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Journal articles on the topic 'And Economic dispatch algorithm'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Shaimaa, R. Spea. "Solving practical economic load dispatch problem using crow search algorithm." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3431–40. https://doi.org/10.11591/ijece.v10i4.pp3431-3440.

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The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other

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2

Spea, Shaimaa R. "Solving practical economic load dispatch problem using crow search algorithm." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3431. http://dx.doi.org/10.11591/ijece.v10i4.pp3431-3440.

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The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other

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3

DSNM, Rao, and Kumar Niranjan. "Comparisional Investigation of Load Dispatch Solutions with TLBO." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3246–53. https://doi.org/10.11591/ijece.v7i6.pp3246-3253.

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This paper discusses economic load dispatch Problem is modeled with nonconvex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm i

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4

Ali Abttan, Rana, Adnan Hasan Tawafan, and Samar Jaafar Ismael. "Economic dispatch by optimization techniques." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2228. http://dx.doi.org/10.11591/ijece.v12i3.pp2228-2241.

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The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic

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Rana, Ali Abttan, Hasan Tawafan Adnan, and Jaafar Ismael Samar. "Economic dispatch by optimization techniques." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2228–41. https://doi.org/10.11591/ijece.v12i3.pp2228-2241.

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The current paper offers the solution strategy for the economic dispatch problem in electric power system implementing ant lion optimization algorithm (ALOA) and bat algorithm (BA) techniques. In the power network, the economic dispatch (ED) is a short-term calculation of the optimum performance of several electricity generations or a plan of outputs of all usable power generation units from the energy produced to fulfill the necessary demand, although equivalent and unequal specifications need to be achieved at minimal fuel and carbon pollution costs. In this paper, two recent meta-heuristic

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6

Mehdi, M. F., A. Ahmad, S. S. Ul Haq, M. Saqib, and M. F. Ullah. "Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function." Electrical Engineering & Electromechanics, no. 2 (April 10, 2021): 64–69. http://dx.doi.org/10.20998/2074-272x.2021.2.09.

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Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. Novelty. The decision-making method to solve the Dynamic Economic Emission Dispatch problem has a goal for each objective function, for this purpose, the multi-objective problem

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Barcelo, W. R., and P. Rastgoufard. "Dynamic economic dispatch using the extended security constrained economic dispatch algorithm." IEEE Transactions on Power Systems 12, no. 2 (1997): 961–67. http://dx.doi.org/10.1109/59.589791.

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8

Chansareewittaya, Suppakarn. "Economic Dispatch Using Modified Hybrid BA/ATS." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 14, no. 1 (2020): 30–36. http://dx.doi.org/10.37936/ecti-cit.2020141.198845.

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In this paper, a new modified algorithm is proposed. This modified algorithm is BA/ATS. The main modifications are including negative value into the main equation of the bee algorithm (BA) and integrating adaptive tabu search (ATS) into BA. BA/ATS aims to improve the performance of hybrid BA/TS. The economic dispatch (ED) is set as the main problem to solve with the proposed algorithm. The operation of each generator is limit by constraints. All test results indicate that the overall costs of operation when using the proposed algorithm are better than test results from other compared algorithm

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9

Rao, DSNM, and Niranjan Kumar. "Comparisional Investigation of Load Dispatch Solutions with TLBO." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3246. http://dx.doi.org/10.11591/ijece.v7i6.pp3246-3253.

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This paper discusses economic load dispatch Problem is modeled with non-convex functions. These are problem are not solvable using a convex optimization techniques. So there is a need for using a heuristic method. Among such methods Teaching and Learning Based Optimization (TLBO) is a recently known algorithm and showed promising results. This paper utilized this algorithm to provide load dispatch solutions. Comparisons of this solution with other standard algorithms like Particle Swarm Optimization (PSO), Differential Evolution (DE) and Harmony Search Algorithm (HSA). This proposed algorithm

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10

M., F. Mehdi, Ahmad A., S. Ul Haq S., Saqib M., and F. Ullah M. "Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function." Electrical Engineering & Electromechanics, no. 2 (April 5, 2021): 64–69. https://doi.org/10.20998/2074-272X.2021.2.09.

