Wind curtailment mitigation in presence of battery energy storage and electric vehicle: A comprehensive multi-objective decision-support framework

Concern to maintain exploitation of power system in secure mode, the wind curtailment (WR) caused by the perpetual fluctuating of wind power (WP) can menace the operational power system schedule. The mentioned phenomenon will intensify by high WP penetration into the power system. In addition, incorporating plugged-in hybrid electric vehicles (PHEVs) into the power system along with the WP intermittent will increase the vagueness rating of the problem. Due to the expansion and development of battery energy storage (BES), the possibility of power shortage compensating and accumulating additional power produced by wind farms (WFs) has been engendered. Providing a stochastic scenario-based structure with different correlation levels can in-crease the robustness of the model. Here, a two-stage model has been proposed to overcome such a high -dimensioned problem. The first stage determined the scheduled power output of thermal generators (TGs) as the unit commitment (UC) problem to minimize operational costs. Next, by reckoning the supplementary con-straints, the scheduled WP, which is re-optimized, will be obtained. The second stage has employed to detect the BES capacity. In this stage, the intelligent parking lots (IPLs) assign price-based signal impetus to the PHEVs to participate in economic dispatch. Due to the prominence of being equipped with the supreme decision-making facility for the intelligent decision-maker operator (IDMO), the augmented epsilon-constraint method has been employed to capture the Pareto sets of some multi-objective functions. The optimum solution has been selected by the decision-making method (DMM) according to the operator's preferences. The results of proposed Multi -Objective Decision-Support (MODS) model show that the total operation cost and BES sizing have dropped by 68 and 6.1 percent, respectively. The performance of the proposed model has been testified through the IEEE-30 bus system via GAMS software.