Photovoltaic power plant design considering multiple uncertainties and risk

Date

2018-03-01

Author

Merzifonluoglu, Yasemin
Uzgoren, Eray

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The objective of this study was to develop stochastic optimization tools for determining the best strategy of photovoltaic installations in a campus environment with consideration of uncertainties in load, power generation and system performance. In addition to a risk neutral approach, we used Conditional Value-at-Risk to estimate the risk in our problem. The resulting Mixed Integer Programming models were formulated using a scenario-based approach. To minimize the mismatch between supply and demand, hourly solar resource and electricity demand levels were characterized via refined models. A sample-average approximation (SAA) method was proposed to provide high-quality solutions efficiently. The SAA problems were solved using exact and heuristic methods. A complete numerical study was conducted to examine the performance of the proposed solution methods, identify optimal selection strategies and consider the sensitivity of the solution to varying levels of risk.

Subject Keywords

Stochastic programming, Renewable energy, Conditional Value-at-Risk, Photovoltaic system sizing

URI

https://hdl.handle.net/11511/65442

Journal

ANNALS OF OPERATIONS RESEARCH

DOI

https://doi.org/10.1007/s10479-017-2557-5

Collections

Economics and Administrative Sciences, Article

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Citation Formats

Y. Merzifonluoglu and E. Uzgoren, “Photovoltaic power plant design considering multiple uncertainties and risk,” ANNALS OF OPERATIONS RESEARCH, pp. 153–184, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/65442.