Investigation of PBUC problem with RES and EV in restructured environment

Abstract

This research proposes a novel solution for the optimal day-ahead scheduling problem in the GAMS environment using the BARON approach. The challenge is extended to include Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more complex and practical. EVs serve as loads, energy suppliers, and storage during RESs’ uncertainties. The framework improves cost savings, quality, reliability, and stability of the power supply system by modeling solar, wind, and EV power in the scheduling problem. The solution is tested on a 10 -unit thermal system considering RESs and EVs under deterministic and stochastic environments. Stochastic scenarios are generated using Monte Carlo simulation, and the simultaneous scenario reduction approach enhances results. The BARON solver outperforms other solvers, achieving profits of $205,321 with wind, solar, and EVs, and $187,297 when considering uncertainty, resulting in a reduction of $18,024.