SOLVING THE OPTIMAL REACTIVE POWER DISPATCH PROBLEM WITH THE HIPPOPOTAMUS ALGORITHM

Abstract

This study proposes the Hippopotamus Optimization (HO) algorithm, inspired by hippopotamus behavior, for the ORPD problem with the aim of minimizing active power losses in power systems. The proposed method seeks the optimal operating point without violating system constraints. The algorithm's performance was tested on a 14-bus IEEE standard test system and a real 22-bus Turkish power system at the 380 kV level. According to the simulation results, the HO algorithm achieved an 8.51% improvement by reducing active power loss from 13.49 MW to 12.342 MW in the IEEE-14 busbar system. At the same time, it achieved this result with a low shunt compensation capacity of 12.4 MVAr, offering a more economical and efficient solution compared to methods such as PSO, ABC, and ACOR in the literature. In the 22-bar Türkiye system, active power losses were reduced by 80.15%. These results concretely demonstrate that the HO algorithm not only reduces losses but also increases system efficiency through the optimal use of reactive power sources and exhibits superior performance in avoiding local minima.

Keywords

• ORPD
• Optimization
• Active Power Loss
• Hippopotamus Algorithm
• Shunt Capacitor

HİPOPOTAM ALGORİTMASI İLE OPTİMAL REAKTİF GÜÇ DAĞITIMI PROBLEMİNİN ÇÖZÜLMESİ

Abstract

Bu çalışma, güç sistemlerinde aktif güç kayıplarını en aza indirmek amacıyla ORPD problemi için hipopotam davranışlarından esinlenen Hipopotam Optimizasyon (HO) algoritmasını önermektedir. Önerilen yöntem, sistem kısıtlarını ihlal etmeden en iyi çalışma noktasını aramaktadır. Algoritmanın performansı, 14 baralı IEEE standart test sistemi ve 380 kV seviyesindeki 22 baralı gerçek bir Türkiye güç sistemi üzerinde test edilmiştir. Elde edilen simülasyon sonuçlarına göre, HO algoritması IEEE-14 baralı sistemde aktif güç kaybını 13.49 MW’tan 12.342 MW’a düşürerek %8,51 oranında bir iyileşme sağlamıştır. Aynı zamanda, toplam 12.4 MVAr gibi düşük bir şönt kompanzasyon kapasitesi ile bu sonucu elde ederek, literatürdeki PSO, ABC ve ACOR gibi yöntemlere kıyasla daha ekonomik ve verimli bir çözüm sunmuştur. 22 baralı Türkiye sisteminde ise aktif güç kayıpları %80,15 oranında kayıp azaltımı başarılmıştır. Bu sonuçlar, HO algoritmasının sadece kayıpları azaltmakla kalmayıp, aynı zamanda reaktif güç kaynaklarının optimal kullanımıyla sistem verimliliğini artırdığını ve yerel minimumlardan kaçınma konusunda üstün bir performans sergilediğini somut verilerle kanıtlamaktadır

Keywords

• ORGD
• Optimizasyon
• Aktif Güç Kaybı
• Hipopotam Algoritması
• Şönt Kapasitör

References

1. Amiri, M.H., Mehrabi Hashjin, N., Montazeri, M., Mirjalili, S., Khodadadi, N., 2024. Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm. Sci. Rep. 14, 1–50. https://doi.org/10.1038/s41598-024-54910-3
2. Basu, M., 2016. Quasi-oppositional differential evolution for optimal reactive power dispatch. International Journal of Electrical Power and Energy Systems 78, 29–40. https://doi.org/10.1016/j.ijepes.2015.11.067
3. Biswas, P.P., Suganthan, P.N., Mallipeddi, R., Amaratunga, G.A.J., 2019. Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach. Applied Soft Computing Journal 75, 616–632. https://doi.org/10.1016/j.asoc.2018.11.042
4. Bjelogrlic, M., Calovic, M.S., Ristanovic, P., Babic, B.S., 1990. Application of Newton’s optimal power flow in voltage/reactive power control. IEEE Transactions on Power Systems 5, 1447–1454. https://doi.org/10.1109/59.99399
5. Cai, J., Ma, X., Li, Q., Li, L., Peng, H., 2009. A multi-objective chaotic particle swarm optimization for environmental/economic dispatch. Energy Convers. Manag. 50, 1318–1325. https://doi.org/10.1016/j.enconman.2009.01.013
6. Carpentier, J., 1962. Contribution a l’etude du dispaching economique. Bull. Soc. Francaise Electricians 8, 431–447.
7. Dai, C., Chen, W., Zhu, Y., Zhang, X., 2009. Seeker optimization algorithm for optimal reactive power dispatch. IEEE Transactions on Power Systems 24, 1218–1231. https://doi.org/10.1109/TPWRS.2009.2021226
8. Duman, S., Sönmez, Y., Güvenç, U., Yörükeren, N., 2012. Optimal reactive power dispatch using a gravitational search algorithm. IET Generation, Transmission and Distribution 6, 563–576. https://doi.org/10.1049/iet-gtd.2011.0681

