Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1360
Título: Distributed energy resource short-term scheduling using signaled particle swarm optimization
Autor: Soares, João
Silva, Marco
Sousa, Tiago
Vale, Zita
Morais, H.
Palavras-chave: Distributed energy resource scheduling
Mixed integer non-linear programming
Particle swarm optimization
Short-term scheduling
Data: 2012
Editora: Elsevier
Relatório da Série N.º: Energy; Vol. 42, Issue 1
Resumo: Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.
URI: http://hdl.handle.net/10400.22/1360
ISSN: 0360-5442
Versão do Editor: http://www.sciencedirect.com/science/article/pii/S0360544212002137
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