Electric fish optimization for economic load dispatch problem

Year 2024, , 680 - 689, 15.04.2024

Yağmur Arıkan Yıldız , Özge Pınar Akkaş , Mustafa Saka , Melih Çoban , İbrahim Eke

https://doi.org/10.28948/ngumuh.1390037

Abstract

The Economic Load Dispatch (ELD) problem is an essential aspect of power system planning and operational scheduling. Different techniques and algorithms have been recommended to solve it, aiming to minimize the cost of power generation with satisfying the load requirements. In this paper, a new algorithm called Electric Fish Optimization (EFO) is used to solve the ELD problem by considering the line losses, ramp rate limits, maximum and minimum capacities of the generators and prohibited operating zones (POZ). The algorithm has been utilized in test systems consisting of 6 and 15 units and its outcomes have been compared to those from previous research studies. The proposed algorithm has been shown to achieve minimum cost, indicating its superiority and effectiveness in addressing power system planning challenges. It is evident that the presented algorithm offers a valuable solution for optimizing ELD problems.

Keywords

Economic load dispatch, electric fish optimization, power systems

Ekonomik yük dağitim problemi için elektrik baliği optimizasyonu

Abstract

Ekonomik Yük Dağıtımı (EYD) problemi, güç sistemi ve güç sisteminin işletimi planlamasında çok önemli bir alandır. Bu problem çözmek için yük talebini karşılarken elektrik üretim maliyetini en aza indirmeyi amaçlayan farklı teknikler ve algoritmalar önerilmiştir. Bu çalışmada, hat kayıpları, rampa hız limitleri, jeneratörlerin maksimum ve minimum kapasiteleri ile yasak çalışma bölgeleri dikkate alınarak EYD problemini çözmek için Elektrik Balığı Optimizasyonu (EBO) adı verilen yeni bir algoritma kullanılmıştır. Algoritma 6 ve 15 birimden oluşan test sistemlerinde uygulanmıştır ve sonuçları daha önce yapılan araştırmalarla karşılaştırılmıştır. Önerilen algoritmanın, güç sistemi planlama zorluklarını ele almadaki üstünlüğünü ve etkinliğini gösteren minimum maliyete ulaştığı gösterilmiştir. Önerilen algoritmanın EYD problemlerini optimize etmek için değerli bir çözüm sunduğu sonucuna varılmıştır.

