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Weighted sum approach using Parallel Particle Swarm Optimization to Solve Multi-objective Energy Scheduling
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Orientador(es)
Resumo(s)
This paper presents a Particle Swarm Optimization
(PSO) methodology to solve the problem of energy resource
management with high penetration of Distributed Generation
(DG) and Electric Vehicles (EVs), based in multi-objective
optimization. The high penetration of unpredictable DG, results
in the increase of the operation cost, due to the additional
constraints on the system, and has a direct influence on the
reducing of carbon dioxide (CO2) emissions. The proposed
methodology consists in a multi-objective function, in which is
intended to maximize the profit, corresponding to the difference
between the income and operating costs, and minimize CO2
emissions. In this case study it was considered a real Spanish
electric network, from the city of Zaragoza, applied to the
productions and consumption values expected in 2030. This
network is constituted by 1300 EVs and 70% DG penetration of
its total installed capacity.
Descrição
Palavras-chave
Energy Resources Management CO2 Emissions Particle Swarm Optimization Multi-Objective
Contexto Educativo
Citação
Editora
Institute of Electrical and Electronics Engineers