Sistema de otimização de resposta à demanda para redes elétricas inteligentes
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Demand-Side Management (DSM) is the planning and implementation of activities designed to influence customer use of electricity in a way that will produce desired changes in the utility’s load shape. Although it has been discussed since the mid-1980s, the advent of the smart grid, through a better integration between information and communication technologies with electrical power systems, brings both opportunities and challenges for the DSM, yielding an effective extension of the power utility activities to the customer and opening a new dimension to the planning and operation of distribution networks. Detailed analysis when planning DSM programs are crucial, because the utility intends to achieve technical and economic benefits e.g. the postponement of investment and congestion relieve, but it does not wish to lose revenue unnecessarily. To assist utilities in planning for price-based demand response programs (an approach to DSM), in this dissertation an optimization system focusing on the selection of residential customers in a distribution feeder is proposed. Two approaches were developed: hybrid and heuristic. The hybrid approach featured two different techniques, Optimal Power Flow for bus-based reduction estimation followed by Binary Particle Swarm Optimization (BPSO) for customers’ selection via global or bus-bases optimization. The heuristic approach was performed only with BPSO. The optimization system was tested using residential load curves, a radial distribution feeder data, customers’ elasticity matrixes as well as a Time-Of-Use (TOU) tariff. The main results show that the system can be of great value supporting power utilities’ analysis and optimization of price-based demand response programs. The hybrid approach via bus-based optimization showed the best compromisse between runtime and the reduction objective achieval. The heuristic approach showed better results regarding the achieval of the reduction objective, but with high computational cost which may prevent its application on power utilities. The different developed approaches present an overview on the use of optimization techniques to customers selection and allow a glimpse of future applications. Key-words: Demand-Side Management. Demand Response. Smart Grid. Binary Optimization. Hybrid Optimization. Optimal Power Flow.