Keywords

Ekonomik yük dağıtımı, elektrik balığı optimizasyonu, güç sistemleri

References

• B. Yanıktepe, T. Kısakürek Parlak and O. Kara, Relationship between energy consumption and economic growth: Turkey. Osmaniye Korkut Ata University Journal of The Institute of Science and Technology, 4 (3),452-465,2021. https://doi.org/10.47495/okufbed.972716.
• M. Karahan, A Modeling of Turkey for energy consumption and economic growth. Master Thesis, Uludağ University, Social Science Institution, Turkey, 2014.
• D. Singh and J. S. Dhillon, Ameliorated grey wolf optimization for economic load dispatch problem. Energy, 169, 398-419, 2019. https://doi.org/10.1016/j.energy.2018.11.034.
• M. Saka, Economic load and emission dispatch analysis at power systems, Master Thesis, Gazi University, Natural and Applied Sciences, Turkey, 2017.
• S. Hemamalini and S. P. Simon, Artificial bee colony algorithm for economic load dispatch problem with non-smooth cost Functions. Electric Power and Components and Systems, 38 (7), 786-803, 2010. https://doi. org/10.1080/15325000903489710.
• M.S. Turgut and G. Kalaycı Demir, Solution of the economic load dispatch problems with artificial cooperative search algorithm. Dokuz Eylul University-Faculty of Engineering Journal of Science and Engineering, 19 (55), 16-27, 2017. https://doi. org/10.21205/deufmd.2017195502.
• I. Eke, S. S.Tezcan and Ç. Çelik, Solving economic load dispatch problem with valve-point effects using filled function. Journal of the Faculty of Engineering and Architecture of Gazi University 32 (2), 429-438, 2017. https://doi. org.tr/10.17341/gazimmfd.322167.
• S. Tosun, A. Öztürk, P. Erdoğmuş, Y. Biçen, U. Hasırcı, Determination of optimal fuel cost in electric power system using simulated annealing (BT) Algorithm. 5th International Advanced Technologies Symposium, Karabuk, Turkey, 2009.
• M. Basu, Economic enviromental dispacth using multi-objective differential evolution. Applied Soft Computing, 11, (2) 2845-2853, 2011. https://doi.org/ 10.1016/j.asoc.2010.11.014.
• X. Yang, S. S.S. Hossesini, Gandomi, A. H., Firefly algorithm for solving nonconvex economic dispatch problems with valve loading effect. Applied Soft Computing 12,1180-1186, 2012. https://doi.org/10.10 16/j.asoc.2011.09.017.
• L. Slimani and T. Bouktir, Economic power dispatch of power systems with pollution control using artificial bee colony algorithm. Turkish Journal of Electrical Engineering and Computer Sciences, 21 (6), 1515-1527, 2013. https://doi.org/ 10.3906/elk-1106-10.
• N. Kumar, U. Nangia and K.B. Sahay, Economic load dispatch using improved particle swarm optimization. 6th IEEE Power India International Conference, Delhi, India, 2014.
• M. H. Sulaiman, Z. Mustaffa, M.R. Mohamed, N.R.H. Abdullah, An application of cuckoo search algorithm for solving combined economic and emission dispatch problem. International Conference on Informatics, Electronics & Vision, Fukuoka, Japan, 2015.
• A. Y. Abdelaziz, E.S. Ali and S. M. Abd Elazim, Implementation of flower pollination algorithm for solving economic load dispatch and combined economic emission dispatch problems in power systems. Energy, 101, 506-518, 2016.
• M. Pradhan, P. K. Roy and T. Pal, Grey wolf optimization applied to economic load dispatch problems. International Journal of Electrical Power& Energy Systems,83, 325-334, 2016.
• I. N. Trivedi, P. Jangir, M. Bhoye and N. Jangir, An economic load dispatch and multiple environmental dispatch problem solution with micgrogrids using interior search algorithm. Neural Computing and Applications, 30, 2173-2189, 2018. https://doi.org/10 .1007/s00521-016-2795-5.
• V. K., Jadoun, V. C. Pandey, N. Gupta, K. R. Niazi and A. Swarnkar, Integration of renewable energy sources in dynamic economic load dispatch problem using an improved fireworks algorithm, 12 (9), 1004-1011, 2018.https://doi.org/ 10.1049/iet-rpg.2017.0744.
• A. Srivastava and D. K. Das, A new aggrandized class topper optimization algorithm to solve economic load dispatch problem in a power system, IEEE Transactions on Cybernetics, 52 (6),4187-4197, 2020. https://doi.org/10.1109/TCYB.2020.3024607.
