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Photovoltaic power plant design considering multiple uncertainties and risk

  • S.I.: Risk Management Approaches in Engineering Applications
  • Published:
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Abstract

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.

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Acknowledgements

This work is supported, in part, by the European Commission Marie Curie (PIRG-GA-2010-268455) and European Commission Marie Curie (PIRG-GA-2010-268426) Grants.

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Authors and Affiliations

  1. Business Administration Program, Middle East Technical University, Northern Cyprus Campus, Mersin 10, Turkey

    Yasemin Merzifonluoglu

  2. Mechanical Engineering Program, Middle East Technical University, Northern Cyprus Campus, Mersin 10, Turkey

    Eray Uzgoren

Authors
  1. Yasemin Merzifonluoglu
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  2. Eray Uzgoren
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Corresponding author

Correspondence to Yasemin Merzifonluoglu.

Appendix

Appendix

See Table 8.

Table 8 Summary of the sensitivity analysis results
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Merzifonluoglu, Y., Uzgoren, E. Photovoltaic power plant design considering multiple uncertainties and risk. Ann Oper Res 262, 153–184 (2018). https://doi.org/10.1007/s10479-017-2557-5

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

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