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Comparison between deterministic and meta-heuristic methods applied to ancillary services dispatch

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Resumo(s)

This paper proposes two meta-heuristics (Genetic Algorithm and Evolutionary Particle Swarm Optimization) for solving a 15 bid-based case of Ancillary Services Dispatch in an Electricity Market. A Linear Programming approach is also included for comparison purposes. A test case based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is used to demonstrate that the use of meta-heuristics is suitable for solving this kind of optimization problem. Faster execution times and lower computational resources requirements are the most relevant advantages of the used meta-heuristics when compared with the Linear Programming approach.

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Artificial intelligence techniques Ancillary services dispatch Electricity markets Evolutionary particle swarm optimization Genetic algorithm Linear programming

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Springer Berlin Heidelberg

Licença CC

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