• D. Das, A., Bhattacharya and R. Narayan Ray, Dragonfly algorithm for solving probabilistic economic load dispatch problems. Neural Computing and Applications, 32, 3029-3045, 2020. https://doi.org/ 10.1007/s00521-019-04268-9.
• S. Deb, E. H. Houssein, M. Said and D. S. Abdelminaam, Performance of turbulent flow of water optimization on economic load dispatch problem. IEEE Access, 9, 77882-77893, 2021. https://doi.org/10.110 9/ACCESS.2021.3083531
• M. H. Hassan, S. Kamel, A. Eid, L. Nasrat, F. Jurado and M. F. Elnaggar, A developed eagle-strategy supply-demand optimizer for solving economic load dispatch problems, Ain Shams Engineering Journal, 14,5,102083,2023.https://doi.org/10.1016/j.asej.2022.102083.
• M.H. Hassan, E.H. Houssein, M.A. Mahdy and S. Kamel, An improved Manta ray foraging optimizer for cost-effective emission dispatch problems. Eng Appl Artif Intell Apr., 100, 104155, 2021. https://doi.org/ 10.1016/j.engappai.2021.104155.
• M.H. Hassan, D. Yousri, S. Kamel and C. Rahmann, A modified Marine predators algorithm for solving single- and multi-objective combined economic emission dispatch problems. Comput Ind Eng 164, 107906,2022.https://doi.org/10.1016/j.cie.2021.107906107906.
• S. Yılmaz and S. Sen, Electric fish optimization: a new heuristic algorithm inspired by electrolocation. Neural Comput & Applic 32, 11543–11578, 2020. https:// doi.org/10.1007/s00521-019-04641-8.
• R. A. Ibrahim, L. Abualigah, A.A. Ewees, M. A.A. Al-ganess, D. Yousri, S. Alshathri, M. A. Elaziz, An Electric Fish-Based Arithmetic Optimization Algorithm for Feature Selection, Entropy, 23,9,1189, 2021. https://doi.org/10.3390/e23091189
• Z-L. Gaing, Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans Power Syst Aug, 18(3), 1187-1195,2003.https://doi.org/10.1109/TPWRS.2003.814889.
• B.R. Adarsh, T. Raghunathan, T. Jayabarathi and X-S, Yang, Economic dispatch using chaotic bat algorithm. Energy, 96, 666-675, 2016. doi: https://doi.org/ 10.1016/j.energy.2015.12.096.
• A.I.Selvakumar and K. A.Thanushkodi, New particle swarm optimization solution to nonconvex economic dispatch problems. IEEE Trans Power Syst, 22,1, 42 51,2007. https://doi.org/10.1109/TPWRS.2006.88913 2
• D.C. Secui, A new modified artificial bee colony algorithm for the economic dispatch problem. Energy Convers Manag Jan., 89,43-62, 2015. https://doi.org/ 10.1016/j.enconman.2014.09.034.
• W.T. Elsayed, Y.G. Hegazy, F.M. Bendary, MS. El-bages, Modified social spider algorithm for solving the economic dispatch problem. Eng Sci Technol an Int J, 19 (4), 1672-1681, 2016. https://doi.org/10.1016/j.jes tch.2016.09.002
• W.T. Elsayed, Y.G, Hegazy, MS. El-bages,FM. Bendary, Improved random drift particle swarm optimization with self-adaptive mechanism for solving the power economic dispatch problem. IEEE Trans Ind Informatics, 13 (3), 1017-1026, 2017. https://doi.org/ 10.1109/TII.2017.2695122.
• N. Noman and H. Iba, Differential evolution for economic load dispatch problems. Electr Power Syst Res Aug, 78 (8), 1322-1331, 2008. https://doi.org/10.1 016/j.epsr.2007.11.007
• W.T. Elsayed, E.F. El-Saadany, A fully decentralized approach for solving the economic dispatch problem. IEEE Trans Power Syst Jul, 30,4,2179-2189, 2015. https://doi.org/10.1109/TPWRS.2014.2360369
• F.Mohammadi and H.A. Abdi, A modified crow search algorithm (MCSA) for solving economic load dispatch problem. Appl Soft Comput, 71, 51-65,2018. https:// doi.org/10.1016/j.asoc.2018.06.040
• M. Fesanghary and M. M. Ardehali, A novel meta-heuristic optimization methodology for solving various types of economic dispatch problem. Energy, 34,6, 757–766, 2009. https://doi.org/10.1016/j.energy.2009.02.00 7.
• K. T. Chaturvedi, M. Pandit, and L. Srivastava, Self-Organizing hierarchical particle swarm optimization for nonconvex economic dispatch. IEEE Transactions on Power Systems, 23 (3), 1079-1087, 2008. https://doi.org/ 10.1109/TPWRS.2008.926455.
• I. Ciornei and E. A. Kyriakides, GA-API solution for the economic dispatch of generation in power system operation. IEEE Transactions on Power Systems, 27,1 233-242, 2012. https://doi.org/10.1109/TPWRS.2011.2 168833
