CN-121984070-A - Method for regulating and optimizing running state of power distribution network containing distributed power supply and flexible load

CN121984070ACN 121984070 ACN121984070 ACN 121984070ACN-121984070-A

Abstract

The invention discloses a method for regulating and optimizing the running state of a power distribution network with a distributed power supply and a flexible load, which comprises the following steps of obtaining the topological structure and the running parameters of the power distribution network, and constructing a power distribution network running state regulating and controlling model according to the topological structure and the running parameters; on the basis of the power distribution network running state regulation model, a traditional knowledge acquisition sharing algorithm is improved, a search individual is guided to approach a current candidate optimal solution along a spiral track by introducing a spiral updating strategy, and the improved knowledge acquisition sharing algorithm is utilized to carry out iterative solution on the running state regulation model, so that running optimization configuration of the power distribution network is obtained. The method and the system remarkably improve the global searching capability and the local convergence precision of the algorithm, thereby being capable of rapidly and accurately obtaining the operation optimization configuration and enhancing the stability, the adaptability and the overall operation performance of the power distribution network when coping with the renewable energy source output fluctuation and the load change.

Inventors

Xiong Guojiang
ZHAO HUIQIN
LI ZHENGYONG

Assignees

贵州大学

Dates

Publication Date: 20260505
Application Date: 20260126

Claims (10)

1. The method for regulating and optimizing the running state of the power distribution network with the distributed power supply and the flexible load is characterized by comprising the following steps of: Acquiring a topological structure and operation parameters of a power distribution network, and constructing a power distribution network operation state regulation model comprising voltage deviation constraint, power balance constraint, energy storage operation constraint and flexible load adjustable constraint according to the topological structure and the operation parameters; On the basis of the power distribution network running state regulation model, a traditional knowledge acquisition sharing algorithm is improved, and a search individual is guided to approach a current candidate optimal solution along a spiral track by introducing a spiral updating strategy; and carrying out iterative solution on the operation state regulation model by utilizing the improved knowledge acquisition sharing algorithm to obtain the operation optimization configuration of the power distribution network.
2. The method of claim 1, wherein the power distribution network comprises a flexible load, a distributed power source, and an energy storage system, wherein the flexible load comprises a translatable load and a reducible load.
3. The method of claim 1, wherein the process of constructing a power distribution network operational state regulation model includes constructing a composite objective function targeting a composite weighted minimization of branch active loss, user-side disturbance level, renewable energy unavailability, and energy storage device circulation loss.
4. The method according to claim 3, wherein the process of constructing the power distribution network running state regulation model further comprises the step of setting a constraint of a parameter value range for the comprehensive objective function, wherein the wind power consumption does not exceed the constraint of the maximum wind power output, the photovoltaic consumption does not exceed the constraint of the maximum photovoltaic output, the constraint that the charge and discharge power of the energy storage system is between the minimum exchange power and the maximum exchange power, the constraint that the state of charge of the energy storage system is between the minimum state of charge and the maximum state of charge, the constraint that the voltage amplitude of each node is between the preset lower limit and the preset upper limit, and the constraint of power conservation of the system is met.
5. The method according to claim 1, wherein improving a traditional knowledge acquisition sharing algorithm comprises introducing a spiral update mechanism, in particular: embedding a dynamically contracted spiral function in a position updating equation of the population individuals; guiding the searched individual to move along the spiral track to the current optimal solution direction through the spiral function; the spiral shape parameters are set at the initial stage of algorithm iteration to enable individuals to explore in a large range, and the spiral shape parameters are adjusted at the later stage of the algorithm iteration to shrink the spiral shape, so that the population is driven to be close to the optimal individuals.
6. The method of claim 1, wherein solving the model using the improved knowledge acquisition sharing algorithm comprises: Constructing an initial population, wherein each individual corresponds to a power distribution network operation scheme comprising distributed power supply output, energy storage charge and discharge power, translatable load time period and reducible load proportion; calculating the fitness value of each individual according to the comprehensive objective function; Executing an iterative process of a knowledge acquisition sharing algorithm comprising the spiral updating mechanism, and updating the positions of population individuals; when the preset maximum iteration times are reached, outputting the operation optimization configuration corresponding to the individual with the optimal fitness.
7. The method of claim 1, further comprising comparing the optimal configuration with a solution of a conventional knowledge acquisition sharing algorithm after the operation optimal configuration is obtained, wherein performance indexes based on the comparison verification comprise convergence speed, voltage deviation level, flexible load response effect and distributed power supply digestion capability, the voltage deviation level is measured by voltage deviation rate and voltage fluctuation rate, the voltage deviation rate is calculated according to square sum of differences between voltage amplitudes and reference voltages of all nodes and the number of nodes, and the voltage fluctuation rate is calculated according to square sum of voltage variation of nodes and the number of nodes between all adjacent time periods.
8. A computer device comprising a memory, a processor and a computer program stored on the memory, characterized in that the processor executes the computer program to carry out the steps of the method according to any one of claims 1-7.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any of claims 1-7.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, realizes the steps of the method according to any one of claims 1-7.