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<strong><em>Introduction.</em></strong><em> Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. <strong>Purpose.</strong> Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. <strong>Novelty.</strong> The decision-making method to solve the Dynamic Economic Emission Dispatch prob

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11

Geem, Zong Woo. "Economic Dispatch Using Parameter-Setting-Free Harmony Search." Journal of Applied Mathematics 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/427936.

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Economic dispatch is one of the popular energy system optimization problems. Recently, it has been solved by various phenomenon-mimicking metaheuristic algorithms such as genetic algorithm, tabu search, evolutionary programming, particle swarm optimization, harmony search, honey bee mating optimization, and firefly algorithm. However, those phenomenon-mimicking problems require a tedious and troublesome process of algorithm parameter value setting. Without a proper parameter setting, good results cannot be guaranteed. Thus, this study adopts a newly developed parameter-setting-free technique c

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12

Latif, Aadil, and Peter Palensky. "Economic Dispatch Using Modified Bat Algorithm." Algorithms 7, no. 3 (2014): 328–38. http://dx.doi.org/10.3390/a7030328.

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13

Wong, K. P., and C. C. Fung. "Simulated annealing based economic dispatch algorithm." IEE Proceedings C Generation, Transmission and Distribution 140, no. 6 (1993): 509. http://dx.doi.org/10.1049/ip-c.1993.0074.

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14

Adarsh, B. R., T. Raghunathan, T. Jayabarathi, and Xin-She Yang. "Economic dispatch using chaotic bat algorithm." Energy 96 (February 2016): 666–75. http://dx.doi.org/10.1016/j.energy.2015.12.096.

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15

Palanichamy, C., and K. Srikrishna. "Simple algorithm for economic power dispatch." Electric Power Systems Research 21, no. 2 (1991): 147–53. http://dx.doi.org/10.1016/0378-7796(91)90029-m.

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16

Sheble, G. B., and K. Brittig. "Refined genetic algorithm-economic dispatch example." IEEE Transactions on Power Systems 10, no. 1 (1995): 117–24. http://dx.doi.org/10.1109/59.373934.

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17

Basu, M., and A. Chowdhury. "Cuckoo search algorithm for economic dispatch." Energy 60 (October 2013): 99–108. http://dx.doi.org/10.1016/j.energy.2013.07.011.

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18

Han, X. S., and H. B. Gooi. "Effective economic dispatch model and algorithm." International Journal of Electrical Power & Energy Systems 29, no. 2 (2007): 113–20. http://dx.doi.org/10.1016/j.ijepes.2006.05.007.

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19

Hardiansyah, Hardiansyah. "Dynamic economic emission dispatch using ant lion optimization." Bulletin of Electrical Engineering and Informatics 9, no. 1 (2020): 12–20. http://dx.doi.org/10.11591/eei.v9i1.1664.

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This paper aims to propose a new meta-heuristic search algorithm, called Ant Lion Optimization (ALO). The ALO is a newly developed population-based search algorithm inspired hunting mechanism of ant lions. The proposed algorithm is presented to solve the dynamic economic emission dispatch (DEED) problem with considering the generator constraints such as ramp rate limits, valve-point effetcs, prohibited operating zones and transmission loss. The 5-unit generation system for a 24 h time interval has been taken to validate the efficiency of the proposed algorithm. Simulation results clearly show

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20

Hardiansyah, Hardiansyah. "Dynamic economic emission dispatch using ant lion optimization." Bulletin of Electrical Engineering and Informatics 9, no. 1 (2020): 12–20. https://doi.org/10.11591/eei.v9i1.1664.

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This paper aims to propose a new meta-heuristic search algorithm, called Ant Lion Optimization (ALO). The ALO is a newly developed population-based search algorithm inspired hunting mechanism of ant lions. The proposed algorithm is presented to solve the dynamic economic emission dispatch (DEED) problem with considering the generator constraints such as ramp rate limits, valve-point effects, prohibited operating zones and transmission loss. The 5-unit generation system for a 24 h time interval has been taken to validate the efficiency of the proposed algorithm. Simulation results clearly show

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21

Zheng, Hong Feng. "An Improved Differential Evolution Algorithm for Dynamic Economic Dispatch of Power Systems." Applied Mechanics and Materials 84-85 (August 2011): 706–10. http://dx.doi.org/10.4028/www.scientific.net/amm.84-85.706.

