Reactive power and voltage control based on general quantum genetic algorithms

Publication: Research - peer-reviewJournal article – Annual report year: 2009

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This paper presents an improved evolutionary algorithm based on quantum computing for optima l steady-state performance of power systems. However, the proposed general quantum genetic algorithm (GQ-GA) can be applied in various combinatorial optimization problems. In this study the GQ-GA determines the optimal settings of control variables, such as generator voltages, transformer taps and shunt VAR compensation devices for optimal reactive power and voltage control of IEEE 30-bus and 118-bus systems. The results of GQ-GA are compared with those given by the state-of-the-art evolutionary computational techniques such as enhanced GA, multi-objective evolutionary algorithm and particle swarm optimization algorithms, as well as the classical primal-dual interior-point optimal power flow algorithm. The comparison demonstrates the ability of the GQ-GA in reaching more optimal solutions.
Original languageEnglish
JournalExpert Systems with Applications
Issue number3
Pages (from-to)6118-6126
StatePublished - 2009
CitationsWeb of Science® Times Cited: 26


  • Genetic algorithm, Reactive power control, Quantum mechanics computation, Steady-state performance, Meta-heuristic techniques
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ID: 4347123