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

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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.

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Acknowledgements

The authors wish to thank Mr. Adam Parke and Mr. Gordon Gillette at Tampa Electric Company for their support to this work. Additionally, we would like to thank the anonymous referees for their constructive suggestions which significantly improved the quality of the paper.

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Authors and Affiliations

  1. Dept. of Industrial and Management Systems Engineering, Tampa, FL, 33620, USA

    Ludwig Kuznia, Bo Zeng & Grisselle Centeno

  2. Dept. of Electrical Engineering, University of South Florida, Tampa, FL, 33620, USA

    Zhixin Miao

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  1. Ludwig Kuznia
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  2. Bo Zeng
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  3. Grisselle Centeno
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  4. Zhixin Miao
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Correspondence to Ludwig Kuznia.

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Kuznia, L., Zeng, B., Centeno, G. et al. Stochastic optimization for power system configuration with renewable energy in remote areas. Ann Oper Res 210, 411–432 (2013). https://doi.org/10.1007/s10479-012-1110-9

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  • DOI: https://doi.org/10.1007/s10479-012-1110-9

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