Planejamento multiobjetivo otimizado de recursos energéticos distribuídos aplicando o método strength pareto evolutionary algorithm 2

• Autor(a) principal: Ney, Rafael Crochemore
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• Texto Completo: http://repositorio.ufsm.br/handle/1/22477
• topic: Planejamento multiobjetivo; Recursos energéticos distribuídos; Método Strength Pareto Evolutionary Algorithm 2; Papel ativo das distribuidoras na geração distribuída; Multiobjective planning; Distributed energy resources; Strength Pareto Evolutionary Algorithm 2 Method; Active role of distribution companies in distributed generation; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

The diffusion of distributed energy resources (DER) in the electric energy distribution systems in Brazil, outcomes in the perception, through the Electric Sector agents, of a set of benefits that these technologies promote to the Distribution Companies and consumers and DER investors. However, several regulatory and market issues need to be improved to leverage these results. For this purpose, the basic DER definitions of allocation and maximum sizing, are essential, so that these disseminating benefits among stakeholders. The National Electrical Energy Agency (ANEEL) has been improving the national regulatory model over the last few years, to equate the Distributed Generation penetration level in the Brazilian energy matrix. Even with all the efforts made so far, the development of more efficient business models remains limited. These models require improvements that incorporate the technical characteristics of the grids, economic, legal, and environmental aspects, as well as incentive policies that seek the economic and financial balance of those companies. Besides, in this dissertation, it is presented a methodology to be aggregated to the planning for Distribution Companies aiming at evaluating the location, sizing and type of DER using the multiobjective method Strength Pareto Evolutionary Algorithm 2 (SPEA2), through an integration between the computational tools, Matlab and OpenDSS. In this study, multi-objective optimizations are made between technical (Technical Losses, Voltage Variation, Injected Energy), economic (Investment, O&M Cost, Expense with CUSD) and environmental (CO2 Emission) aspects, which will be the basis for defining the best solutions for the agents. Also, the optimizations aim at minimizing the above mentioned Objective Functions (OF), and will be subject to the restrictions of minimum and maximum voltage limits, and analyzed system conductors’ overload. Also, are determined the buses or nodes of the Distribution System with the highest level of service´s critical before the entry of the connection of the Distributed Generation Systems. For these buses, differentiated degrees of incentive will be defined through the Distribution Companies participation in the DER Investor Initial Investment and discount in the distribution system´s tariffs for use (TUSD). Finally, are compared the multi-objective analysis results based on the cost of implementation and operation by the investor, considering the absence of Distribution Companies participation in the DER site and size definition, and later with the involvement of those Companies in this definition, through the mentioned incentives.