Economic Emission Load Dispatch with Renewable Energy and Electric Vehicle Integration: A Real-Data Approach Using Equilibrium Optimizer

Abstract

This paper presents an optimized solution to the Wind-Solar Plug-in Electric Vehicle Dynamic Economic Emission Load Dispatch (WSPEV DEELD) problem using the Equilibrium Optimizer (EO) algorithm. Real-world data from the renewable. Ninja platform for Gujarat, India, is used to handle uncertainties related to the underestimation and overestimation of wind and solar power, as well as PEV arrival, departure, and waiting times. EO’s balance between exploration and exploitation helps minimize generation cost and emissions while ensuring sustainability. Simulations consider Vehicle-to-Grid (V2G) and Grid- to-Vehicle (G2V) interactions using real-time RES data and PEV behavior. The results show improved system performance and demonstrate that the EO algorithm provides a robust, feasible strategy for dynamic RES and PEV integration into the power grid. Com- parisons with other recent methods confirm EO’s effectiveness in solving complex power dispatch problems under real-world constraints.