Solving Renewables-Integrated Economic Load Dispatch Problem by Variant of Metaheuristic Bat-Inspired Algorithm

Abstract

One of the most important concerns in the planning and operation of an electric power generation system is the effective scheduling of all power generation facilities to meet growing power demand. Economic load dispatch (ELD) is a phenomenon where an optimal combination of power generating units is selected in such a way as to minimize the total fuel cost while satisfying the load demand, subject to operational constraints. Different numerical and metaheuristic optimization techniques have gained prominent importance and are widely used to solve the nonlinear problem. Although metaheuristic techniques have a good convergence rate than numerical techniques, however, their implementation seems difficult in the presence of nonlinear and dynamic parameters. This work is devoted to solving the ELD problem with the integration of variable energy resources using a modified directional bat algorithm (dBA). Then the proposed technique is validated via different realistic test cases consisting of thermal and renewable energy sources (RESs). From simulation results, it is observed that dBA reduces the operational cost with less computational time and has better convergence characteristics than that of standard BA and other popular techniques like particle swarm optimization (PSO) and genetic algorithm (GA).

A Cost Effective Solution to Dynamic Economic Load Dispatch Problem Using Improved Chimp Optimizer

“…Chimp optimizer algorithm is suggested to get optimized outcomes for dynamic load dispatch with the effect of EVs as V2G and G2V. A seven generator test system without valve point loading effect, with loss coefficient matrix as zero is considered (Tariq et al, 2020), (Gholami et al, 2014). Table 4 displays that the fuel price is 296174.3087 $/day using the chimp optimizer algorithm.…”

Recent Methodology-Based Gradient-Based Optimizer for Economic Load Dispatch Problem

“…The hybridization of PSO and TCO favoured faster convergence and produced better quality of solutions. The authors performed ELD considering renewable resources [29]. A modified version of BA was used for solving the problem.…”

“…VOLUME 4, 2016 ELD, ELD with valve point effect, CEED CTO [28] Dynamic ELD PSO TCO [29] ELD considering renewable sources Modified BA [30] ELD with losses QBA [31] Dynamic ELD considering renewable sources PSO [32] ELD with valve point effect QBA [33] ELD with losses PSO [34] Non convex ELD ACS [35] CEED Hybrid FA BA [74] ELD Jaya Algorithm [36] ELD with valve point effect, CEED MBA [37] ELD with valve point effect, ramp rates and prohibited zones Improved PSO [38] Convex and non-convex ELD SHO [39] ELD with ramp rates and prohibited zones WOA [40] Convex, non-convex and dynamic ELD MFO [41] ELD with valve point effect Hybrid GWO [42] ELD with losses Improved PSO [43] ELD with losses AEFA [44] Non-convex ELD ALO [45] ELD with losses ACSS [46] ELD with losses Adaptive PSO [47] ELD with losses Enhanced PSO [48] ELD with losses GWO [49] ELD with losses Enhanced BA [50] CEED QBA [51] Dynamic ELD, CEED Modified ABC [52] CEED Enhanced Cultural algorithm [53] Dynamic CEED Chaotic FA [54] Dynamic CEED TLBO [55] Smooth and non-smooth ELD WCA [56] ELD with renewable resources Hybrid BA [57] Multi-area ELD SSA [75] Multi-area ELD Hybrid Jaya TLBO [58] Multi-area ELD ISFS [76] CEED with renewable sources MOEA/D [59] Multi-area ELD MFO [60] CEED Improved TLBO [61] ELD with losses Modified GWO [62] Dynamic ELD GA PSO…”

Performance of Turbulent Flow of Water Optimization on Economic Load Dispatch Problem

“…This algorithms are used in several problems such as extraction of photovoltaic parameters using gradient based optimizer [12] and Turbulent flow of water optimization [13]. In addition, solving ELD problem is performed with several al-gorithms such as non dominated sorting genetinc algorithm [14], modified jrill algorithm [15], Whale Optimization Algorithm [16], Henry gas solubility optimization [17], gravitational search algorithm [18], improved Firework Algorithm [19], grasshopper optimization algorithm [20], multi gradient practical swarm optimization [21], Salp Swarm Algorithm [22], Differential Evolution [23], Equilibrium Optimizer [24], reinforcement learning [25], virus colony search algorithm [26], Harmony Search Algorithm [27], improved grey wolf optimization [28], bat algorithm [29], improved class topper optimization algorithm [30], improved bat algorithm [31], Ant Colony Optimization [32], improved Jaya algorithm [33] and artificial cooperative search algorithm [34].…”

“…Also, the ELD application in a power system is solved using class topper optimization (CTO) algorithm in [30]. In [31], authors have used an improved version of BA to solve ELD in presence of renewable energy sources. In [32], authors have used ACO to solve ELD with losses.…”