May 16, 2024
Sayyad Nojavan

Sayyad Nojavan

Academic rank: Associate professor
Address:
Education: Ph.D in ٍElectrical Power Engineering
Phone: 09148903379
Faculty: Faculty of Engineering
Department: Electrical Engineering

Research

Title
Pumped hydro energy storage arbitrage in the day-ahead market in smart grid using stochastic p-robust optimization method
Type Article
Keywords
Pumped hydro energy storage Stochastic p-robust optimization Bidding strategy Offering strategy Maximum relative regret
Researchers Zhifeng Li، Qing Zhang، Qun Guo، Sayyad Nojavan

Abstract

Individual operation of pumped hydro energy storage (PHES) as large-scale energy storage needs the bidding and offering curves to participate, as a prosumer, in the day-ahead electricity market. Therefore, in this paper, by taking advantage of stochastic and robust optimization, a new stochastic p-robust optimization (SPRO) method is proposed to deal with the financial risks of the day-ahead price uncertainty. The proposed method compares the profit of PHES with the relative regret to get a risk-controlled strategy. According to obtained results, reducing the robustness parameter (p) from the p=+∞ to p=0.21, the profit, and the maximum relative regret are reduced by $ 2611 and 15.02 %, respectively. In other words, with a 19.11 % decline in profit, the maximum amount of relative regret decreased by 41.30 %. Therefore, it can be shown that by a few reductions in profit, the maximum amount of relative regret decreases significantly. At the same time, the robustness of PHES is guaranteed against the day-ahead market price uncertainty. Finally, the risk-based bidding and offering curves are derived using the results of the proposed SPRO method.