Description

Method for regulating and optimizing running state of power distribution network containing distributed power supply and flexible load Technical Field The invention belongs to the technical field of operation and control of power systems, and particularly relates to a method for regulating and optimizing the operation state of a power distribution network comprising a distributed power supply and a flexible load. Background Along with the continuous improvement of the permeability of renewable energy sources in a power distribution network, distributed power sources such as distributed photovoltaic and wind power generation, and coordinated control of an energy storage system and a flexible load become key technical directions for improving the running stability of the power distribution network and enhancing the adaptability of the system to volatility. Through the cooperative regulation and control of multiple types of resources, cross-period and cross-region power balance and energy optimization are realized, and the method has important significance in improving the voltage quality of a power distribution network, enhancing the toughness of the system and promoting the efficient consumption of new energy. However, the access of high proportion of distributed energy makes the distribution network operation scheduling problem increasingly complex. The distributed power output has intermittence and randomness, and the peak-to-valley difference of the load curve is obvious, so that the scheduling model has the characteristics of strong nonlinearity, high dimensionality, multiple constraints and uncertainty. In this context, conventional optimized scheduling methods face significant challenges. On the one hand, the traditional numerical optimization method based on the accurate mathematical model is highly dependent on the accuracy of system parameters, and when the uncertainty and random factors in actual operation are dealt with, the solving error is large, and the robustness and the practicability of an optimization result are difficult to ensure. On the other hand, although the standard element heuristic algorithm such as the particle swarm optimization algorithm can handle the nonlinear problem to a certain extent, when solving the complex optimization model with high dimension and multiple peaks, the problem of unbalanced global exploration and local development capacity is commonly existed, and the problem of unbalanced global exploration and local development capacity is easy to sink into the local optimal solution too early, so that the convergence precision is insufficient, the algorithm stability is poor, and the practical requirements of the power distribution network on the accuracy and reliability of the dispatching strategy are difficult to meet. Therefore, a method for controlling and optimizing the operation state of the power distribution network with the distributed power supply and the flexible load is needed to be provided. Disclosure of Invention In order to solve the technical problems, the invention provides a method for regulating and optimizing the running state of a power distribution network comprising a distributed power supply and a flexible load, which comprises the steps of firstly obtaining the topological structure and the running parameters of the power distribution network, constructing an objective function and constraint conditions based on the characteristics of the power distribution network comprising the flexible load, and forming a power distribution network running optimization model; and then solving the high-dimensional, nonlinear and multiparameter coupled optimization model by adopting an improved optimization algorithm introducing a spiral updating strategy. The population is guided to approach the optimal solution along the continuous shrinkage track by the spiral updating mechanism, so that the algorithm maintains stronger global searching capability and improves optimizing precision, convergence speed and operation stability, thereby realizing efficient regulation and control on the running state of the power distribution network. The invention provides a method for regulating and optimizing the running state of a power distribution network with a distributed power supply and a flexible load, which comprises the following steps: Acquiring a topological structure and operation parameters of a power distribution network, and constructing a power distribution network operation state regulation model comprising voltage deviation constraint, power balance constraint, energy storage operation constraint and flexible load adjustable constraint according to the topological structure and the operation parameters; On the basis of the power distribution network running state regulation model, a traditional knowledge acquisition sharing algorithm is improved, and a search individual is guided to approach a current candidate optimal solution along a spiral track by intr