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Sayyad Nojavan

Sayyad Nojavan

Academic rank: Associate Professor
ORCID:
Education: PhD.
ScopusId:
HIndex: 0/00
Faculty: Faculty of Engineering
Address:
Phone: 09148903379

Research

Title
Regret-based management of wind-solar-thermal generation company under uncertainties: A novel stochastic p-robust optimization approach
Type
JournalPaper
Keywords
Wind-solar-thermal generation company (WST-GenCo) Maximum relative regret Stochastic optimization approach Stochastic p-robust optimization approach (SPROA) Risk management
Year
2022
Journal Sustainable Energy Technologies and Assessments
DOI
Researchers Xinghua Guo ، Qun Guo ، Yifei Chen ، Esmaeil Valipour ، Sayyad Nojavan

Abstract

Uncertainty in the market prices and production are challenging issues in the optimal management of wind-solar-thermal generation companies (WST-GenCo). So, the stochastic p-robust optimization approach (SPROA), an efficient and computationally tractable approach, is used in this paper to manage the risk associated with various uncertainty. The proposed WST-GenCo model, comprised of thermal units, wind farms and solar farms, sells its productions in energy and reserve markets. The proposed model is scheduled in a day-ahead framework considering the uncertainties of the electricity and reserve market prices and the outputs of the renewable sources. So, maximizing the WST-GenCo’s profit and minimizing the relative regret level, which stands for the robustness level, are the objective functions of the studied paper. The proposed SPROA is applied successfully to the studied WST-GenCo model, and the obtained results indicate the efficiency of the proposed approach from the accuracy and efficiency perspectives. According to the obtained results, by reducing the WST-GenCo’s profit level by approximately 1.88%, the relative regret level can plunge to 46.27%.