4-E (Energy-Emission-Environment-Economic) Dispatch Problem in Solar PV Energy Using Hybrid PSOTLBO Search Algorithm

Abstract

Renewable energy sources have evolved into a technologically and economically feasible choice for use by electrical utilities. Furthermore, the widespread usage of renewable energy sources is driving policymakers and utilities to increase green energy's role to ensure long-term economic growth. The most influential non-conventional energy source for generating power is solar energy. Electric power systems must be designed, built, and run in such a way that the majority of energy demand for loads is supplied reliably, cost-effectively, and in an environmentally responsible manner. In 4-E dispatch, the term "energy"refers to generated power in the scheduled period, the term "emission"refers to the amount of emission released in the scheduled period, and the term "environment"refers to health and environmental damage costs in the scheduled period and the term "economic"refers to power generating cost in the scheduled period. In this paper a hybrid of particle swarm optimization (PSO) and teaching learning-based optimization (TLBO), named as PSOTLBO is proposed, developed, and effectively applied to attain the best or optimum solutions for the 4-E (Energy-Emission-Environment-Economic) dispatch problem for scenarios involving ten thermal power plants and thirteen solar photovoltaic (PV) plants.