Vale, ZitaRamos, CarlosFaria, PedroSoares, JoãoCanizes, BrunoTeixeira, JoaquimKhodr, H. M.2013-05-132013-05-132010978-3-642-13021-2978-3-642-13022-90302-9743http://hdl.handle.net/10400.22/1562This 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.engArtificial intelligence techniquesAncillary services dispatchElectricity marketsEvolutionary particle swarm optimizationGenetic algorithmLinear programmingbook part2013-04-1710.1007/978-3-642-13022-9_73