A method for diagnosing and analyzing a distribution network and planning a network framework based on intrinsic safety

Abstract

The present invention provides a distribution network diagnosis and analysis and grid framework planning method based on intrinsic safety. First, the planning information of the target distribution network is obtained; then, according to the planning information, a source-network-load-storage collaborative planning model is established; next, a random fault is applied to the target distribution network to evaluate the intrinsic safety index of the target distribution network under the fault; wherein, the intrinsic safety index is determined by the power flow overload coefficient, the cascading fault coefficient, and the minimum node inertia; finally, according to the intrinsic safety index, the source-network-load-storage collaborative planning model is optimized to obtain the optimal planning scheme of the target distribution network. By comprehensively calculating the intrinsic safety index through the power flow overload coefficient, the cascading fault coefficient, and the minimum node inertia, on the basis of minimizing costs, the planning of the target distribution network is further optimized based on the intrinsic safety index to ensure that the distribution network can effectively prevent and respond to accident risks.

Description

Technical Field

[0001] The present invention belongs to the technical field of power grid planning, and in particular relates to a distribution network diagnosis analysis and grid framework planning method based on intrinsic safety. Background Art

[0002] With the continuous growth of the social economy, the demand for electricity in various industries has been continuously rising. To meet this demand, it has become an inevitable choice for development to construct a modern power system centered on ultra-high voltage power transmission, long-distance power transmission, and large-capacity generating units. Such a power system can transmit electricity more effectively and meet the growing energy demand.

[0003] However, complex climatic conditions and frequent natural disasters pose additional challenges to the power system. The intensity and frequency of these disasters sometimes exceed the expectations during the design of the power system, resulting in the operation of the power system often approaching its limit state, thus making the safe and stable operation of the system face a major test.

[0004] In traditional distribution network planning, the main consideration is the minimization of cost, which often leads to a weak ability of the distribution network to prevent and respond to accident risks. This planning method may not be able to effectively guarantee the stability and safety of power supply when facing natural disasters or unexpected situations. Summary of the Invention

[0005] In view of this, the present invention provides a distribution network diagnosis analysis and grid framework planning method based on intrinsic safety, aiming to solve the problem that the existing distribution network has a weak ability to prevent and respond to accident risks.

[0006] The first aspect of the embodiment of the present invention provides a distribution network diagnosis analysis and grid framework planning method based on intrinsic safety, including:

[0007] Obtain the planning information of the target distribution network;

[0008] Establish a source-network-load-storage collaborative planning model according to the planning information;

[0009] Apply random faults to the target distribution network and evaluate the intrinsic safety index of the target distribution network under faults; wherein, the intrinsic safety index is determined by the power flow overload coefficient, the cascading fault coefficient, and the minimum node inertia;

[0010] Optimize the source-network-load-storage collaborative planning model according to the intrinsic safety index to obtain the optimal planning scheme of the target distribution network.

[0011] In a possible implementation manner, establishing a source-network-load-storage collaborative planning model according to the planning information includes:

[0012] A source-network-load-storage collaborative planning model is established with the goal of minimizing the power generation cost, investment cost, and operation and maintenance cost.

[0013] In a possible implementation, the objective function of the source-network-load-storage collaborative planning model is:

[0014] minF = f1 + f2 + f3 + f4

[0015] Where, F is the total cost, f1 is the power generation cost, f2 is the investment cost, f3 is the operation and maintenance cost, and f4 is the fault cost, which is determined by the impact of the applied random faults on the power grid operation.

[0016] In a possible implementation, random faults are applied to the target distribution network, and the inherent safety indicators of the target distribution network under faults are evaluated, including:

[0017] Random faults are applied to the target distribution network; the random faults include multiple groups of N-k faults;

[0018] According to the simulation results of the power grid fault simulation model under each group of N-k faults, the cascading faults corresponding to each group of N-k faults are determined; among them, the power grid fault simulation model is constructed according to the planning information of the target distribution network.

[0019] According to each group of N-k faults and the cascading faults corresponding to each group of N-k faults, the inherent safety indicators of the target distribution network under faults are evaluated.

