A Non-convex Economic Load Dispatch Using Hybrid Salp Swarm Algorithm

Alkoffash, Mahmud S.; Awadallah, Mohammed A.; Alweshah, Mohammed; Zitar, Raed Abu; Assaleh, Khaled; Al-Betar, Mohammed Azmi

doi:10.1007/s13369-021-05646-z

Cited by 34 publications

(13 citation statements)

References 79 publications

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“…and 32697.2819 $/hr. respectively, better than other existing techniques like ESSA (Alkoffash et al, 2021), Jaya SML (Yu et al, 2019), etc. The number of hits to the best solution is 49 out of 50 trials with a simulation time of 0.59 seconds.…”

Section: Results Summarymentioning

confidence: 88%

Artificial Electric Field Algorithm Applied to the Economic Load Dispatch Problem With Valve Point Loading Effect

Shah

Soni

Bhattacharjee

2023

International Journal of Swarm Intelligence Research

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Economic load dispatch is to operate thermal generators economically with fulfilling load demand. This economic dispatch problem becomes highly complex and non-linear after considering various operating constraints like valve-point loading effect, generator operating constraints, and prohibited operating zone. The recently developed physics law-based artificial electric field algorithm has been applied to solve highly complex and non-linear ELD problems. The exploration and exploitation strategy of the algorithm helps to avoid local optimum value, and to get global optimum value in less computation time. The AEFA method has been applied to 10, 13, 15, 40, and large 110 thermal generators to validate the effectiveness of the proposed algorithm. The results obtained by the proposed algorithm have been compared with other recently developed algorithms.

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Section: Results Summarymentioning

confidence: 88%

Artificial Electric Field Algorithm Applied to the Economic Load Dispatch Problem With Valve Point Loading Effect

Shah

Soni

Bhattacharjee

2023

International Journal of Swarm Intelligence Research

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“…Algorithm 4 divulges that IHCSA commences by approximating the global optimum solutions by creating a population of capuchins with stochastic positions. During the iterative procedure of IHCSA, the capuchins use Equations 12,14,15,16,17,18,21 and 47 to continuously explore and exploit the search domain as they search for optimal food sources, so their position is frequently changed within the search space. Thereafter, the solutions are assessed using a predefined cost function, which is recomputed inside the optimization process to locate the capuchin with the best cost value.…”

Section: Implementation Of the Proposed Ihcsamentioning

confidence: 99%

“…Such modified MH algorithms include island-based harmony search algorithm [10], evolutionary simplex adaptive Hooke-Jeeves algorithm [11], multi-group marine predator algorithm [12], modified Krill Herd Algorithm (KHA) [13], and many more. Such hybrid MH algorithms include hybrid salp swarm algorithm [14], hybrid Grey Wolf Op-timizer (GWO) [15], and others. These methods will be discussed thoroughly in the upcoming sections.…”

Section: Introductionmentioning

confidence: 99%

“…In general, there are two main strategies for dealing with the constraints in an ELD solution: penalty or feasibility [9]. In the penalty strategy, the violations of the constraints may occur in the solution and the significant penalty weight of each constraint violated will be embedded in the evaluation function [12] or an independent objective function can be drafted to handle the violated constraints [14]. The feasibility strategy precludes any constraint violation in the solution.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Capuchin Search Algorithm with Gradient Search Algorithm for Economic Dispatch Problem

Braik

Awadallah

Al-Betar

et al. 2022

Preprint

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Economic Load Dispatch (ELD) is an important task in power systems that is concerned with scheduling a set of thermal generating units to produce specific power at low consumption costs. In this task, there are some operational constraints related to power demand, power output, valve-point loading effect, transmission losses, prohibited operating zones, and ramp-rate limits. ELD is drafted as a non-linear, non-convex, and highly constrained optimization problem with a large number of local minima. Due to the complex and rugged search space of this problem, it has been tackled by many meta-heuristic algorithms. To cope with the above issues of this problem, we presented a novel Improved based Hybrid Capuchin Search Algorithm (IHCSA). First, a memory element was added to CSA to consolidate its position and velocity updating mechanisms in order to exploit the most encouraging candidate solutions. Second, two adaptive functions rather than stationary social and cognitive parameters were used to manage and adequately balance exploration and exploitation of features over the iterations path. Finally, the hybridization was carried out using Gradient Search Algorithm (GBO) and Local Escaping Capability (LEO) to strengthen the intensification ability of CSA and balance its search capabilities to fulfill robust search performance. The proficiency of IHCSA was divulged by assessing it on a computationally difficult ELD problem under 6 different tests with different numbers of generators and loading conditions. The proposed IHCSA provided the best performance, in terms of the minimum cost, among the basic CSA and other optimization methods.

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“…The important characteristics like, simple structure, robustness, and scalability, makes SSA an efficient method for solving various kinds of real world problems (e.g., engineering design and optimization [80], feature selection [38], job shop scheduling [75], optimal power flow problem [22], parameter optimization of power system stabilizer [21], power generation [68], image segmentation [39,84], parameter estimation for soil water retention curve [95], PID controller for AVR system [20], target localization [54]). Also, SSA shows the following outstanding features like: (1) It can be easily applied to different optimization problems without adjusting other parameters except population size and stopping criterion and it is worth mentioning that these parameters are essential for all MHAs; (2) It has a powerful neighbourhood search ability and it can easily fitted for wide search space [8]. Therefore, these advantages make SSA an efficient technique and a rapid growth of the SSA studies has also been noticed recently.…”

Section: Introductionmentioning

confidence: 99%

A hybrid salp swarm algorithm based on TLBO for reliability redundancy allocation problems

2022

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A novel optimization algorithm called hybrid salp swarm algorithm with teaching-learning based optimization (HSSATLBO) is proposed in this paper to solve reliability redundancy allocation problems (RRAP) with nonlinear resource constraints. Salp swarm algorithm (SSA) is one of the newest meta-heuristic algorithms which mimic the swarming behaviour of salps. It is an efficient swarm optimization technique that has been used to solve various kinds of complex optimization problems. However, SSA suffers a slow convergence rate due to its poor exploitation ability. In view of this inadequacy and resulting in a better balance between exploration and exploitation, the proposed hybrid method HSSATLBO has been developed where the searching procedures of SSA are renovated based on the TLBO algorithm. The good global search ability of SSA and fast convergence of TLBO help to maximize the system reliability through the choices of redundancy and component reliability. The performance of the proposed HSSATLBO algorithm has been demonstrated by seven well-known benchmark problems related to reliability optimization that includes series system, complex (bridge) system, series-parallel system, overspeed protection system, convex system, mixed series-parallel system, and large-scale system with dimensions 36, 38, 40, 42 and 50. After illustration, the outcomes of the proposed HSSATLBO are compared with several recently developed competitive meta-heuristic algorithms and also with three improved variants of SSA. Additionally, the HSSATLBO results are statistically investigated with the wilcoxon sign-rank test and multiple comparison test to show the significance of the results. The experimental results suggest that HSSATLBO significantly outperforms other algorithms and has become a remarkable and promising tool for solving RRAP.

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A Non-convex Economic Load Dispatch Using Hybrid Salp Swarm Algorithm

Cited by 34 publications

References 79 publications

Artificial Electric Field Algorithm Applied to the Economic Load Dispatch Problem With Valve Point Loading Effect

Artificial Electric Field Algorithm Applied to the Economic Load Dispatch Problem With Valve Point Loading Effect

A Hybrid Capuchin Search Algorithm with Gradient Search Algorithm for Economic Dispatch Problem

A hybrid salp swarm algorithm based on TLBO for reliability redundancy allocation problems

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