Programação estocástica aplicada ao planejamento de sistemas de distribuição considerando geração distribuída e emissões de CO2
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Data
2019-08-24
Autores
Lima, Tayenne Dias de
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
A presença de Geração Distribuída (GD) no Sistema de Distribuição de Energia Elétrica (SDEE) tem se incrementado nos últimos anos devido a mudanças na regulação e a incentivos governamentais, proporcionando benefícios técnicos e econômicos. Em particular, é esperado que a GD renovável (eólica ou solar) seja integrada adequadamente no SDEE, visando contribuir na redução de emissões de gases de efeito estufa. Entretanto, a presença da GD renovável, junto com suas inerentes incertezas, aumenta a complexidade no planejamento do SDEE. Diante do exposto, neste trabalho propõe-se um modelo de programação estocástica de dois estágios para o problema de planejamento da expansão do SDEE multi-período. As incertezas da geração renovável (associadas à irradiação solar e velocidade do vento) e demanda são representadas por meio de cenários. A função objetivo minimiza o valor presente líquido dos investimentos (subestações, circuitos, e alocação de GD), custo da energia, manutenção e operação, assim como o custo das emissões de CO2. A operação das unidades de GD é representada limitando a potência ativa/reativa que pode ser injetada segundo as curvas de capabilidade e restrições de fator de potência. O modelo proposto foi implementado na linguagem de modelamento AMPL e resolvido com o solver CPLEX. Testes utilizando um SDEE de 24 e 54 nós comprovam a eficiência do modelo.
The presence of Distributed Generation (DG) in Electrical Distribution Systems (EDSs) has been increased in recent years due to changes in regulation and government incentives, leading to technical and economic benefits. In particular, renewable DG (wind or solar power) is expected to be properly integrated into the EDS, aiming to contribute to the reduction of greenhouse gas emissions. However, the presence of renewable DG, along with its inherent uncertainties, increases the complexity in the planning of the EDS. In this context, this work proposes a two-stage stochastic programming model for the problem of EDSs expansion planning. The uncertainties of renewable generation (associated with solar irradiation and wind speed) and demand, are represented through scenarios. The objective function minimizes the net present value of investments (substations, circuits, and DG allocation), energy cost, maintenance and operation, as well as the cost of CO2 emissions. The operation of the DG units is represented by limiting the active/reactive power that can be injected according to capability curves and power factor constraints. The proposed model was implemented in the modeling language AMPL and solved with the solver CPLEX. Tests using a 24 and 54-nodes EDS prove the efficiency of the proposed model.
The presence of Distributed Generation (DG) in Electrical Distribution Systems (EDSs) has been increased in recent years due to changes in regulation and government incentives, leading to technical and economic benefits. In particular, renewable DG (wind or solar power) is expected to be properly integrated into the EDS, aiming to contribute to the reduction of greenhouse gas emissions. However, the presence of renewable DG, along with its inherent uncertainties, increases the complexity in the planning of the EDS. In this context, this work proposes a two-stage stochastic programming model for the problem of EDSs expansion planning. The uncertainties of renewable generation (associated with solar irradiation and wind speed) and demand, are represented through scenarios. The objective function minimizes the net present value of investments (substations, circuits, and DG allocation), energy cost, maintenance and operation, as well as the cost of CO2 emissions. The operation of the DG units is represented by limiting the active/reactive power that can be injected according to capability curves and power factor constraints. The proposed model was implemented in the modeling language AMPL and solved with the solver CPLEX. Tests using a 24 and 54-nodes EDS prove the efficiency of the proposed model.
Descrição
Palavras-chave
Geração distribuída, Incertezas, Planejamento de sistemas de distribuição de energia elétrica, Programação estocástica, Distributed generation, Planning of electric power distribution systems, Stochastic programming, Uncertainties