[0020] In a possible implementation, the method further includes:

[0021] According to each group of N-k faults and the cascading faults corresponding to each group of N-k faults, the load shedding amount caused by the faults and the importance of each shed load are determined;

[0022] According to the load shedding amount caused by the faults and the importance of each shed load, the loss cost is determined;

[0023] The restoration cost of each group of N-k faults and the cascading faults corresponding to each group of N-k faults is calculated;

[0024] The sum of the loss cost and the restoration cost is used as the fault cost.

[0025] In a possible implementation, according to each group of N-k faults and the cascading faults corresponding to each group of N-k faults, the inherent safety indicators of the target distribution network under faults are evaluated, including:

[0026] The number of cascading faults is divided by the number of N-k faults to obtain the cascading fault coefficient;

[0027] According to the cascading faults corresponding to each group of N-k faults, the power flow overload coefficient is calculated;

[0028] Taking each group of N-k faults and the cascading faults corresponding to each group of N-k faults as disturbance sources, calculate the minimum node inertia under each group of N-k faults;

[0029] According to the cascading fault coefficient, power flow overload coefficient, and minimum node inertia, evaluate the inherent safety index of the target distribution network under faults.

[0030] In a possible implementation manner, according to the cascading fault coefficient, power flow overload coefficient, and minimum node inertia, evaluating the inherent safety index of the target distribution network under faults includes:

[0031] After normalizing the cascading fault coefficient, power flow overload coefficient, and minimum node inertia, perform weighted summation to obtain the inherent safety index of the source-grid-load-storage collaborative planning model under faults.

[0032] In a possible implementation manner, according to the inherent safety index, optimize the source-grid-load-storage collaborative planning model to obtain the optimal planning scheme of the target distribution network, including:

[0033] Taking the minimization of power generation cost, investment cost, operation and maintenance cost, and the maximization of inherent safety as the objectives, and using the multi-objective particle swarm optimization algorithm to optimize the source-grid-load-storage collaborative planning model to obtain the optimal planning scheme of the target distribution network.

[0034] The distribution network diagnosis analysis and grid framework planning method based on inherent safety provided by the embodiments of the present invention first obtains the planning information of the target distribution network; then establishes a source-grid-load-storage collaborative planning model according to the planning information; then applies random faults to the target distribution network and evaluates the inherent safety index of the target distribution network under faults; wherein, the inherent safety index is determined by the power flow overload coefficient, cascading fault coefficient, and minimum node inertia; finally, according to the inherent safety index, optimize the source-grid-load-storage collaborative planning model to obtain the optimal planning scheme of the target distribution network. By comprehensively calculating the inherent safety index through the power flow overload coefficient, cascading fault coefficient, and minimum node inertia, on the basis of minimizing costs, further optimize the planning of the target distribution network based on the inherent safety index to ensure that the distribution network can effectively prevent and respond to accident risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings.

[0036] Figure 1It is the implementation flowchart of the distribution network diagnosis analysis and grid framework planning method based on intrinsic safety provided by the embodiments of the present invention. Detailed implementation manners

[0037] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0038] Figure 1 It is the implementation flowchart of the distribution network diagnosis analysis and grid framework planning method based on intrinsic safety provided by the embodiments of the present invention. As Figure 1 shown, in some embodiments, the distribution network diagnosis analysis and grid framework planning method based on intrinsic safety includes:

[0039] S110, obtaining the planning information of the target distribution network;

[0040] In the embodiments of the present invention, the planning information of the target distribution network includes cost information and node information; among them, the cost information includes power generation cost, investment cost, and operation and maintenance cost. Multiplying the output data of each generator set by the corresponding cost coefficient of each type of generator set can obtain the power generation cost. Adding up costs such as the unit construction cost, unit transformation cost, energy storage construction cost, and line construction cost can obtain the investment cost. Taking the sum of the unit start-stop cost and the energy storage maintenance cost as the operation and maintenance cost. The above costs can be simply calculated based on the planning of the distribution network such as the information of the generator sets and will not be described here.

[0041] S120, establishing a source-network-load-storage collaborative planning model according to the planning information;

[0042] In some embodiments, S120 includes: establishing a source-network-load-storage collaborative planning model with the minimization of power generation cost, investment cost, and operation and maintenance cost as the goal.

[0043] In some embodiments, the objective function of the source-network-load-storage collaborative planning model is:

[0044] minF = f1 + f2 + f3 + f4 (1)

[0045] where F is the total cost, f1 is the power generation cost, f2 is the investment cost, f3 is the operation and maintenance cost, and f4 is the fault cost, which is determined by the impact of the applied random faults on the power grid operation.

