Solution to economic emission load dispatch problem using modified artificial bee colony algorithm

Jadhav, H. T.; Raj, Shubham; Roy, Ranjit

doi:10.1109/epecs.2013.6713021

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…Recently, many studies have been conducted to solve the EED problem. There is a growing interest in many modern random-based metaheuristic algorithms (MAs), because they do not need any derivative information or gradient information in the search process (Jadhav et al, 2013); these methods include particle swarm optimization (PSO) (Cao et al, 2020;Lin et al, 2022), the colony predation algorithm (CPA) (Tu et al, 2021), hunger games search (HGS) (Yang et al, 2021), Harris hawks optimization (HHO) (Heidari et al, 2019), the slime mould algorithm (SMA) (Li et al, 2020a), the weighted mean of vectors (INFO) (Ahmadianfar et al, 2022), and the Runge Kutta optimizer (RUN) (Ahmadianfar et al, 2021), which have yielded great success in a variety of fields, such as feature selection (Hu et al, 2022;Liu et al, 2022), economic emission dispatch (Dong et al, 2021), bankruptcy prediction (Xu et al, 2019;Zhang et al, 2021), train scheduling (Song et al, 2023), image segmentation (Hussien et al, 2022;Yu et al, 2022), multi-objective problems (Hua et al, 2021;Deng et al, 2022a), gate resource allocation (Wu et al, 2020a;Deng et al, 2020), complex optimization problems (Deng et al, 2022b), resource allocation (Deng et al, 2022c), expensive optimization problems (Li et al, 2020b;Wu et al, 2021a), airport taxiway planning (Deng et al, 2022d), robust optimization (He et al, 2020), scheduling problems (Gao et al, 2020;Han et al, 2021;Wang et al, 2022b), and medical diagnosis (Wang et al, 2017) (Chen et al, 2016). Hota et al (2010) used fuzzy computing to solve EED problems using a modified bacterial forag...…”

Section: Introductionmentioning

confidence: 99%

Hybrid kernel search and particle swarm optimization with Cauchy perturbation for economic emission load dispatch with valve point effect

Dong

Chen

et al. 2023

Front. Energy Res.

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Due to growing concerns over environmental protection, economic and environmentally responsible power dispatching has become a hot topic in the field of power system control. Multi-objective optimization minimizes fuel costs and pollution emissions without violating operational constraints. To solve this problem, the MOP is decomposed into individual objects via the weighted sum method, and Newton’s method is used to tackle equality constraints iteratively. To this end, a hybrid algorithm (HKSOPSO-CP) based on kernel search optimization (KSO) and particle swarm optimization (PSO) with Cauchy perturbation is proposed in this paper. An experiment with 23 CEC benchmark functions shows that HKSOPSO-CP offers better performance compared with various popular algorithms proposed in recent years. When employed to solve the IEEE standard economic emission dispatch (EED) problems with 6, 10, 40, and 110 units, the proposed HKSOPSO-CP algorithm produces results indicating a better trade-off between the objectives relating to fuel costs and emissions compared to other algorithms that have recently been reported on in the literature.

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Section: Introductionmentioning

confidence: 99%

Hybrid kernel search and particle swarm optimization with Cauchy perturbation for economic emission load dispatch with valve point effect

Dong

Chen

et al. 2023

Front. Energy Res.

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“…Economic emission dispatch problem (EED) has become an interesting and important task in power system as the environment protection gets more and more attention. EED problem is essentially a Multi-objective Optimization Problem (MOP) [1], which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits such as power balance and generation limits.…”

Section: Introductionmentioning

confidence: 99%

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

Dong

Wang

2020

IEEE Access

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With the increasing concern over environment protection, Economic Emission Dispatch (EED) problem has received much attention. It is essentially a Multi-objective Optimization Problem, which minimizes both fuel cost and emission pollution simultaneously, as well as meets some system limits. This study transforms EED problem to a single-objective problem with weighted sum method, and then use Newton method to solve the equality constraint iteratively and introduce a common penalty function to deal with the inequality constraint. Moreover, this study tries to propose a new meta-heuristic algorithm inspired by kernel tricks to solve EED problem with no hyper parameters to be tuned. The new algorithm can map a non-linear objective function into a linear one with higher-dimension. Thus the optimization process could be transformed into a linear process, which is more likely to get the optimum solution. When applied in the 3 real-world EED cases with valve point, the new algorithm achieved a better performance compared with other algorithms in the literature. INDEX TERMS Economic emission dispatch, Kernel search optimization, meta-heuristic algorithm, swarm intelligence.

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What metaheuristic solves the economic dispatch faster? A comparative case study

2018

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Solution to economic emission load dispatch problem using modified artificial bee colony algorithm

Cited by 7 publications

References 11 publications

Hybrid kernel search and particle swarm optimization with Cauchy perturbation for economic emission load dispatch with valve point effect

Hybrid kernel search and particle swarm optimization with Cauchy perturbation for economic emission load dispatch with valve point effect

New Optimization Algorithm Inspired by Kernel Tricks for the Economic Emission Dispatch Problem With Valve Point

What metaheuristic solves the economic dispatch faster? A comparative case study

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