JOURNAL ARTICLE

Recurrent multi‐objective differential evolution approach for reactive power management

Himmat SinghLaxmi Srivastava

Year: 2015 Journal:   IET Generation Transmission & Distribution Vol: 10 (1)Pages: 192-204   Publisher: Institution of Engineering and Technology

Abstract

This study proposes a novel recurrent multi‐objective differential evolution (RMODE) algorithm to solve the constrained reactive power management (RPM) problem, which is a non‐linear, multi‐objective optimisation problem. Minimisation of total active power loss and improvement of voltage profile are considered as the objectives of the RPM problem. For RPM, generator bus voltage magnitudes, transformer tap settings and reactive power of capacitor/reactor are taken as the decision variables. In the proposed RMODE algorithm, the multi‐objective differential evolution (MODE) algorithm has been applied repeatedly using the available Pareto‐optimal solutions and re‐initialising the remaining population. Thus, for each next cycle of the RMODE, the better values of best compromise solution have been obtained. Effectiveness of the proposed RMODE algorithm has been demonstrated for RPM in the standard IEEE‐30 bus system and a practical 75‐bus Indian system. Compared with multi‐objective particle swarm optimisation (PSO), genetic algorithm toolbox for multi‐objective optimisation, MODE and reported results using modified differential evolution and classical PSO, the proposed approach seems to be a promising alternative approach for solving RPM problem in practical power system.

Keywords:
Differential evolution Differential (mechanical device) AC power Computer science Power (physics) Engineering Artificial intelligence Physics

Metrics

24
Cited By
1.50
FWCI (Field Weighted Citation Impact)
30
Refs
0.87
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Optimal Power Flow Distribution
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Microgrid Control and Optimization
Physical Sciences →  Engineering →  Control and Systems Engineering
Power System Optimization and Stability
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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