Multi-objective voltage control method for distribution network based on fuzzy multi-agent

Abstract

The present invention relates to a distribution network multi-target voltage control system based on fuzzy multi-agent. The present invention utilizes the advantages of multi-agent technology to propose a fuzzy multi-agent based distribution network multi-target voltage control system. On the one hand, the problem of feeder power congestion is eliminated through network reconfiguration; on the other hand, through coordinated control of shunt capacitor bank (Shunt capacitor bank, SCB), transformer on-line tap change (on-line tap change, transformer on-load tap changer OLTC) , with the help of network reconfiguration, the voltage of the distribution network is maintained within the normal range. This method is a hybrid centralized-decentralized distributed control strategy, which has the characteristics of good robustness, flexibility, speed and reliability.

Description

technical field [0001] The invention relates to a multi-objective voltage control method of distribution network based on fuzzy multi-agents. Background technique [0002] In order to alleviate the seriousness of global environmental pollution and the shortage of traditional fossil fuels, the power industry is transforming towards green and low-carbon. Distributed energy generation has the characteristics of flexibility, economy, and environmental protection. If properly configured, it can effectively reduce network losses and improve power quality. It is an important step to solve the contradiction between energy utilization and environmental protection. At present, distributed generation (Distributed Generation, DG) technology, especially renewable energy (Renewable Energy Sources, RES) power generation technology is developing rapidly, and the penetration rate of DG in the distribution network is gradually increasing. The combination of DG and power grid is conducive to ...

AI Technical Summary

Problems solved by technology

However, this control method mainly has the following problems: 1) Renewable energy generation and load forecast data are required, and the accuracy of the forecast data has a greater impact on the effectiveness of the control strategy; 2) Network topology signals are required A large amount of data such as the state quantity of each node and the parameters of the adjustment equipment are processed in a unified manner, which leads to complex calculations and long calculation times, which cannot ensure rapid voltage control in emergencies; 3) There are convergence problems in the optimization calculation method; 4) Reliable The communication line transmits the signal, and the failure of the communication line may lead to the instability of the whole system

However, the existing multi-intelligence-based power system reactive power and voltage control technology mostly focuses on the system's control architecture, coordination and cooperation mechanism, and communication mechanism, without giving specific decision-making algorithms and coordination strategies between agents.

In addition, the research on MAS-based voltage and other aspects of the distribution network is less mature, and the specific coordinated voltage regulation strategy needs to be deepened.

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