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-based optimal performance of a PV/fuel cell/battery/grid hybrid energy system using information gap decision theory in the presence of demand response program
Type Article
Keywords
Information gap decision theory (IGDT) Hybrid energy system Demand response program (DRP)
Researchers Sayyad Nojavan، Majid Majidi، Kazem Zare

Abstract

One of the big challenges that system operators have always dealt with is uncertainty of different parameters in the power systems. In this paper, optimal performance of an ongrid PV/fuel cell/battery hybrid system has been evaluated in the presence of demand response program with considering electrical load uncertainty. Information gap decision theory (IGDT) has been proposed to model the uncertainty of electrical load. Utilizing different strategies obtained through the robustness and opportunity functions, operator will have several options to control the uncertainty. By shifting some percentage of load from peak periods to other periods, DRP flattens load curve and minimizes total cost of hybrid system. A sample system is simulated and the results are compared to validate the proposed techniques.