• J. Yu, C-H. Kim, A. Wadood, T. Khurshaid, S. B. Rhee, Jaya Algorithm With SelfAdaptive Multi-Population and Lévy Flights for Solving Economic Load Dispatch Problems. IEEE Access, 7, 21372-21384, 2019. https:// doi.org/ 10.1109/ACCESS.2019.2899043.
• S. Pothiya, I. Ngamroo, W. Kongprawechnon, Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints. Energy Convers Manag Apr, 49 (4), 506-516, 2008. https://doi.org/10.1016/j.enconman.2007.0 8.012.
• C.C Kuo, A novel string structure for economic dispatch problems with practical constraints. Energy Conversin and Management, 49 (12), 3571-3577. https://doi.org/ 10.1016/j.enconman.2008.07.007.
• Y. Yang, B. Wei, H. Liu, Y. Zhang, J. Zhao E. Manla, Chaos firefly algorithm with self-adaptation mutation mechanism for solving large-scale economic dispatch with valve-point effects and multiple fuel options. IEEE Access 6, 45907–45922,2018. https:// doi.org/10.1109/ACCESS.2018.2865960.
• S. Agnihotri, Atre A. and Verma HK. Equilibrium optimizer for solving economic dispatch problem, in 2020 IEEE 9th Power India International Conference (PIICON), Feb. 2020, pp. 1–5. https://doi.org/10.1109/ PIICON49524.2020.9113048.
• S.K. Nayak, K.R. Krishnanand, B.K. Panigrahi and P.K. Rout, Application of artificial bee colony to economic load dispatch problem with ramp rate limits andprohibited operating zones. World Congress on Nature & Biologically Inspired Computing (NaBIC) 1237–42. 2009 https://doi.org/10.1109/NABIC.2009. 5393751
• S.H. Nee Dey, Teaching learning based optimization for different economic dispatch problems. Scientia Iranica, 21,3, 870-884, 2014.
• H. Barati and M. Sadeghi, An efficient hybrid MPSO-GA algorithm for solving nonsmooth/non-convex economic dispatch problem with practical constraints.Ain Shams Eng J Dec. 9 (4), 1279-1287, 2018. https://doi.org/10.1016/j.asej.2016.08.008.
• A. Atre, S. Agnihotri and H.K. Verma, Hybrid EO-SCA based economic load dispatch. In: 2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control. https://doi.org10.1109/ STPEC49749.2020.9297737.
• N. Ghorbani, S. Vakili, E. Babaei and A. Sakhavati, Particle swarm optimization with smart inertia factor for solving non-convex economic load dispatch problems. Int Trans Electr Energy Syst Aug. 24,8, 1120-1133, 2014. https://doi.org/ 10.1002/etep.1766
• X.S. Yang, S.S. Sadat Hosseini and A.H. Gandomi, Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect. Appl. Soft Comput.,12 (3), 11801186,2012. https://doi.org/10.10 16/j.asoc.2011.09.017
• M.N Abdullah, A.H. Abu Bakar, N.A, Rahim, and H. Moklis, Economic load dispatch with nonsmooth cost functions using evolutionary particle swarm optimization. IEEJ Trans. Electr Electron Eng, 8, S1,30-37, 2013. https:// doi.org/10.1002/tee.21915.
• V.S. Aragón, S.C. Esquivel and C.A. Coello Coello, An immune algorithm with power redistribution for solving economic dispatch problems. Inf. Sci. (Ny)., 295609–632 2015. https:// doi.org/10.1016/j.ins.2014.10.026
• N. Ghorbani and E. Babaei, Exchange market algorithm for economic load dispatch. Int J Electr Power Energy Systems, 75, 19-27, 2016. https://doi.org/10.1016/j.ije pes.2015.08.013
• H.T. Jadhav and R. Roy, Gbest guided artificial bee colony algorithm for environmental/economic dispatch considering wind power. Expert System with Applications, 40 (16) 6385–6399. ,2013. https://doi.org/ 10.1016/j.eswa.2013.05.048
• J. Yu, C-H. Kim and S-B. Rhee, Clustering cuckoo search optimization for economic load dispatch problem. Neural Computing and Applications, 32 (22), 16951–69, 2020. https://doi.org/10.1007/s00521-020-05036-w.
• B.K. Panigrahi and V. Ravikumar Pandi, Bacterial foraging optimisation: NelderMead hybrid algorithm for economic load dispatch.IET Generation, Transmission and Distribuition, 2 (4), 556-565, 2008. https://doi. org/10.1049/iet-gtd:20070422.
• S. Khamsawang and S. Jiriwibhakorn DSPSO–TSA for economic dispatch problem with nonsmooth and noncontinuous cost functions. Energy Conversion and Management, 51 (2), 365-375,2010. https://doi.org/ 10.1016/j.enconman.2009.09.034