Sayyad Nojavan

The integration of solar thermal storage (STS) with concentrating solar power plants (CSPP) is increasingly considered worldwide to enhance energy systems' flexibility and reduce the allegiance to sun radiation uncertainty. The uncertainties and imposed risks are challenging for the CSPP operators in the optimal operation process. Also, CSPP can profit by offering curves and selling the generated power in the electricity market. The uncertainties of electricity market price and solar radiation will affect the provided offers. The provided offers should have a proper level of conservation to avoid more costs in the risk-averse strategy. A new proper risk modeling approach is required to get a logical risk strategy while modeling the uncertainties to reach this goal. Therefore, stochastic p-robust optimization (SPRO) is provided to suggest robust offering curves, maximize the average profit of the studied CSPP model and minimize the maximum value of the relative regret (MRR). The provided Mixed-integer linear programming (MILP)-based model is optimized using CPLEX solver in GAMS. The obtained results show the efficiency and effectiveness of the proposed method. Based on the obtained results, a 45 % reduction of the relative regret to a lower feasible regret level reduces the total profit by 3.86 %.