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Stochastic Optimization for Power System Configuration with Renewable Energy in Remote Areas

By Ludwig Kuznia, Bo Zeng, Grisselle Centeno and Zhixin Miao

Abstract

This paper presents the first stochastic mixed integer programming model for a comprehensive hybrid power system design, including renewable energy generation, storage device, transmission network, and thermal generators, in remote areas. Given the computational complexity of the model, we developed a Benders ’ decomposition algorithm with Pareto-optimal cuts. Computational results show significant improvement in our ability to solve this type of problem in comparison to a state-of-the-art professional solver. This model and the solution algorithm provide an analytical decision support tool for the hybrid power system design problem

Topics: stochastic mixed integer programming, power system design, renewable energy, Benders ’ decomposition
Year: 2011
OAI identifier: oai:CiteSeerX.psu:10.1.1.416.3107
Provided by: CiteSeerX
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