[0046] In the embodiments of the present invention, based on the traditional cost minimization model, the fault cost is introduced, and then by simulating the addition of random faults, the cost minimization under faults is calculated.

[0047] S130, apply random faults to the target distribution network, and evaluate the inherent safety index of the target distribution network under faults; wherein, the inherent safety index is determined by the power flow overload coefficient, the cascading fault coefficient, and the minimum node inertia;

[0048] In the embodiments of the present invention, the N-K fault analysis of the power system is a common means in the power system planning and operation, used to verify whether the operating state of the system is within the allowable safety range after K components in the system fail and stop operating.

[0049] In some embodiments, S130 includes: applying random faults to the target distribution network; the random faults include multiple groups of N-k faults; according to the simulation results of the power grid fault simulation model under each group of N-k faults, determine the cascading faults corresponding to each group of N-k faults; wherein, the power grid fault simulation model is constructed according to the planning information of the target distribution network; according to each group of N-k faults and the cascading faults corresponding to each group of N-k faults, evaluate the inherent safety index of the target distribution network under faults.

[0050] In the embodiments of the present invention, various distribution network faults can be pre-recorded, such as bus faults, line faults, circuit breaker faults, maloperation and refusal of relay protection, etc. During fault simulation, the recorded faults are randomly combined to obtain multiple groups of N-k faults. Subsequently, each group of N-k faults is respectively applied to the power grid fault simulation model for simulation, and the cascading faults caused by it are calculated.

[0051] In the embodiments of the present invention, the power grid fault simulation model can specifically be a power grid node model for power flow calculation. It can be specifically implemented through the following steps:

[0052] 1. System data input: First, read in the power grid network data required for power flow calculation, including line parameters, node information, and initial load distribution.

[0053] 2. Fault application: Apply any one fault to the corresponding line or node, and perform power flow calculation of the system in the power grid node model.

[0054] 3. Load data acquisition: Perform load forecasting on the faulty line.

[0055] 4. Power flow calculation update: According to the results of load forecasting, update the power flow calculation according to the change of line impedance (considering four parameters of resistance, reactance, conductance, and susceptance).

[0056] 5. Overload judgment: According to the results of power flow calculation, judge whether the line or node where the fault is applied is overloaded.

[0057] 6. Cascading fault judgment: If line overload is detected and the time difference between the time point of the overload and the time point of the applied fault is less than the preset time difference, it is considered that a cascading fault has occurred, the calculation terminates, and it is judged that the system has a continuous fault.

[0058] 7. Handling of no-overload situation: If there is no line overload, apply the next fault and return to step 3 until all the faults of N - k components are applied, and all the cascading faults caused by these N - k components are obtained.

[0059] Through this algorithm process and simulation steps, the load overload situation of the power grid during the fault can be effectively monitored, and the possible cascading faults can be identified in time, so as to take measures to prevent further faults and ensure the stable operation of the power grid.

[0060] In some embodiments, the method further includes: determining the load shedding amount caused by the fault and the importance of each shed load according to each group of N - k faults and the corresponding cascading faults of each group of N - k faults; determining the loss cost according to the load shedding amount caused by the fault and the importance of each shed load; calculating the recovery cost of each group of N - k faults and the corresponding cascading faults of each group of N - k faults; taking the sum of the loss cost and the recovery cost as the fault cost.

[0061] In the embodiments of the present invention, whether it is the applied fault or the caused cascading fault, it will cause some lines or nodes to be cut out, that is, part of the load loses power supply, resulting in certain economic losses. Therefore, the load amount on each cut-out node can be defined as the load shedding amount caused by the fault, multiplied by the cost coefficient corresponding to the importance of the load connected to this node, which is the loss cost. At the same time, each type of fault corresponds to a fixed recovery cost, and by adding up the recovery costs of all faults, the total recovery cost can be obtained.

