increasing the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; a second update strategy for reducing the number of simulation operations that the initial scheme needs to perform in the next round of execution of the preset algorithm; determining a target simulation number of each initial scheme based on a preset increment number and the target update strategy of each initial scheme, wherein the preset increment number is the sum of the number of simulation operations that the P initial schemes need to perform in the next round of execution of the preset algorithm.

6. The method of claim 5, wherein, determining a target update strategy of each initial scheme based on the mean and variance of the performance index corresponding to each initial scheme, comprising: performing a non-dominated sorting operation on the P initial schemes based on the mean and variance of the performance index corresponding to each initial scheme to obtain a target scheme, wherein the target scheme is a non-dominated scheme in the order result corresponding to the non-dominated sorting operation; in the case that the difference between the mean of the performance index corresponding to the zth initial scheme and the target scheme is less than a preset difference / the variance corresponding to the zth initial scheme is greater than or equal to a preset variance, the first update strategy is taken as the target update strategy of the zth initial scheme; in the case that the difference between the mean of the performance index corresponding to the zth initial scheme and the target scheme is greater than or equal to the preset difference, the second update strategy is taken as the target update strategy of the zth initial scheme.

7. The method of claim 5, wherein, determining a target simulation number of each initial scheme based on a preset increment number and the target update strategy of each initial scheme, comprising: determining a number increase ratio of each initial scheme based on the target update strategy of each initial scheme; determining a target simulation number of each initial scheme based on the product of the number increase ratio of each initial scheme and the preset increment number.

8. A device for site selection and volume determination of a flexible interconnection device, characterized in that comprising: an initial scheme acquisition unit configured to acquire P initial schemes corresponding to a power distribution network, wherein each initial scheme includes installation positions and maximum capacities of K flexible interconnected devices to be deployed, and P and K are positive integers; an iterative simulation unit configured to perform simulation operations on the P initial schemes based on a preset algorithm to obtain performance indexes of the power distribution network corresponding to each initial scheme, wherein the preset algorithm is used to dynamically allocate simulation resources for each initial scheme, and the performance indexes include at least one of: maximum load rate, node safety level, and power supply capacity level. The target scheme determination unit is configured to, in a case where the total simulation times are greater than or equal to the preset global simulation times, select at least one initial scheme from the P initial schemes as a target scheme based on the performance indicators corresponding to each initial scheme, wherein the total simulation times are the sum of the simulation operation times of the P initial schemes in the iteration process of the preset algorithm. The location and capacity determination unit is configured to perform a location and capacity determination operation on the K flexible interconnected devices based on the target scheme.

9. A computer program product, characterised in that, The computer program product comprises a computer program, wherein the computer program controls the computer program product to perform the location and capacity determination method of the flexible interconnected device according to any one of claims 1 to 7 when the computer program is running.

10. An electronic device, comprising: The computer program product comprises a computer program, wherein the computer program controls the computer program product to perform the location and capacity determination method of the flexible interconnected device according to any one of claims 1 to 7 when the computer program is running. The computer program product comprises a computer program, wherein the computer program controls the computer program product to perform the location and capacity determination method of the flexible interconnected device according to any one of claims 1 to 7 when the computer program is running. The computer program product comprises a computer program, wherein the computer program controls the computer program product to perform the location and capacity determination method of the flexible interconnected device according to any one of claims 1 to 7 when the computer program is running.

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