Risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles using downside risk constraints method, By Sayyad Nojavan

Research

Title	Risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles using downside risk constraints method
Type	Article
Keywords	Risk-involved stochastic, performance Hydrogen storage based intelligent parking lots, Electric vehicles, Downside risk constraints method (DRCM), Risk model,
Researchers	Yan Cao، Jiang Du، Xueming Qian، Sayyad Nojavan، Kittisak Jermsittiparsert

Abstract

Today, the utilizations of hydrogen storage systems (HSS), renewable generation units (PV and wind generation) and distributed energy units are increased in the intelligent parking lots (IPL) in order to charge the electric vehicles (EVs) with clean energy sources. In this work, the uncertainties of upstream grid price, the demand of IPL, wind speed, solar irradiation and temperature are modeled via scenario approach based on stochastic programing. Furthermore, the downside risk constraints method (DRCM) is applied to consider risk related to uncertainties to get risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles. The proposed risk-based formulation is modeled using mixed-integer linear programming (MIP) which is implemented under GAMS software and solved via CPLEX solver. Two cases namely risk-averse and risk-neutral strategies are studied and compared to show the effects of DRCM implementation. The obtained results demonstrate the expected performance cost (EPC) of IPL is slowly raised while risk-in-cost (RIC) is significantly reduced due to model of risk related to uncertainties.