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Differential Evolution (DE), a vector population based stochastic optimization method has been introduced to the public in 1995. During the last 25 years research on and with DE has reached an impressive state, yet there are still many open questions, In this paper ,An improved differential evolution (IDE) algorithm was presented for power system Dynamic economic dispatch(IDED), Dynamic economic dispatch (DED), an extension of the economic dispatch problem, is a method of scheduling the online generators with a predicted load demand over acertain period of time taking into account the various

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22

Ma, Hongyan. "The role of clustering algorithm-based big data processing in information economy development." PLOS ONE 16, no. 3 (2021): e0246718. http://dx.doi.org/10.1371/journal.pone.0246718.

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The purposes are to evaluate the Distributed Clustering Algorithm (DCA) applicability in the power system’s big data processing and find the information economic dispatch strategy suitable for new energy consumption in power systems. A two-layer DCA algorithm is proposed based on K-Means Clustering (KMC) and Affinity Propagation (AP) clustering algorithms. Then the incentive Demand Response (DR) is introduced, and the DR flexibility of the user side is analyzed. Finally, the day-ahead dispatch and real-time dispatch schemes are combined, and a multi-period information economic dispatch model i

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23

Singh, O. V., and M. Singh. "A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques." International Journal of Software Science and Computational Intelligence 12, no. 2 (2020): 50–73. http://dx.doi.org/10.4018/ijssci.2020040104.

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This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it diffi

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S, Nagaraju. "Comparison of the PSO Algorithm and JAYA Algorithm for Economic Load Dispatch." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30314.

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The electrical power industry has undergone the significant changes, leading to a competitive market and the need for optimal economic dispatch solutions. As energy resources becoming scarce, prices rise, environmental concerns intensify, and electricity consumption increases, classical optimization techniques struggle to handle these complex issues. This project compares particle swarm optimization (PSO) and JAYA optimization method for economic load dispatch (ELD) problems in the electrical power industry. PSO has gained recognition as an effective solution for ELD problems in the last decad

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25

Kim, Jinho, Chang Seob Kim, and Zong Woo Geem. "A Memetic Approach for Improving Minimum Cost of Economic Load Dispatch Problems." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/906028.

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Economic load dispatch problem is a popular optimization problem in electrical power system field, which has been so far tackled by various mathematical and metaheuristic approaches including Lagrangian relaxation, branch and bound method, genetic algorithm, tabu search, particle swarm optimization, harmony search, and Taguchi method. On top of these techniques, this study proposes a novel memetic algorithm scheme combining metaheuristic algorithm and gradient-based technique to find better solutions for an economic load dispatch problem with valve-point loading. Because metaheuristic algorith

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Zahraoui, Younes, Ibrahim Alhamrouni, Saad Mekhilef, Tarmo Korõtko, Awang Jusoh, and Tole Sutikno. "A Chameleon algorithm for solving economic dispatch problem in microgrid system." Bulletin of Electrical Engineering and Informatics 12, no. 4 (2023): 1982–92. http://dx.doi.org/10.11591/beei.v12i4.4700.

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The economic power dispatch (ED) is considered a critical optimization issue in the power system and microgrid. There are several objectives through the economic load dispatch issues such as reducing the operating cost, total emission, or start-up operations. This paper presents a Chameleon swarm algorithm (CSA) for determining the optimal ED of distributed energy resources (DER) in the microgrid. The proposed technique numerically mimics and executes chameleons' behavioral processes to their quest for food, such as their action for rotating their eyes to identify and grab prey using the speed

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Zahraoui, Younes, Ibrahim Alhamrouni, Saad Mekhilef, Tarmo Korõtko, Awang Jusoh, and Tole Sutikno. "A Chameleon algorithm for solving economic dispatch problem in microgrid system." Bulletin of Electrical Engineering and Informatics 12, no. 4 (2023): 1982–92. http://dx.doi.org/10.11591/eei.v12i4.4700.

