Quantum Evolutionary Algorithms for Unit Commitment and OPF
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Providing clean, reliable, secure and economic Electric Power with due regard to the quality and ecology is primary objective of power systems' operation. Two important problems involved in fulfilling this objective are Unit Commitment and the OPF. These are complex problems involving considerations that are nightmarish for researchers and demand complex algorithms for solving them. QEA is a population-based probabilistic EA that integrates concepts from quantum computing for higher representation power and EAs for robust search. This work presents QEA based meta-heuristics for Economic Load D...
Providing clean, reliable, secure and economic Electric Power with due regard to the quality and ecology is primary objective of power systems' operation. Two important problems involved in fulfilling this objective are Unit Commitment and the OPF. These are complex problems involving considerations that are nightmarish for researchers and demand complex algorithms for solving them. QEA is a population-based probabilistic EA that integrates concepts from quantum computing for higher representation power and EAs for robust search. This work presents QEA based meta-heuristics for Economic Load Dispatch, Reactive power Dispatch, Optimal Power Flow, Dynamic Economic Dispatch and Unit Commitment problems. This work also presents specially designed problem specific heuristics for improving algorithmic performance. The contributions of this work are twofold viz. development of effective and versatile optimization strategies and solving more realistic and comprehensive problem formulations using these strategies. The Techniques presented are quite general and can be easily adapted with advantage in variety of other optimization problems in power systems and other real life systems.
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