Dual-Sided Involvement of Energy Optimization and Strategic Bidding in Wind-PV System to Maximize Benefits for Customers and Power Providers

Abstract

Global warming is causing industrial development to increase greenhouse gas emissions, impacting power provider economies and potentially posing a solution through renewable energy. In order to solve these issues, the research offers a dual strategic auction difficulty for renewable energy market clear prices (MCPs) to maximize supplier and buyer revenues while mitigating rival unpredictability and renewable vacillation power supply sources. The study uses scenario reduction techniques, including Beta and Weibull distribution of probability, forward-reduction technique, and underestimation and overestimation of the cost function to manage uncertainties in renewable energy. The Gravitation Search algorithm and a hybrid approach ordered weighted average distance (OWAD) combined, with Topsis operational gravitational search algorithm TOGSA (OWAD-TOGSA), are used to solve the multi-objective issue. The study evaluates the performance of IEEE standard 30-bus and 57-bus test systems and an Indian 75-bus operational system to solve a problem involving wind and sun energy in the spite of its volatility. The proposed bidding approach is deemed feasible and revenue the potential to improve the efficiency of electric energy-producing utilities and consumers.