Photovoltaic power plant design considering multiple uncertainties and risk

Yasemin Merzifonluoglu*, Eray Uzgoren

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)153-184
JournalAnnals of Operations Research
Issue number1
Publication statusPublished - Mar 2018
Externally publishedYes


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


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