Regret-based management of wind-solar-thermal generation company under uncertainties: A novel stochastic p-robust optimization approach

Uncertainty in the market prices and production are challenging issues in the optimal management of wind-solarthermal 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%.