Economic load dispatch using population-variance harmony search algorithm

Abstract

This paper presents a novel stochastic optimization approach to solve the constrained economic load dispatch (ELD) problem using the harmonic search algorithm (HS). HS is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work analyses the evolution of the population-variance over successive generations in HS and thereby draws some important conclusions regarding the explorative power of HS. The proposed methodology easily takes care of solving non-convex ELD problems along with different constraints like transmission losses, ramp rate limits of the generators and prohibited operating zones. Simulations were performed over various standard test systems with different number of generating units and a comparative study is carried out with other existing relevant approaches. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.

Tournament-based harmony search algorithm for non-convex economic load dispatch problem

“…The main aim of solving ELD is to distribute the required generation among the generating units in such a way to minimize the fuel costs of each unit subject to satisfying equality constraints related to the power balance and inequality constraints related to the power output [27,65]. Therefore, ELD problem is considered as a non-convex and highly non-linear optimization problem which can not be easily tackled using traditional calculus-based optimization methods [65,28]. Indeed, the calculus-based methods require smoothing and differentiable objective function when applied to tackle the ELD problems [34].…”

“…In the recent years, several harmony search (HS) algorithms have been proposed to tackle ELD problems [30,27,47,65,63]. The HS, which is the recent evolutionary algorithm proposed in [40], is considered to be an efficient approximation technique due to its derivative-free characteristics [53].…”

Evolutionary optimization technique for comparative analysis of different classical controllers for an isolated wind–diesel hybrid power system

“…This algorithm has found a number of successful applications in some real world problems [5,6] in the recent years. HS has been used for static economic load dispatch problems [7][8][9]. HS is able to identify the high performance regions in the solution space but it does not have a good local searching capability [10] and also requires large number of design parameters for each specific problem.…”

A Memetic Approach for Improving Minimum Cost of Economic Load Dispatch Problems

“…Many studies have aimed to overcome the shortcomings of the conventional deterministic algorithms and to investigate the efficiency and applicability of the algorithms in ELD problem. For example, genetic-based different types of algorithms (GA) [8][9][10][11][12][13][14][15], a variety of evolutionary programming-based algorithms (EP) [16][17][18][19], particle swarm optimization (PSO) with its variations [20][21][22][23][24][25][26][27][28], tabu search (TS) [29], Taguchi method [30], bioinspired optimization algorithms [31][32][33][34], harmony search (HS) [35,36], and hybrid methods combining two or more metaheuristic algorithms [37][38][39][40][41][42] have been applied to explore the capability of stochastic artificial intelligence algorithms to solve ELD problem so far.…”