An improved TLBO based economic dispatch of power generation through distributed energy resources considering environmental constraints

Abstract

Abstract In today’s era, to attain sustainable energy on the increasing environmental apprehension and diminution in the fuel expenditure, the endeavor on the integration of distributed energy resources (such as wind, solar etc.) along with conventional energy sources are gaining the highest consideration. Development of such hybrid model presents an interesting challenge of solving complex multi-objective optimization problem without getting trapped in local optima. In the present work, various optimization techniques such as Particle Swarm Optimization (PSO), Teaching Learning Based Optimization (TLBO), and Improved TLBO (TLBO–PSO) are presented to optimize the total operating cost of the system. This system consists of multiple solar PV modules, wind turbines, and thermal generators. Main objective of this work is “to check the strength of improved TLBO (TLBO–PSO) on complex multi-objective optimization problem”, “to analyze the effect of renewable resources on the total operating cost of emission constrained economic dispatch system” and “to evaluate the effect of emission constraint on economic dispatch problem considering renewable energy resources using different optimization algorithms.” Results have also been compared with the classical optimization technique QCP and other metaheuristic technique such as GA and one of the recently developed techniques, namely comprehensive TLBO (CTLBO), which indicates that the computational strength and quality of solution obtained from improved TLBO (TLBO–PSO) is superior to other four algorithms under consideration.