Node Sensitivity Analysis Method for Power Quality Governance of Distributed Photovoltaic Access Distribution Network

Abstract

The invention discloses a node sensitivity analysis method for distributed photovoltaic access distribution network power quality management. The technical scheme of the invention comprises the following steps: an optimization objective function of node voltage deviation sum, current total harmonic distortion rate and installation cost is proposed; A multi-objective optimization model for site selection and volume determination of composite energy storage devices is constructed; Each node is equipped with a composite energy storage device with the same capacity, and the voltage deviation and current total harmonic distortion rate of each node are obtained by power flow calculation; Particle Swarm Optimization (PSO) is used to set the size of particle swarm and the number of iterations; Theinstallation position and capacity of the composite energy storage device are obtained by solving the problem. The invention utilizes node sensitivity analysis method to preprocess nodes to reduce the number of calculation nodes, thereby greatly reducing the calculation amount and improving the optimization efficiency. At the same time, the improved particle swarm optimization algorithm with adaptive dynamic weights is used to dynamically change the weight coefficients according to the difference between the objective function value and the global average value, which improves the global optimization speed.

Description

technical field [0001] The invention relates to the field of power quality control of distribution networks, in particular to a node sensitivity analysis method for power quality control after high power density distributed photovoltaics are connected to the distribution network. Background technique [0002] At present, the world's energy is exhausted, energy transformation is imperative, and high-power-density distributed photovoltaic power generation is developing rapidly. However, its own fluctuation and intermittent characteristics and the access of a large number of power electronic devices will lead to serious voltage quality problems in the distribution network. Studies have shown that configuring energy storage devices with a certain capacity at corresponding nodes can achieve the goal of improving power quality. The difference in the access location and capacity of the energy storage system has a great impact on the governance of power quality. Therefore, how to u...

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Problems solved by technology

[0003] In recent years, there have been some scientific research results on the optimal installation location and installation capacity of the energy storage system. Some scholars have proposed an optimization algorithm based on genetic algorithms, and added capacity correction links to the algorithm, thereby greatly saving installation costs; there are also some Scholars use the combination of particle swarm optimization and genetic algorithm cross-mutation operations to improve the speed and efficiency of the solution; but overall, the current solution algorithms for the optimal installation location and installation capacity of the energy storage system are only carried out in the algorithm itself. The improvement only improves the solution rate of the algorithm itself, but does not consider the influence of the complex structure of the distribution network itself, the large number of nodes, and the large amount of calculation and low solution efficiency.

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