A Hybrid Metaheuristic Approach for the Solution of Renewables-Incorporated Economic Dispatch Problems

Abstract

This paper presents a hybrid metaheuristic optimization algorithm developed to solve the Economic Dispatch Problem (EDP) encountered in different combinations of power plants. The algorithm is developed by assimilating the prominent features of Particle Swarm Optimization (PSO) and Bat Algorithm (BA) and improves cost reduction and convergence with lesser computational time. The developed algorithm is employed for the solution of EDP consisting of only Renewable Energy Sources (RESs) implemented at various locations in Pakistan. The all RES based EDP consists of scenarios composed of sub-scenarios having no constraints, with time-varying loads and multi-area economic dispatch (MAED). The algorithm is also tested for three different combinations of power plants, comprising of RES integrated with thermal power plants (TPPs), the small-scaled thermal power system with constraints, and a large-scaled power system with Valve Point Loading (VPL) effect. The comparative analysis of the results for the developed metaheuristic algorithm with various existing techniques shows a reasonable reduction in the cost, improved computational time, and fast convergence.

A Modified Hybrid Particle Swarm Optimization With Bat Algorithm Parameter Inspired Acceleration Coefficients for Solving Eco-Friendly and Economic Dispatch Problems

“…4 presents a comparison of plots for the recently developed HPSOBA, MHPSO-BAAC, and MHPSO-BAAC-χ. The comparative plots indicate the superior performance of the presented algorithm against the recently developed HPSOBA [43] and MHPSO-BAAC-χ. Although the plot of the constriction factor-based MHPSO-BAAC stays aligned with the simple MHPSO-BAAC plot, the latter shows a marginal reduction in the cost while approaching the end of the pre-defined no.…”

“…The authors present a novel, versatile, and robust PSO with bat algorithm parameter inspired acceleration coefficients (MHPSO-BAAC) with and without constriction factor developed through the improvement of the hybrid PSO and BA (HPSOBA) algorithm. The modified hybrid algorithm has been verified through the calculation of an optimal solution for EDP when implemented for different scenarios consisting of various combinations of RESs and TPPs presented in [43] and some additional cases considered in this paper. The RES-based EDP was solved with the consideration of climatic conditions, six different time slots, and RLSD for the sources instigated in the south of Pakistan.…”

“…The updated HPSO-BAAC algorithm is developed through the modifications in the standard HPSOBA presented in [43]. The unique parameter alpha α introduced in the HPSOBA algorithm is employed to control the coefficients of cognitive and social terms of the PSO velocity equation while the rest of the equations remain the same.…”

“…The HPSOBA was a multipurpose and distinctive technique that combined the significant topographies of the standard PSO and BA. The designed technique offered the optimal solution of EDP for thermal, hybrid, and all RESbased plants as cited in [55]. The mathematical representation of the HPSOBA is given in ( 27) and ( 28),…”

Optimal Energy Scheduling Strategy in Power System using Bat Algorithm Optimization Approach

“…Various methods have been used, including optimization method. Optimization method can be categorized into several categories, including metaheuristic [6][7][8], combinatorial optimization [9][10][11] and linear programming [12][13][14]. A power system can be built up by more than one generator depending on the power demand.…”