An Efficient Simulated Annealing Algorithm for Economic Load Dispatch Problems

Hardiansyah, Hardiansyah; Junaidi, Junaidi; Ms, Yohannes

doi:10.12928/telkomnika.v11i1.880

Cited by 8 publications

(3 citation statements)

References 19 publications

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“…The results of presented hybrid algorithms (nPSO, nDE and ihPSODE) are compared with CDE-SQP (Coelho and Mariani 2006), PPSO (Chen and Yeh 2006), APPSO (Chen and Yeh 2006), SFL (Serapião 2009), BFO (Serapião 2009), CCPSO (Park et al 2010), SOMA (Coelho and Mariani 2010), CSOMA (Coelho and Mariani 2010), DE/BBO (Bhattacharya and Chattopadhyay 2010), EDA/DE (Wang et al 2010), ARCGA (Amjady and Rad 2010), TSAGA (Subbaraj et al 2011), MODE (Basu 2011), NSGAII (Basu 2011), PDE (Basu 2011), SPEA-2 (Basu 2011), GA (Kumar and Alwarsamy 2012), PSO (Kumar and Alwarsamy 2012), GSA (Güvenç et al 2012), ABC_PSO (Manteaw and Odero 2012), DE (Kumar and Alwarsamy 2012), QP (Hardiansyah et al 2013), EMOCA (Zhang et al 2013), SA (Hardiansyah et al 2013), CS (Serapiao 2013), DHS (Wang and Li 2013), ABC (Serapiao 2013), FA (Serapiao 2013), MPSO (Hardiansyah 2013), MABC/D/Cat (Secui 2015) and MABC/D/Log (Secui 2015), WOA (Mirjalili and Lewis 2016), FPA (Abdelaziz et al 2016), GA-WOA (Edwin Selva Rex et al 2019), β-GWO (Betar et al 2020), on ELD and CEED test systems.…”

Section: Resultsmentioning

confidence: 99%

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An innovative hybrid algorithm for solving combined economic and emission dispatch problems

Verma

Parouha

2022

Soft Comput

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As environmental concerns have grown, the combined economic emission dispatch (CEED) problem has gotten a lot of attention. Both the cost of fuel and the emission pollution caused by it must be kept to a minimum. As a result, this paper presents an innovative hybrid approach (ihPSODE) for solving CEED problems. This hybrid technique incorporated novel differential evolution (nDE) and particle swarm optimization (nPSO). Where nDE introduces a new mutation approach and crossover rate (to prevent premature convergence) as well as nPSO introduces a new acceleration coefficient, inertia weight and position improve equation (to alleviate the stagnation). So as to balance among local and global search ability, after ihPSODE population evaluation, the best half individuals are determined and the rest individuals are discarded. Then, nPSO is used in the current population (to sustain exploration and exploitation) and nDE is employed in the nPSO generated population (to improve convergence accuracy). The competence of the proposed algorithms (ihPSODE, nPSO and nDE) are inspected on 23 unconstrained benchmark function and then solved 3 test system (3-, 6-and 40-unit) of economic load dispatch (ELD) and 3 test system (3-, 10-and 40-unit) of CEED problem. The experiments have denoted that the proposed algorithms show competitive results and significant performances.

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Section: Resultsmentioning

confidence: 99%

“…Problem Unit Test Systems (UTSys) Description ELD UTS-1 (3-unit test system) (Hardiansyah et al 2013) it involves load demand of 300MW.…”

Section: Unit Test Systemsmentioning

confidence: 99%

An innovative hybrid algorithm for solving combined economic and emission dispatch problems

Verma

Parouha

2022

Soft Comput

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“…In recent times, the knowledge growth of MOTs has given an opportunity to optimize the ED problem in a more practical way than the mathematical techniques. Researchers have implemented many MOTs to solve the problem such as Genetic Algorithm (GA) [3], Evolutionary Algorithms [4], Particle Swarm Optimization (PSO) [5], Evolutionary Programming (EP) [6], Tabu Search (TS) [7], Simulated Annealing (SA) [8], Firefly Algorithm (FA) [9] and Glowworm Swarm Optimization (GWO) [10]. However, many of these techniques and their variants have shown a lack of ability to obtain consistent and robust optimal results reducing their effectiveness in a practical operation.…”

Section: Introductionmentioning

confidence: 99%

Chaos-Enhanced Cuckoo Search for Economic Dispatch with Valve Point Effects

2016

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IntroductionDespite the global agenda of increasing the share of renewable energy production, thermal power plants contribute predominantly to the global electricity production and will continue to do so in the foreseeable future. This warrants a global concern to lower their operating costs. Allocating power generated in these plants in the least possible operating cost while meeting the system constraints has been one of the main concerns of the utility operators globally. To address this, engineers use the economic dispatch (ED) formulations which is a practical power system optimization problem.Because of the non-linearity, non-convexity and the multimodal characteristics present in the cost function of the ED, adopting a metaheuristic optimization technique (which is the state-of-the-art global optimization technique [1]) has two major advantages over the usage of the conventional techniques. Firstly, metaheuristic optimization techniques (MOTs) lead to better problem modelling that reduce assumptions related to problem characterization in terms of nonlinearity. Secondly, MOTs have better ability to obtain optimal solutions as compared with a conventional technique. Both of these aspects lead to optimal generator loadings for least cost operation within the power system. As a result, system operators can benefit from significant cost savings over the years.Earlier formulations of the ED problem were tackled using coventional mathematical techniques such as interior point method, lambda-iteration method and linear programming [2]. However, those methods cannot solve the ED problem when formulated in a non-linear context and they suffer from "curse of dimensionality" problems. In recent times, the knowledge growth of MOTs has given an opportunity to optimize the ED problem in a more practical way than the mathematical techniques. [9] and Glowworm Swarm Optimization (GWO) [10]. However, many of these techniques and their variants have shown a lack of ability to obtain consistent and robust optimal results reducing their effectiveness in a practical operation.

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Planned production of thermal units for reducing the emissions and costs using the improved NSGA II method

Neyestani

Hesari

Hatami

2019

Case Studies in Thermal Engineering

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An Efficient Simulated Annealing Algorithm for Economic Load Dispatch Problems

Abstract: AbstrakMakalah ini menyajikan suatu algoritma simulated annealing (SA)

Cited by 8 publications

References 19 publications

An innovative hybrid algorithm for solving combined economic and emission dispatch problems

An innovative hybrid algorithm for solving combined economic and emission dispatch problems

Chaos-Enhanced Cuckoo Search for Economic Dispatch with Valve Point Effects

Planned production of thermal units for reducing the emissions and costs using the improved NSGA II method

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