Volt/VAr control in distribution systems by fuzzy multiobjective and particle swarm

Abstract

This paper presents the optimal dispatch for the under load tap changer (ULTC) of a substation transformer, substation capacitors, and feeder capacitors for volt/VAr control in a distribution system. Three objectives of interest in the problem consist of energy loss, total capacitor kVAr to be switched on, and total number of daily switching operations of the ULTC and all capacitors. The optimization problem is subjected to power flow equations, voltage limits, and maximum switching operations for the ULTC and the capacitors. All the objectives are fuzzified using a trapezoidal membership function and are integrated to represent the fuzzy decision value. Fuzzy multiobjective and particle swarm optimization are employed to determine the optimal dispatch schedule that provides the best compromise among all the objectives. The methodology is demonstrated by a 29-bus distribution system of Provincial Electricity Authority (PEA), Thailand.

Evaluation of Conservation Voltage Reduction (CVR) on a National Level

“…There have been numerous proposed methods [8][9][10][11][12][13][14], numerous studies of deployed systems [13][14][15][16][17][18][19][20], and many vendors offer CVR based systems [23][24][25][26]. For the purposes of this analysis, a CVR scheme that has been published in the IEEE Transactions on Power Systems and is openly available has been selected [11].…”

Volt/VAR Optimization: A Survey of Classical and Heuristic Optimization Methods

“…References [145]- [147] formulate a fuzzy-linear programming-based reactive power/voltage control, combining the reliability and speed characteristics of linear programming with fuzzy set theory's ability to more efficiently depict the realistic system objective and constraint functions, leading to a more practical solution of the problem. Other examples of hybrid methods incorporating fuzzy set theory or fuzzy logic are the fuzzydynamic programming approach presented in [148], and the fuzzy-PSO multi-objective algorithm presented in [149].…”

Hybrid intelligent technique for voltage/VAR control in power systems

“…Some papers focus on voltage and reactive power optimisation by improving VVO techniques. For instance, some authors propose the AI techniques for VVO considering different optimisation methods such as fuzzy logic control with multi-objective techniques and particle swarm optimisation [11]; MAS control with genetic algorithms [12].…”