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The economic power dispatch (ED) is considered a critical optimization issue in the power system and microgrid. There are several objectives through the economic load dispatch issues such as reducing the operating cost, total emission, or start-up operations. This paper presents a Chameleon swarm algorithm (CSA) for determining the optimal ED of distributed energy resources (DER) in the microgrid. The proposed technique numerically mimics and executes chameleons' behavioral processes to their quest for food, such as their action for rotating their eyes to identify and grab prey using the speed

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Dr., A. Subramanian, Sindhu A., and Vijayaraj S. "SOLVING COMBINED ECONOMIC AND EMISSION DISPATCH USING KRILL HERD ALGORITHM." International Journal of Multidisciplinary Research and Modern Education 3, no. 1 (2017): 496–501. https://doi.org/10.5281/zenodo.816243.

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In this paper, fuel cost and the environmental emission functions are considered and formulated as a multi-objective economic load dispatch problem. For obtaining the solution of multi-objective economic load dispatch Krill Herd Algorithm was used. Potency of the algorithm is tested on six unit system. The promising results show the quick convergence and effectiveness of the Krill Herd Algorithm.

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Sulaiman, Mohd Herwan, Zuriani Mustaffa, Muhammad Ikram Mohd Rashid, and Hamdan Daniyal. "Economic Dispatch Solution Using Moth-Flame Optimization Algorithm." MATEC Web of Conferences 214 (2018): 03007. http://dx.doi.org/10.1051/matecconf/201821403007.

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This paper proposes an application of a recent nature inspired optimization technique namely Moth-Flame Optimization (MFO) algorithm in solving the Economic Dispatch (ED) problem. In this paper, the practical constraints will be included in determining the minimum cost of power generation such as ramp rate limits, prohibited operating zones and generators operating limits. To show the effectiveness of proposed algorithm, two case systems are used: 6-units and 15-units systems and then the performance of MFO is compared with other techniques from literature. The results show that MFO is able to

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30

Rachid, Habachi, Touil Achraf, Boulal Abdellah, Charkaoui Abdelkabir, and Echchatbi Abdelwahed. "Economic and emission dispatch using cuckoo search algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3384–90. https://doi.org/10.11591/ijece.v9i5.pp3384-3390.

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The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. This paper proposes the use of Cuckoo Search Algorithm (CSA) for solving the economic and Emission dispatch. The effectiveness of the proposed approach has been tested on 3 generator system.CSA is a new meta-heuristic optimization method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species.The results shows that performance of the proposed app

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31

Zheng, Peng, and Wen Tan Jiao. "The Application of Multi-Objective Particle Swarm Optimization in Economic Dispatch of Power System." Advanced Materials Research 760-762 (September 2013): 2119–22. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.2119.

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Economic dispatch (ED) is a typical power system operation optimization problem. But it has non-smooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult. According to the characteristics of economic dispatch problem, a improved algorithm based on particle swarm optimization for solving economic dispatch strategy is researched in this paper. Multi-objective economic\environmental dispatch demands that the pollutant emission of power plants should reach minimum while the condition of least generation cost should be satisfied. Ac

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Dr., A. Amsavalli, Vigneshwaran D., Lavanya M., and Vijayaraj S. "STUDY OF MULTI-AREA ECONOMIC DISPATCH ON SOFT COMPUTING TECHNIQUES." International Journal of Multidisciplinary Research and Modern Education 2, no. 2 (2016): 351–64. https://doi.org/10.5281/zenodo.168050.

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<em>This paper analyses the performance of soft computing techniques to solve single and multi area economic dispatch problems. The paper also includes of inter-area flow constraints on power system network, which are normally ignored in most economic load dispatch problems. Economic load dispatch results for these two area, three area and four area systems are presented in the paper and they determine the importance of multiple area representation of a system in economic load dispatch. Such representation affects the cost and assures the determination of optimum dispatch.</em>

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Aydın, Mehmet Safa, and Ertuğrul Çam. "Application of Chaotic Maps to Economic Load Dispatch Problem." Karadeniz Fen Bilimleri Dergisi 14, no. 3 (2024): 1630–39. http://dx.doi.org/10.31466/kfbd.1530071.

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This paper aims to solve the economic load dispatch problem (ELD) by using random numbers generated by chaotic maps with particle swarm optimization (PSO). The randomly generated coefficients r1 and r2 in the velocity equation of the PSO algorithm are generated by three different chaotic map methods namely logistic map, gaussian map, and tent map. As a result, three different methods are proposed: PSO with logistic map (LMPSO), PSO with Gaussian map (GMSPO), and PSO with tent map (TMPSO). These algorithms are applied to a 40-unit test system that includes transmission line losses, and the resu

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Wang, Wenjing, and Renjun Zhou. "Application of improved ant-lion algorithm for power systems." PLOS ONE 19, no. 12 (2024): e0311563. https://doi.org/10.1371/journal.pone.0311563.