[0062] In some embodiments, according to each group of N - k faults and the corresponding cascading faults of each group of N - k faults, the inherent safety index of the target distribution network under the fault is evaluated, including: dividing the number of cascading faults by the number of N - k faults to obtain the cascading fault coefficient; calculating the power flow overload coefficient according to the cascading faults corresponding to each group of N - k faults; taking each group of N - k faults and the corresponding cascading faults of each group of N - k faults as disturbance sources, and calculating the minimum node inertia under each group of N - k faults; evaluating the inherent safety index of the target distribution network under the fault according to the cascading fault coefficient, the power flow overload coefficient, and the minimum node inertia.

[0063] In the embodiments of the present invention, each cascading fault is caused by line overload due to the applied fault. Therefore, it can be considered that one cascading fault corresponds to one overload, and dividing the number of overloaded nodes by the total number of nodes is the power flow overload coefficient.

[0064] In the embodiments of the present invention, the change in power caused by a fault can be defined as a disturbance. During the process of fault occurrence and disconnection of a node, other power nodes will be affected by this disturbance. The closer the electrical distance between each node and the fault node, the greater the impact of the disturbance received. According to the results of power flow calculation in the above-mentioned fault simulation process, the power changes of each node can be obtained, and by multiplying with a preset inertia time constant, the node inertia of each node can be obtained. The nodes with smaller node inertia are more likely to have faults after being disturbed.

[0065] In some embodiments, according to the cascading fault coefficient, power flow overload coefficient, and minimum node inertia, the inherent safety index of the target distribution network under faults is evaluated, including: after normalizing the cascading fault coefficient, power flow overload coefficient, and minimum node inertia, performing weighted summation to obtain the inherent safety index of the source-network-load-storage collaborative planning model under faults.

[0066] In the embodiments of the present invention, the weights of each comprehensive energy consumption index are all preset values, which are not limited herein.

[0067] S140. Optimize the source-network-load-storage collaborative planning model according to the inherent safety index to obtain the optimal planning scheme of the target distribution network.

[0068] In some embodiments, S140 includes: aiming at minimizing the power generation cost, investment cost, operation and maintenance cost and maximizing the inherent safety, using a multi-objective particle swarm optimization algorithm to optimize the source-network-load-storage collaborative planning model to obtain the optimal planning scheme of the target distribution network.

[0069] In the embodiments of the present invention, the multi-objective particle swarm optimization algorithm is an optimization algorithm based on swarm intelligence, which is used to solve problems with multiple optimization objectives. Its steps are as follows:

[0070] Initialize the particle swarm: Randomly initialize the positions and velocities of a group of particles. Each particle represents a potential solution to the problem.

[0071] Individual best and global best: Assign initial individual best positions (pbest) and global best positions (gbest) to each particle.

[0072] External archive: Initialize an external archive for storing non-dominated solutions found during the execution of the algorithm.

[0073] Iterative optimization: Update the particle velocity and position: Update the particle velocity and position according to the current velocity of the particle, individual best position, and global best position.

[0074] Update individual best: Compare the new position of each particle with its individual best position. If the new position is better, update the individual best.

[0075] Update the external archive: Add the newly discovered non-dominated solutions to the external archive, and maintain the size of the archive according to a certain mechanism (such as crowding distance).

[0076] Select the global best: Select a global best position for each particle from the external archive. This can be done in various ways, such as random selection, selection based on crowding distance, etc.

[0077] Check the termination condition: Check whether the termination condition is met, such as reaching the maximum number of iterations, the quality of the solution meets the requirements, etc. If the condition is met, the algorithm ends; otherwise, return to the iterative optimization step.

[0078] Output the result: After the algorithm ends, the external archive stores a set of approximate non-dominated solution sets of the multi-objective optimization problem, and these solution sets can be provided to decision-makers for further analysis and decision-making.

[0079] In the iterative optimization process of the multi-objective particle swarm of the present invention, cost and security will affect each other. First, calculate the source-network-load-storage collaborative planning model with the minimum cost without applying faults. After applying faults, perform security calculations. The particle swarm algorithm selects the optimization result with the highest security to obtain a new distribution network planning scheme. On the basis of this scheme, considering the cost increase caused by applying faults, perform cost minimization calculations again to obtain a new optimization result. Through continuous iteration of the particle swarm algorithm in the above process, the final result takes into account both low cost and high security.

