May 17, 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
Risk-Constrained Stochastic Optimization of a Concentrating Solar Power Plant
Type Article
Keywords
Concentrating solar power (CSP) plant,Downside risk constraints (DRC), Solar thermal storage unit, Risk-in-profit (RIP), Stochastic optimization,
Researchers Dongmin Yu، Abdol Ghaffar Ebadi، Kittisak Jermsittiparsert، Noor H. Jabarullah، Marina Vladimirovna Vasiljeva، Sayyad Nojavan

Abstract

A central concentrating solar power (CSP) plant is increasing in the power systems as novel technology in the solar energy sources. Also, solar thermal storage unit is combined with the CSP plant to increase flexibility and decrease the dependence on the instantaneous solar radiation. Furthermore, the CSP plant can be obtained the optimal offering strategies to submit to the electricity market in order to sell the produced power and increase the expected profit. In this paper, the uncertaintymodeling of solar irradiation and electricity market price is a big challenge for a CSP plant. Therefore, the scenario-based stochastic framework is proposed for optimal scheduling of a CSP plant in the presence of uncertainties to obtain optimal offering curves in order to sell to power market. Also, the risk related to uncertainties is considered via the downside risk constraints (DRC),which leads to obtain riskconstrained stochastic optimization of a CSP plant. The proposed model is formulated as mixed-integer linear programming, which is solved via CPLEX solver under GAMS optimization software. Risk-averse strategy is introduced in comparison with risk-neutral strategy to investigate the impacts of DRC implementation, which leads to decrease the expected profit while the expected risk-inprofit reduced.