Solution of combined economic and emission dispatch problem using a novel chaotic improved harmony search algorithm

Abstract

This paper presents a new optimization technique developed based on harmony search algorithm (HSA), called chaotic improved harmony search algorithm (CIHSA). In the proposed algorithm, the original HSA is improved using several innovative modifications in the optimization procedure such as using chaotic patterns instead of uniform distribution to generate random numbers, dynamically tuning the algorithm parameters, and employing virtual harmony memories. Also, a novel type of local optimization is introduced and employed in the algorithm procedure. Applying these modifications to HSA has resulted in enhancing the robustness, accuracy and search efficiency of the algorithm, and significantly reducing the iterations number required to achieve the optimal solution. To validate the effectiveness of CIHSA, it is used to solve the combined economic emission dispatch (CEED) problem, which practically is a complex high-dimensional non-convex optimization task with several equality and inequality constraints. Six test systems having 6, 10, 13, 14, 40, and 140 generators are investigated in this study, and the valve-point loading effects, ramp rate limits and power transmission losses are also taken into account. The results obtained by CIHSA are compared with the results reported in a large number of other research works. Furthermore, the statistical data regarding the CIHSA performance in all test systems is presented. The numerical and statistical results confirm the high quality of the solutions found by CIHSA and its superiority compared to other existing techniques employed in solving CEED problems. Highlights An innovative and strong optimization technique based on harmony search is proposed. The proposed algorithm is tested on solving economic emission dispatch problem. It has the potential to be applied to many other engineering optimization problems. Six test systems considering valve point effect and transmission losses are studied. High quality solutions are obtained and compared with a large number of other methods.

Chaotic sine–cosine algorithm for chance‐constrained economic emission dispatch problem including wind energy

“…Moghaddam et al [38] added a fuzzy-based strategy in the PSO algorithm for optimal management of a typical microgrid system. In [39], the chaotic patterns were used to generate the random parameters in the HSA to provide the global optimum solution for the combined EED problem.…”

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

“…This biobjective CEED optimization problem is converted to a single objective problem using penalty factors and then solved using various potent metaheuristic algorithms and their variants such as improved artificial bee colony algorithm (ABC) in [8], global particle swarm optimization (GPSO) in [9], the chaotic improved harmony search algorithm in [10], flower pollination algorithm in [11], biogeography based optimization in [12], the gravitational search algorithm in (GSA) [13], the stochastic fractal search algorithm in [14], the symbiotic organism search algorithm for multi area power system in [15], fluid mechanism inspired algorithm in [16], and the lightning flash algorithm in [17].…”

“…The heat balance equality constraint given by (10) balances the heat produced by Nc CHP units and Nh heat only units with the total heat demand Hd of the system.…”

“…The objective of the CHPEED problem is to obtain the PO solution vector x * that simultaneously minimizes the conflicting objectives given by (6) and 7while satisfying the real power balance equality constraint given by (8), heat balance constraint given by (10), inequality constraints given by (11) to (14) and the bounds given by (15) and (16). The essential goals of the CHPEED problem are 1.…”

Hybrid Flower Pollination Algorithm with Sequential Quadratic Programming Technique for Solving Dynamic Combined Economic Emission Dispatch Problem

“…Second form of EmD considers fuel cost and emission as a single objective expression with unified constraints [10,11] but this unification inhibits us to focus and target on fuel cost or emission individually. Third form of EmD considers emission and fuel cost as two different objective functions tied together in a single multi objective expression by assigning weights to each objective [12]. This setting allows flexibility in solution as well as individual autonomy and because of these strengths we use this form in our research.…”