Sayyad Nojavan

In order to stabilize the operation of power systems, it's essential to model the uncertainties threatening the normal performance of these systems. In this study, a renewable based grid-photovoltaic (PV)-boiler-battery-fuel cell hybrid energy system (RBHES) has been scheduled according to the uncertainty modeling of upstream net price and employment of demand response program (DRP). The main reason of implementing DRP is to motivate electricity consumers to modify their energy usage pattern in a way that economic goals of RBHES are obtained. In this paper, interval optimization technique has been used to model the uncertainty of upstream net price and to prepare a stabilized condition for safe operation of RBHES. Converting the single-objective-uncertainty-based model into a deterministic multi-objective model with average and deviation costs, the interval optimization technique models uncertainty and guarantees the optimal performance of RBHES under the minimum impact of upstream net price uncertainty. To solve the aforementioned multi-objective model, the weighted sum technique and the fuzzy approach are used. An RBHES has been investigated as a case study and the simulation results showing positive effects of employed techniques are presented for comparison. In cases with and without DRP, the average costs of RBHES in the interval method in comparison with the deterministic method have increased 1.61 % and 2.06 %, respectively. This is while the deviation costs of RBHES has reduced up to 13.61 % and 15.28 %, respectively. Due to the successful implementation of the DRP, the average cost and the deviation cost of the RBHES have lessened for 5.89 % and 11.08 %, respectively, in comparison with the case lacking the DRP.