Evaluation of different initial solution algorithms to be used in theheuristics optimization to solve the energy resource scheduling insmart grids

• Autor(a) principal: Sousa, Tiago
• Data de Publicação: 2016
• Outros Autores: Morais, Hugo, Castro, Rui, Vale, Zita
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/9394
• topic: Electric vehicles; Hybrid metaheuristic; Optimal power scheduling; Simulated annealing; Virtual power player

Over the last years, an increasing number of distributed resources have been connected to the powersystem due to the ambitious environmental targets, which resulted into a more complex operation ofthe power system. In the future, an even larger number of resources is expected to be coupled which willturn the day-ahead optimal resource scheduling problem into an even more difficult optimization prob-lem. Under these circumstances, metaheuristics can be used to address this optimization problem. Anadequate algorithm for generating a good initial solution can improve the metaheuristic’s performanceof finding a final solution near to the optimal than using a random initial solution. This paper proposestwo initial solution algorithms to be used by a metaheuristic technique (simulated annealing). Thesealgorithms are tested and evaluated with other published algorithms that obtain initial solution. Theproposed algorithms have been developed as modules to be more flexible their use by other metaheuris-tics than just simulated annealing. The simulated annealing with different initial solution algorithms hasbeen tested in a 37-bus distribution network with distributed resources, especially electric vehicles. Theproposed algorithms proved to present results very close to the optimal with a small difference between0.1%. A deterministic technique is used as comparison and it took around 26 h to obtain the optimal one.On the other hand, the simulated annealing was able of obtaining results around 1 min.