A scatter search heuristic for the optimal location, sizing and contract pricing of distributed generation in electric distribution systems
ABSTRACT: In this paper we present a scatter search (SS) heuristic for the optimal location, sizing and contract pricing of distributed generation (DG) in electric distribution systems. The proposed optimization approach considers the interaction of two agents: (i) the potential investor and owner o...
| Autores: | , |
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| Tipo de documento: | artigo |
| Estado: | Versão publicada |
| Data de publicação: | 2017 |
| País: | Colombia |
| Recursos: | Universidad de Antioquia |
| Repositório: | Repositorio UdeA |
| Idioma: | inglês |
| OAI Identifier: | oai:bibliotecadigital.udea.edu.co:10495/13206 |
| Acesso em linha: | http://hdl.handle.net/10495/13206 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Bilevel programming Distributed generation (DG) Evolutionary algorithms Scatter search (SS) Algoritmos evolutivos Programación binivel |
| Resumo: | ABSTRACT: In this paper we present a scatter search (SS) heuristic for the optimal location, sizing and contract pricing of distributed generation (DG) in electric distribution systems. The proposed optimization approach considers the interaction of two agents: (i) the potential investor and owner of the DG, and (ii) the Distribution Company (DisCo) in charge of the operation of the network. The DG owner seeks to maximize his profits from selling energy to the DisCo, while the DisCo aims at minimizing the cost of serving the network demand, while meeting network constraints. To serve the expected demand the DisCo is able to purchase energy, through long-term bilateral contracts, from the wholesale electricity market and from the DG units within the network. The interaction of both agents leads to a bilevel programming problem that we solve through a SS heuristic. Computational experiments show that SS outperforms a genetic algorithm hybridized with local search both in terms of solution quality and computational time. |
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