Chaos-enhanced multi-objective tunicate swarm algorithm for economic-emission load dispatch problem

Abstract Climate change and environmental protection have a significant impact on thermal plants. So, the main principles of combined economic-emission dispatch (CEED) problem are indeed to reduce greenhouse gas emissions fuel costs. Many approaches demonstrated their efficacy in addressing CEED problem. However, designing robust algorithm capable achieving Pareto optimal solutions under its multimodality non-convexity natures caused by valve ripple effects is true challenge. In this paper, chaos-enhanced multi-objective tunicate swarm (CMOTSA) for To promote exploration exploitation abilities basic (TSA), an exponential strategy based chaotic logistic map (ESCL) incorporated. Based ESCL CMOTSA, it can improve possibility diversification feature search different areas within solution space, then, gradually with progress iterative process converts emphasize intensification ability. The CMOTSA approved applying some benchmarking functions which front characteristics including convex, discrete, non-convex. inverted generational distance (IGD) (GD) employed assess robustness good quality against successful algorithms. Additionally, computational time evaluated, consumes less most functions. applied one practical engineering problems such as economic emission ripples. By using three systems (IEEE 30-bus 6 generators system, 10 units system IEEE 118-bus 14 generating units), methodology validation made. It be stated large-scale case that results equal 8741.3 $/h minimum cost 2747.6 ton/h very viable others. pointed out cropped proposed efficient tool proven.