Güç sisteminde meta-sezgisel algoritmalarla güç kaybı ve gerilim kararlılığı optimizasyonu

Öz

Güç sistemi alanında en belirgin problemlerden biri olan güç akışı, kararlı durum gerilim genlikleri ve güç değerleri bilinen bara verileri kullanılarak her bir baranın gerilim genliklerinin, faz açılarının ve güç kayıplarının hesaplanması işlemidir. Artan talep ve merkezi olmayan yeni enerji kaynaklarının güç sistemine çeşitli noktalardan bağlanması güç akış problemini daha karmaşık hale getirmektedir. Güç akışı problemi hem elektrik üretimi hem de iletimi için büyük önem taşımaktadır. Gelecekte sisteme bağlanabilecek yeni yüklerin planlanması ve mevcut iletim hatlarının tam kapasite ile kullanılması güç akışı sorununun çözümüne dayanmaktadır. Doğrusal olmayan bir problem olan güç akışı geleneksel olarak Newton-Raphson ve Gauss Seidel gibi nümerik yöntemler kullanılarak çözülmüştür. Ancak güç sisteminin şartlarına bağlı olarak klasik çözüm algoritmalarının başarısı azalmaktadır. Son yıllarda geliştirilen meta-sezgisel optimizasyon teknikleri ve arama algoritmaları güç akışı probleminin çözümünde daha iyi sonuçların elde edilebileceğini göstermektedir. Bu çalışmada, Matlab yazılımı kullanılarak oluşturulan IEEE-14 bara test güç sisteminde güç akışı problemini optimize etmek için Yapay Arı Kolonisi (ABC), Gri Kurt (GWO), Parçacık Sürüsü Optimizasyonu (PSO) ve Newton Raphson algoritmaları uygulanmıştır. Algoritmaların performansı model güç sisteminden elde edilen gerilim genlikleri, gerilim sapması, faz açıları, güç kayıpları ve hesaplama süreleri göz önünde bulundurularak karşılaştırılmıştır.

Anahtar Kelimeler

• Güç akışı
• Meta-sezgisel algoritmalar
• Gerilim sapması

Power loss and voltage stability optimization with meta-heuristic algorithms in power system

Öz

Power flow, which is one of the most prominent problems in the field of power system, is the calculation of the voltage amplitudes and phase angles of each bus and the power losses by using the bus data with known steady state voltage amplitudes and power values. Increasing demand and the connection of decentralized energy sources to the power system at various points make more complicated power flow problem. The power flow problem is of great importance for both electricity generation and transmission. Planning new loads that can be connected to the system in the future and using the existing transmission lines at full capacity are based on the solution of the power flow problem. Power flow, which is a nonlinear problem, has traditionally been solved using numerical methods such as Newton-Raphson and Gauss Seidel. However, the success of classical solution algorithms decreases depending on the conditions of the power system. Meta-heuristic optimization techniques and search algorithms developed in recent years show that better results can be obtained in solving the power flow problem. In this study, Artificial Bee Colony (ABC), Gray Wolf (GWO), Particle Swarm Optimization (PSO) and Newton Raphson algorithms have been applied to optimize the power flow problem in the IEEE-14 bus test power system created using Matlab software. The performance of the algorithms has been compared by considering the voltage amplitudes, voltage deviation, phase angles, power losses and calculation times obtained from the model power system.

Anahtar Kelimeler

• Power Flow
• Meta-heuristic algorithms
• Voltage deviation

Kaynakça

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