Optimal Reaktif Güç Dağıtımı için Equilibrium Optimizasyon Algoritması

Optimal Reaktif Güç Dağıtımı (ORPD), şebekenin güvenilirliğini ve güvenliğini sağlamak ve güç sistemini daha ekonomik bir şekilde işletmek açısından önemli bir araştırma alanıdır. ORPD problemi, aktif güç kayıplarının ve gerilim sapmasının en aza indirilmesi ve gerilim kararlılık performansının iyileştirilmesi dahil olmak üzere çeşitli açılardan oluşturulabilir. ORPD problemiyle başa çıkmak için kullanılan yöntemlerin çoğu, problemin karmaşık, doğrusal olmayan ve dışbükey olmayan doğası nedeniyle meta-sezgisel tekniklerdir. Bu çalışmada, ORPD probleminin PV baralardaki gerilim büyüklükleri, transformatörlerin kademe pozisyonları ve şönt ekiomanların reaktif güç desteği gibi kontrol değişkenlerinin optimal ayarlarına ulaşması için fizik-tabanlı yeni bir meta-sezgisel algoritma olan Equilibrium Optimizer (EO) önerilmiştir. Tanıtılan algoritma, çeşitli hedefler kullanılarak IEEE 30-baralı test sistemi üzerinde değerlendirilmiştir ve etkinliğini tespit edebilmek için uygulanan yöntemin literatürde açıklanan diğer optimizasyon teknikleri ile karşılaştırılması yapılmıştır. Simülasyon sonuçları ve istatistiksel göstergeler, EO algoritmasının ORPD problemini çözme açısından etkinliğini ve sağlamlığını doğrulamaktadır.

Anahtar Kelimeler:

Equilibrium optimizasyon algoritması, meta-sezgisel, optimal reaktif güç dağıtımı, optimizasyon algoritmaları

Equilibrium Optimizer Algorithm for Optimal Reactive Power Dispatch

Optimal Reactive Power Dispatch (ORPD) is a significant research area in terms of maintaining the reliability and safety of the power system and operating it more economically. ORPD problem can be formed from a variety of perspectives including the minimization of the active power losses and voltage deviation, and improving the voltage stability performance. The majority of methods so as to deal with ORPD problem is meta-heuristic techniques because of the complex, non-linear and non-convex nature of the problem. In this paper, a new physic-based meta-heuristic algorithm, Equilibrium Optimizer (EO), is proposed for ORPD problem to reach the optimal settings of control variables such as voltage magnitudes in PV buses, tap positions of transformers and reactive power support of shunt devices. The introduced algorithm is evaluated on IEEE 30-bus test system by using various objectives, and a comparison of the implemented method to other optimization techniques described in the literature is utilized to assess its efficacy. Simulation results and statistical indicators demonstrate that the EO algorithm validates its computational efficacy and robustness in handling the ORPD problem.

Keywords:

Optimal reactive power dispatch, Meta-heuristics, Optimization algorithms, Equilibrium Optimizer,