9. Ghasemi, M., Ghanbarian, M.M., Ghavidel, S., Rahmani, S., Mahboubi Moghaddam, E., 2014. Modified teaching learning algorithm and double differential evolution algorithm for optimal reactive power dispatch problem: A comparative study. Inf. Sci. (N. Y). 278, 231–249. https://doi.org/10.1016/j.ins.2014.03.050
10. Ghasemi, M., Taghizadeh, M., Ghavidel, S., Aghaei, J., Abbasian, A., 2015. Solving optimal reactive power dispatch problem using a novel teaching-learning-based optimization algorithm. Eng. Appl. Artif. Intell. 39, 100–108. https://doi.org/10.1016/j.engappai.2014.12.001
11. Güvenç, U., Kaymaz, E., 2019. Economic Dispatch Integrated Wind Power Using Coyote Optimization Algorithm, in: 7th International Istanbul Smart Grids and Cities Congress and Fair, ICSG 2019 - Proceedings. Istanbul, pp. 179–183. https://doi.org/10.1109/SGCF.2019.8782354
12. Khazali, A.H., Kalantar, M., 2011. Optimal reactive power dispatch based on harmony search algorithm. International Journal of Electrical Power and Energy Systems 33, 684–692. https://doi.org/10.1016/j.ijepes.2010.11.018
13. Khorsandi, A., Alimardani, A., Vahidi, B., Hosseinian, S.H., 2011. Hybrid shuffled frog leaping algorithm and Nelder-Mead simplex search for optimal reactive power dispatch. IET Generation, Transmission and Distribution 5, 249–256. https://doi.org/10.1049/iet-gtd.2010.0256
14. Kurban, M., Filik, Ü., 2007. Türkiye’deki 22 Baralı 380 Kv’luk Güç Sisteminin İki Farklı Yöntem Kullanılarak Ekonomik Dağıtım Analizi. Sakarya University Journal of Science 11, 78–86. https://doi.org/10.16984/saufbed.11036
15. Liang, R.H., Wang, J.C., Chen, Y.T., Tseng, W.T., 2015. An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration. International Journal of Electrical Power and Energy Systems 64. https://doi.org/10.1016/j.ijepes.2014.09.008
16. Mahadevan, K., Kannan, P.S., 2010. Comprehensive learning particle swarm optimization for reactive power dispatch. Applied Soft Computing Journal 10. https://doi.org/10.1016/j.asoc.2009.08.038
17. Medani, K. ben oualid, Sayah, S., Bekrar, A., 2018. Whale optimization algorithm based optimal reactive power dispatch: A case study of the Algerian power system. Electric Power Systems Research 163. https://doi.org/10.1016/j.epsr.2017.09.001
18. Naderi, E., Narimani, H., Fathi, M., Narimani, M.R., 2017. A novel fuzzy adaptive configuration of particle swarm optimization to solve large-scale optimal reactive power dispatch. Applied Soft Computing Journal 53. https://doi.org/10.1016/j.asoc.2017.01.012
19. Nguyen, T.T., Vo, D.N., 2020. Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives. Neural Comput. Appl. 32. https://doi.org/10.1007/s00521-019-04073-4
20. Quintana, V.H., Santos-Nieto, M., 1989. Reactive-power dispatch by successive quadratic programming. IEEE Transactions on Energy Conversion 4. https://doi.org/10.1109/60.43245
21. Saadat, H., 2011. Power System Analysis: Third Edition. Systems, Controls, Embedded Systems, Energy, and Machines.
22. Saddique, M.S., Habib, S., Haroon, S.S., Bhatti, A.R., Amin, S., Ahmed, E.M., 2022. Optimal Solution of Reactive Power Dispatch in Transmission System to Minimize Power Losses Using Sine-Cosine Algorithm. IEEE Access 10. https://doi.org/10.1109/ACCESS.2022.3152153
23. Shaheen, A.M., El-Sehiemy, R.A., Farrag, S.M., 2018. Integrated Strategies of Backtracking Search Optimizer for Solving Reactive Power Dispatch Problem. IEEE Syst. J. 12. https://doi.org/10.1109/JSYST.2016.2573799
24. Tudose, A.M., Picioroaga, I.I., Sidea, D.O., Bulac, C., 2021. Solving single-and multi-objective optimal reactive power dispatch problems using an improved salp swarm algorithm. Energies (Basel). 14. https://doi.org/10.3390/en14051222
25. Varadarajan, M., Swarup, K.S., 2008. Solving multi-objective optimal power flow using differential evolution. IET Generation, Transmission and Distribution 2. https://doi.org/10.1049/iet-gtd:20070457
26. Yoshida, H., Kawata, K., Fukuyama, Y., Takayama, S., Nakanishi, Y., 2000. A Particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Transactions on Power Systems 15. https://doi.org/10.1109/59.898095
27. Zamzam, T., Shaban, K., Massoud, A., 2023. Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes. Sensors 23. https://doi.org/10.3390/s23167216