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An improved ant-lion algorithm is proposed to solve the load allocation problem to improve the efficiency of load allocation in the power system. The global search capability and optimization performance of the algorithm have been significantly improved by introducing elite weights and chaotic search mechanisms. The innovation of the research lies in not only optimizing economic goals, but also considering environmental goals, achieving dual optimization of economy and environment. The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s,

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Hardiansyah, Hardiansyah. "Hybrid PSOGSA technique for solving dynamic economic emission dispatch problem." Engineering review 40, no. 3 (2020): 96–104. http://dx.doi.org/10.30765/er.40.3.10.

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In this paper, a new hybrid population-based algorithm is proposed with the combining of particle swarm optimization (PSO) and gravitational search algorithm (GSA) techniques. The main idea is to integrate the ability of exploration in PSO with the ability of exploration in the GSA to synthesize both algorithms’ strength. The new algorithm is implemented to the dynamic economic emission dispatch (DEED) problem to minimize both fuel cost and emission simultaneously under a set of constraints. To demonstrate the efficiency of the proposed algorithm, a 5-unit test system is used. The results show

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Wang, Yuanyuan, Zexu Yu, Zhenhai Dou, et al. "Decentralized Coordination Dispatch Model Based on Chaotic Mutation Harris Hawks Optimization Algorithm." Energies 15, no. 10 (2022): 3815. http://dx.doi.org/10.3390/en15103815.

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Aiming at the economic dispatch problem for an interconnected system with wind power integration, and in order to realize the goals of system economy and improvement of the cross-regional consumption level of wind energy, a decentralized coordination dispatch model is established in this paper. In this model, a DC tie-line is cut by the branch cutting method and used as a coupling variable. A virtual upper-level dispatch center is established, and the economic dispatch problem to be solved is decomposed into a master optimization problem for the upper-level dispatch center and subsidiary optim

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Habachi, Rachid, Abdellah Boulal, Achraf Touil, Abdelkabir Charkaoui, and Abdelwahed Echchatbi. "Economic and emission dispatch using cuckoo search algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3384. http://dx.doi.org/10.11591/ijece.v9i5.pp3384-3390.

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<p class="Default">The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. This paper proposes the use of Cuckoo Search Algorithm (CSA) for solving the economic and Emission dispatch. The effectiveness of the proposed approach has been tested on 3 generator system. CSA is a new meta-heuristic optimization method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species.The results shows that perfo

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38

Liu, Haiqing, Jinmeng Qu, and Yuancheng Li. "The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 3 (2020): 384–95. http://dx.doi.org/10.2174/2213111607666181226150448.

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Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units

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39

LI Jian. "Modified Plasmodium Evolutionary Algorithm for Economic Dispatch." International Journal of Advancements in Computing Technology 3, no. 11 (2011): 333–39. http://dx.doi.org/10.4156/ijact.vol3.issue11.42.

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40

Hussein, Balasim Mohammed. "Evolutionary algorithm solution for economic dispatch problems." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2963. http://dx.doi.org/10.11591/ijece.v12i3.pp2963-2970.

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<span>A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints; these include the practical operation constraints of the generators (such as the forbidden wo

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Swain, R. K., N. C. Sahu, and P. K. Hota. "Gravitational Search Algorithm for Optimal Economic Dispatch." Procedia Technology 6 (2012): 411–19. http://dx.doi.org/10.1016/j.protcy.2012.10.049.

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42

Po-Hung Chen and Hong-Chan Chang. "Large-scale economic dispatch by genetic algorithm." IEEE Transactions on Power Systems 10, no. 4 (1995): 1919–26. http://dx.doi.org/10.1109/59.476058.

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Mandal, Barun, Provas Kumar Roy, and Sanjoy Mandal. "Economic load dispatch using krill herd algorithm." International Journal of Electrical Power & Energy Systems 57 (May 2014): 1–10. http://dx.doi.org/10.1016/j.ijepes.2013.11.016.

