Solving Environment-Constrained Economic Dispatch for a Microgrid System with Varying Electricity Market Pricing Strategy: A DSM-Based Approach

Abstract

Microgrids (MG) can be considered as a reduced power system network wherein the generation, transmission, and distribution of power take place within a limited geographical area. They are employed to utilize the maximum penetration of renewable energy sources (RES). Microgrid also has advantages such as reduction of transmission losses and costs pertaining to such losses. In this research, economic dispatch, emission dispatch, combined economic emission dispatch (CEED) based on fractional programming (FP), and environment-constrained economic dispatch (ECED) were assessed. An MG system for three distinct scenarios is studied. A novel, robust, and powerful swarm-intelligence hybrid algorithm, created by amalgamating the features of the conventional gray-wolf optimizer (GWO), sine-cosine algorithm (SCA), and crow search algorithm (CSA), is implemented as the optimization tool for the study. A significant reduction in generation costs of about 4.50-9.75% was achieved throughout the study when the time-of-usage (TOU) electricity market pricing strategy was used instead of the fixed pricing strategy. Furthermore, the paper also dealt with the Demand Side Management (DSM) to facilitate the generation cost by managing the controllable load demand. The generation cost decreased by a notable amount when ECED was evaluated with a 15% and 20% DSM-based revised load curve for the MG system.