Abstract
The paper presents a modified hybrid particle swarm optimization with bat algorithm parameter inspired acceleration coefficients (MHPSO-BAAC) without and with the constriction factor to find the optimal solution of the economic dispatch problems (EDPs) incorporating conventional as well as hybrid and renewable energy sources (RESs) based plants. The algorithm is designed by modifying the recently presented hybrid PSO and BA (HPSOBA) algorithm applied for the achievement of the optimal solution of the EDPs. The modified algorithm is implemented to solve EDPs of all RESs-based power systems for three scenarios, without constraints, with time-varying demand, and with the consideration of regional load sharing dispatch (RLSD). The performance of the algorithm is also verified through the implementation of various combinations of hybrid as well as thermal power plants (TPPs). The case of TPPs consists of three different scenarios: 1) a small-scale system with constraints like ramp-rate limits (RRLs), prohibited operating zones (POZs), and power losses; 2) a medium-scale power system with consideration of emission-economic dispatch (EED); 3) a large-scale power system with valve-point loading (VPL) effect. The results of the designed MHPSO-BAAC algorithm are compared with the various metaheuristic algorithms available in the literature and the comparative analysis shows the superior performance of the developed algorithm in terms of fuel cost reduction, fast convergence, and computational time.
Highlights
Reference [33] presented the solution of economic dispatch problem (EDP) for a mechanism based on virtual power plants (VPPs) composed of wind farms but, the authors considered the cost of wind-based plants as zero, neglecting the impact of penalty factors for over and underestimations
The algorithm is tested for the achievement of the optimal solution of the EDPs comprising different cases of thermal power plants (TPPs), one case of HPSs, and three cases of only Renewable energy sources (RESs) based power systems
The hybrid PARTICLE SWARM OPTIMIZATION (PSO) and BAT ALGORITHM (BA) (HPSOBA), MHPSO-BAAC, and MHPSO-BAAC-χ algorithms are run for 30 successive trials and the results are compared with the backtracking search algorithm (BSA) and the designed hybrid algorithms
Summary
The developed algorithm is implemented to solve EDPs for HPSs developed through the combination of TPPs and RESs. Reference [33] presented the solution of EDP for a mechanism based on virtual power plants (VPPs) composed of wind farms but, the authors considered the cost of wind-based plants as zero, neglecting the impact of penalty factors for over and underestimations. PROBLEM FORMULATION EDP, in this paper, is divided into two parts: i) cost calculation for OED of the traditional TPPs and hybrid electric power generation systems with due consideration of the operational restrictions and ii) all RESs-based power systems comprising of PV, biofuel, and wind-based power plants instigated in the south of Pakistan while considering time variation and regional load sharing dispatch (RLSD). Where α, β and γ are the coefficients for the quadratic cost function
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