Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/6784
Title: Multi-objective energy storage power dispatching using plug-in vehicles in a smart-microgrid.
Authors: Coelho, Vitor Nazário
Coelho, Igor Machado
Coelho, Bruno Nazário
Cohen, Miri Weiss
Reis, Agnaldo José da Rocha
Silva, Sidelmo Magalhães
Souza, Marcone Jamilson Freitas
Fleming, Peter J.
Guimarães, Frederico Gadelha
Keywords: Microgrids
Power dispatching
Energy storage management
Plug-in electric vehicle
Probabilistic forecast
Issue Date: 2016
Citation: COELHO, V. N. et al. Multi-objective energy storage power dispatching using plug-in vehicles in a smart-microgrid. Renewable Energy, v. 89, p. 730-742, 2016. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0960148115305000>. Acesso em: 11 jul. 2016.
Abstract: This paper describes a multi-objective power dispatching problem that uses Plug-in Electric Vehicle (PEV) as storage units.We formulate the energy storage planning as a Mixed-Integer Linear Programming (MILP) problem, respecting PEV requirements, minimizing three different objectives and analyzing three different criteria. Two novel cost-to-variability indicators, based on Sharpe Ratio, are introduced for analyzing the volatility of the energy storage schedules. By adding these additional criteria, energy storage planning is optimized seeking to minimize the following: total Microgrid (MG) costs; PEVs batteries usage; maximum peak load; difference between extreme scenarios and two Sharpe Ratio indices. Different scenarios are considered, which are generated with the use of probabilistic forecasting, since prediction involves inherent uncertainty. Energy storage planning scenarios are scheduled according to information provided by lower and upper bounds extracted from probabilistic forecasts. A MicroGrid (MG) scenario composed of two renewable energy resources, a wind energy turbine and photovoltaic cells, a residential MG user and different PEVs is analyzed. Candidate non-dominated solutions are searched from the pool of feasible solutions obtained during different Branch and Bound optimizations. Pareto fronts are discussed and analyzed for different energy storage scenarios. Perhaps the most important conclusion from this study is that schedules that minimize the total system cost may increase maximum peak load and its volatility over different possible scenarios, therefore may be less robust.
URI: http://www.repositorio.ufop.br/handle/123456789/6784
ISSN: 09601481
metadata.dc.rights.license: O Periódico Renewable Energy concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3914200800652
Appears in Collections:DECAT - Artigos publicados em periódicos

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