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44

Ghorbani, Naser, and Ebrahim Babaei. "Exchange market algorithm for economic load dispatch." International Journal of Electrical Power & Energy Systems 75 (February 2016): 19–27. http://dx.doi.org/10.1016/j.ijepes.2015.08.013.

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45

Lei, X., E. Lerch, and D. Povh. "Genetic algorithm solution to economic dispatch problems." European Transactions on Electrical Power 9, no. 6 (1999): 347–53. http://dx.doi.org/10.1002/etep.4450090601.

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Balasim, Mohammed Hussein. "Evolutionary algorithm solution for economic dispatch problems." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2963–70. https://doi.org/10.11591/ijece.v12i3.pp2963-2970.

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A modified firefly algorithm (FA) was presented in this paper for finding a solution to the economic dispatch (ED) problem. ED is considered a difficult topic in the field of power systems due to the complexity of calculating the optimal generation schedule that will satisfy the demand for electric power at the lowest fuel costs while satisfying all the other constraints. Furthermore, the ED problems are associated with objective functions that have both quality and inequality constraints, these include the practical operation constraints of the generators (such as the forbidden working areas,

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Said, Mokhtar, Ali M. El-Rifaie, Mohamed A. Tolba, Essam H. Houssein, and Sanchari Deb. "An Efficient Chameleon Swarm Algorithm for Economic Load Dispatch Problem." Mathematics 9, no. 21 (2021): 2770. http://dx.doi.org/10.3390/math9212770.

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Economic Load Dispatch (ELD) is a complicated and demanding problem for power engineers. ELD relates to the minimization of the economic cost of production, thereby allocating the produced power by each unit in the most possible economic manner. In recent years, emphasis has been laid on minimization of emissions, in addition to cost, resulting in the Combined Economic and Emission Dispatch (CEED) problem. The solutions of the ELD and CEED problems are mostly dominated by metaheuristics. The performance of the Chameleon Swarm Algorithm (CSA) for solving the ELD problem was tested in this work.

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Kumar, Sanjay, Vineet Kumar, Nitish Katal, Sanjay Kumar Singh, Sumit Sharma, and Pushpendra Singh. "Multiarea Economic Dispatch Using Evolutionary Algorithms." Mathematical Problems in Engineering 2021 (August 31, 2021): 1–14. http://dx.doi.org/10.1155/2021/3577087.

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Multiarea economic dispatch (MAED) is a vital problem in the present power system to allocate the power generation through dispatch strategies to minimize fuel cost. In economic dispatch, this power generation distribution always needs to satisfy the following constraints: generating limit, transmission line, and power balance. MAED is a complex and nonlinear problem and cannot be solved with classical techniques. Many metaheuristic methods have been used to solve economic dispatch problems. In this study, the dynamic particle swarm optimization (DPSO) and grey wolf optimizer (GWO) have been u

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T, Vijayakumar, and Vinothkanna R. "Efficient Energy Load Distribution Model using Modified Particle Swarm Optimization Algorithm." December 2020 2, no. 4 (2021): 226–31. http://dx.doi.org/10.36548/jaicn.2020.4.005.

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Reduction of emission and energy conservation plays a major role in the current power system for realizing sustainable socio-economic development. The application prospects and practical significance of economic load dispatch issue in the electric power market is remarkable. The various generating sets must be assigned with load capacity in a reasonable manner for reducing the cost of electric power generation. This problem may be overcome by the proposed modified particle swarm optimization (PSO) algorithm. The practical issue is converted and modelled into its corresponding mathematical coun

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Gao, Ren, Juebo Wu, Wen Hu, and Yun Zhang. "An Improved ABC Algorithm for Energy Management of Microgrid." International Journal of Computers Communications & Control 13, no. 4 (2018): 477–91. http://dx.doi.org/10.15837/ijccc.2018.4.3143.

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Microgrids are an ideal way of electricity generation, distribution, and regulation for customers by means of distributed energy resources on the community level. However, due to the randomness of photovoltaic and wind power generation, it is a crucial and difficult problem to achieve optimal economic dispatch in microgrids. In this paper, we present an optimal economic dispatch solution for a microgrid by the improved artificial bee colony (ABC) optimization, with the aim of satisfying load and balance demand while minimizing the cost of power generation and gas emission. Firstly, we construc

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