Stochastic optimization for power system configuration with renewable energy in remote areas

Ludwig Kuznia (), Bo Zeng (), Grisselle Centeno () and Zhixin Miao ()

Annals of Operations Research, 2013, vol. 210, issue 1, 432 pages

Abstract: This paper presents a stochastic mixed integer programming model for a comprehensive hybrid power system design problem, including renewable energy generation, storage device, transmission network, and thermal generators, for remote areas. Given the complexity of the model, we developed a Benders’ decomposition algorithm with two additional types of cutting planes: Pareto-optimal cuts generated using a modified Magnanti-Wong method and cuts generated from a maximum feasible subsystem. 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. Copyright Springer Science+Business Media, LLC 2013

Keywords: Stochastic mixed integer programming; Power system design; Renewable energy; Benders’ decomposition (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (14)

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DOI: 10.1007/s10479-012-1110-9

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