[0080] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0081] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0082] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0083] In the embodiments provided by the present invention, it should be understood that the disclosed device / electronic device and method can be implemented in other ways. For example, the device / electronic device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0084] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] In addition, each functional unit in various embodiments of the present invention can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0086] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned method embodiments of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0087] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for diagnosing, analyzing and planning the grid framework of a distribution network based on intrinsic safety, characterized in that Including: Obtain the planning information of the target distribution network; Establish a source-network-load-storage collaborative planning model according to the planning information; Apply random faults to the target distribution network and evaluate the inherent safety index of the target distribution network under faults; wherein, the inherent safety index is determined by the power flow overload coefficient, the cascading fault coefficient, and the minimum node inertia; Optimize the source-network-load-storage collaborative planning model according to the inherent safety index to obtain the optimal planning scheme of the target distribution network; Apply random faults to the target distribution network and evaluate the inherent safety index of the target distribution network under faults, including: Apply random random faults to the target distribution network; the random faults include multiple groups of N-k faults; Determine the cascading faults corresponding to each group of N-k faults according to the simulation results of the power grid fault simulation model under each group of N-k faults; wherein, the power grid fault simulation model is constructed according to the planning information of the target distribution network; Evaluate the inherent safety index of the target distribution network under faults according to each group of N-k faults and the cascading faults corresponding to each group of N-k faults; Evaluate the inherent safety index of the target distribution network under faults according to each group of N-k faults and the cascading faults corresponding to each group of N-k faults, including: Divide the number of cascading faults by the number of N-k faults to obtain the cascading fault coefficient; Calculate the power flow overload coefficient according to the cascading faults corresponding to each group of N-k faults; Use each group of N-k faults and the cascading faults corresponding to each group of N-k faults as disturbance sources to calculate the minimum node inertia under each group of N-k faults; Evaluate the inherent safety index of the target distribution network under faults according to the cascading fault coefficient, the power flow overload coefficient, and the minimum node inertia.

2. The method for diagnosing, analyzing and planning the grid structure of a distribution network based on intrinsic safety according to claim 1, wherein, Establish a source-network-load-storage collaborative planning model according to the planning information, including: Establish a source-network-load-storage collaborative planning model with the goal of minimizing the power generation cost, investment cost, and operation and maintenance cost.

3. The method for diagnosing and analyzing a distribution network and planning a network framework based on intrinsic safety according to claim 2, wherein The objective function of the source-network-load-storage collaborative planning model is: minF = f1 + f2 + f3 + f4 Wherein, F is the total cost, f1 is the power generation cost, f2 is the investment cost, f3 is the operation and maintenance cost, and f4 is the fault cost, which is determined by the impact of the applied random faults on the operation of the power grid.

4. The method for diagnosing and analyzing a distribution network and planning a network framework based on intrinsic safety according to claim 1, wherein The method further includes: Determine the load shedding amount caused by the faults and the importance of each shed load according to each group of N-k faults and the cascading faults corresponding to each group of N-k faults; Determine the loss cost according to the load shedding amount caused by the faults and the importance of each shed load; Calculate the restoration cost of each group of N-k faults and the cascading faults corresponding to each group of N-k faults; Take the sum of the loss cost and the restoration cost as the fault cost.

5. The method for diagnosing and analyzing a distribution network and planning a network framework based on intrinsic safety according to claim 4, wherein Evaluate the inherent safety index of the target distribution network under faults according to the cascading fault coefficient, the power flow overload coefficient, and the minimum node inertia, including: Normalize the cascading fault coefficient, the power flow overload coefficient, and the minimum node inertia, and then perform weighted summation to obtain the inherent safety index of the source-network-load-storage collaborative planning model under faults.

6. The method for diagnosing, analyzing and planning the grid framework of a distribution network based on intrinsic safety according to claim 1, wherein Optimize the source-network-load-storage collaborative planning model according to the inherent safety index to obtain the optimal planning scheme of the target distribution network, including: Aiming at minimizing the power generation cost, investment cost, operation and maintenance cost and maximizing the inherent safety, a multi-objective particle swarm algorithm is adopted to optimize the source-network-load-storage collaborative planning model, and an optimal planning scheme for the target distribution network is obtained.

7. 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 computer program, the steps of the method for diagnosing and analyzing a distribution network based on inherent safety and grid framework planning according to any one of claims 1 to 6 above are implemented.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for diagnosing and analyzing a distribution network based on inherent safety and grid framework planning according to any one of claims 1 to 6 above are implemented.

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