Optimal management of storage for offsetting solar power uncertainty using multistage stochastic programming

Papavasiliou, Anthony;Kaneda, T.;Losseau, B.;Scieur, D.;Leemput, N.;et.al.
(2018) 20th Power Systems Computation Conference — Location: Dublin (6.November.2018)

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  • Papavasiliou, Anthonyorcid-logoUCLouvain
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  • Kaneda, T.
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  • Losseau, B.
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  • Scieur, D.
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  • Leemput, N.
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  • et. al.
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Abstract
Africa has recently engaged in implementing an aggressive renewable energy integration plan. A major challenge in the deployment of renewable power is the management of excess energy. The use of battery storage has been considered as a technically attractive solution. This paper tackles this operational problem using stochastic dual dynamical programming.We present an open-source MATLAB toolbox for multistage stochastic programming which employs stochastic dual dynamic programming. We use the toolbox in order to compare the stochastic solution to a greedy policy which operates batteries without future foresight as a benchmark. We consider a case study of storage management in Burkina Faso. We quantify the benefits of the stochastic solution and test the sensitivity of our results to the optimization horizon of the stochastic program.
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Papavasiliou, A., Kaneda, T., Losseau, B., Scieur, D., Cambier, L., Henneaux, P., Leemput, N., & et al. (2018). Optimal management of storage for offsetting solar power uncertainty using multistage stochastic programming. 20th Power Systems Computation Conference, Dublin. https://hdl.handle.net/2078.5/223672