Economic load dispatch using memetic sine cosine algorithm

Abstract

In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. Therefore, -hill climbing optimizer, a recent local search algorithm, is hybridized as a new operator in SCA to empower its exploitation capability to tackle ELD. The proposed hybrid algorithm is abbreviated as SCA- HC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. (ii) 6-units and 15-units with Ramp Rate Limits and Prohibited Operating Zones constraints. The sensitivity analysis of the control parameters for SCA- HC is initially studied. The results show that the performance of the SCA- HC algorithm is increased by tuning its parameters in proper value. The comparative evaluation against several state-of-the-art methods show that the proposed method is able to produce new best results for some tested cases as well as the second-best for others. In a nutshell, hybridizing HC optimizer as a new operator for SCA is very powerful algorithm for tackling ELD problems.

Comparative Study of Horse Swarm Algorithm and Classical Algorithm

“…It can be clearly seen from the figure that the WHO algorithm has reached a stable point for all functions. In addition, for all CEC2019 benchmark functions, through a small number of function evaluations, this algorithm can reach the lowest average of global solutions faster than other algorithms [6][7].…”

An efficient bi-objective approach for dynamic economic emission dispatch of renewable-integrated microgrids

“…To begin with, the authors of Al-Betar et al ( 2022) developed a hybrid approach based on β-hill climbing optimizer and sine cosine algorithm to solve the ELD problem. As revealed from the results of Al-Betar et al (2022), this hybridization helps to find superior results for some case studies compared with other state-ofthe-art methods. Particle swarm optimization algorithm was also modified in Gholami and Dehnavi (2019) to effectively schedule both thermal and renewable resources in an islanded microgrid.…”

Optimize power generation of thermal generating sources in solving the green energies-based economic load dispatch using Electric Eel Foraging Optimization

“…Therefore, the trend of using meta-heuristic algorithms to solve both ELD and GE-ELD is not an exception and also become more popular. Notably, the application of meta-heuristic algorithms to solve the mentioned problems, such as interior search algorithm (ISA) [12], Turbulent Flow of Water Optimization (TFWO) [13], whale optimization algorithm (WOA) [14], moth-flame optimization algorithm (MFO) [15], equilibrium optimizer (EO) [16], Grasshopper optimization algorithm (GOA) [17], chaotic bat algorithm (CBA) [18], Chaotic whale optimization algorithm (CWOA) [19], slime mould algorithm (SMA) [20], JAYA algorithm (YA) [21], bat-inspired algorithm (BIA) [22], multi-swarm statistical particle swarm optimization (MSPSO) [23], search and rescue optimization algorithm (SROA) [24], Harmony search algorithm (HSA) [25], the new metaheuristic evolutionary programming (NMEP) [26], artificial cooperative search algorithm (ACSA) [27], A Multi-Objective Cross-Entropy Optimization (MOCEO) [28], particle oriented cat swarm optimization (POCSO) [29], the Online learning Honey Bee Mating Optimization (OLHBMO) [30], artificial bee colony algorithm (ABCA) [31], A Modified Teaching -Learning-Based Optimization (MTLBO) [32], improved water wave optimization algorithm (IWWOA) [33], Dragonfly algorithm (DA) [34], memetic sine cosine algorithm (MSCA) [35].…”