Planejamento de reativos em sistemas elétricos de potência multi-área através de modelos estocásticos

Detalhes bibliográficos
Ano de defesa: 2014
Autor(a) principal: López Quizhpi, Julio César [UNESP]
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual Paulista (Unesp)
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/11449/123362
http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/23-04-2015/000825243.pdf
Resumo: In this work, the reactive power planning problem is modeled and solved as a two stage sto- chastic multi-period convex optimization problem in multi-area power systems. The classical mixed integer reative power planning model is reformulated as a multi-period conic convex mi- xed integer model considering the taps of transformers as integer variables. In the multi-area power system context the problem is decentralized by lagrangian relaxation, decomposing the multi-area problem in subproblems associated with each area. The transmission system opera- tors in each area solve their subproblems in coordination with adjacent areas while maintaining the confidentiality of their power system data, only exchanging boundary buses information. In the stochastic formulation, demand uncertainty in each area is considered by a Normal distribu- tion function, and the scenario generation in each period is made through the efficient technique Latin Hypercube sampling. The uncertainty presence at the problem is analyzed by computing the values that quantify the importance of that parameters. Moreover, the stochastic reactive power planning problem is formulated as a multiobjective mathematical programming problem optimizing the expansion costs function and load shedding risk function that is modeled by regret, considering the fix cost budget limit. A ε -constraint methodology is used to solve the multiobjective mathematical programming problem. Finally the obtained solutions from propo- sed problem are analyzed using the real equivalent South and Southeast Brazilian power system and the IEEE-118 test power system