PDF

___

Abaza, A., Fawzy, A., El-Sehiemy, R. A., Alghamdi, A. S., Kamel, S., 2021. Sensitive reactive power dispatch solution accomplished with renewable energy allocation using an enhanced coyote optimization algorithm. Ain Shams Engineering Journal, 12(2), 1723–1739.
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.
Duman, S., 2018. FACTS Cihazlarını İçeren Reaktif Güç Planlama Probleminin Hibrit PSOGSA Algoritması Kullanarak Çözülmesi. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 6, 1234–1257.
Duman, S., Sönmez, Y., Güvenç, U., Yörükeren, N., 2012. Optimal reactive power dispatch using a gravitational search algorithm. IET Generation, Transmission and Distribution, 6(6), 563–576.
Elsayed, S. K., Elattar, E. E., 2021. Slime mold algorithm for optimal reactive power dispatch combining with renewable energy sources. Sustainability, 13(11).
Ettappan, M., Vimala, V., Ramesh, S., Kesavan, V. T., 2020. Optimal reactive power dispatch for real power loss minimization and voltage stability enhancement using Artificial Bee Colony Algorithm. Microprocessors and Microsystems, 76.
Faramarzi, A., Heidarinejad, M., Stephens, B., Mirjalili, S., 2020. Equilibrium optimizer: A novel optimization algorithm. Knowledge-Based Systems, 191.
Gangotri, K. M., Bhimwal, M. K., 2010. Genetic algorithm based reactive power dispatch for voltage stability improvement. International Journal of Electrical Power & Energy Systems, 32(10), 1151–1156.
Granville, S., 1994. Optimal reactive dispatch through interior point methods. IEEE Transactions on Power Systems, 9(1), 136–146.
Grudinin, N., 1998. Reactive power optimization using successive quadratic programming method. IEEE Transactions on Power Systems, 13(4), 1219–1225.
Güvenç, U., Bingöl, O., Özkaya, B., 2020. Optimal Reakti̇ f Güç Dağıtımı içi̇ n Kir Kurdu Opti̇ mi̇ zasyon Algori̇ tmasi. Mühendislik Bilimleri ve Tasarım Dergisi, 8(5), 1–10.
Hussain, K., Salleh, M. N. M., Cheng, S., Shi, Y, 2019. On the exploration and exploitation in popular swarm-based metaheuristic algorithms. Neural Computing and Applications, 31(11), 7665–7683.
Kanagasabai, L., 2020. Solving optimal reactive power problem by Alaskan Moose Hunting, Larus Livens and Green Lourie Swarm Optimization Algorithms. Ain Shams Engineering Journal, 11(4), 1227–1235.
Kessel, P., Glavitsch, H., 1986. Estimating the Voltage Stability of a Power System. IEEE Transactions on Power Delivery, 3, 346–354.
Li, Y., Wang, Y., Li, B., 2013. A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow. International Journal of Electrical Power & Energy Systems, 52(1), 25–33.
Nasouri Gilvaei, M., Jafari, H., Jabbari Ghadi, M., Li, L., 2020. A novel hybrid optimization approach for reactive power dispatch problem considering voltage stability index. Engineering Applications of Artificial Intelligence, 96.
Nguyen, T. T., Vo, D. N., 2020. Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives. Neural Computing and Applications, 32, 5919–5950.
pg_tca30bus. (n.d.). Retrieved February 19, 2022, from http://labs.ece.uw.edu/pstca/pf30/pg_tca30bus.htm
Rajan, A., Malakar, T., 2016. Exchange market algorithm based optimum reactive power dispatch. Applied Soft Computing Journal, 43, 320–336.
Robbins, B. A., Domínguez-García, A. D., 2016. Optimal Reactive Power Dispatch for Voltage Regulation in Unbalanced Distribution Systems. IEEE Transactions on Power Systems, 31(4), 2903–2913.
Saddique, M. S., Bhatti, A. R., Haroon, S. S., Sattar, M. K., Amin, S., Sajjad, I. A., ul Haq, S. S., Awan, A. B., Rasheed, N., 2020. Solution to optimal reactive power dispatch in transmission system using meta-heuristic techniques―Status and technological review. Electric Power Systems Research, 178.
Shaheen, M. A. M., Hasanien, H. M., Alkuhayli, A., 2021. A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution. Ain Shams Engineering Journal, 12(1), 621–630.
Singh, R. P., Mukherjee, V., Ghoshal, S. P., 2015. Optimal reactive power dispatch by particle swarm optimization with an aging leader and challengers. Applied Soft Computing, 29, 298–309.
Sulaiman, M. H., Mustaffa, Z., Mohamed, M. R., Aliman, O., 2015. Using the gray wolf optimizer for solving optimal reactive power dispatch problem. Applied Soft Computing, 32, 286–292.
Sulaiman, M. H., Mustaffa, Z., Saari, M. M., Daniyal, H., 2020. Barnacles Mating Optimizer: A new bio-inspired algorithm for solving engineering optimization problems. Engineering Applications of Artificial Intelligence, 87.
Thieu, N. van, & Molina, D. (2021). Meta-Heuristic Algorithms using Python (MEALPY). Zenodo. https://doi.org/10.5281/zenodo.5789724.