Optimal power flow (OPF) is the most addressed modern power system planning and operating optimization problem. The complexity of the OPF problem is quite high due to constraints. It becomes a very difficult and high complexity optimization problem with the inclusion of the optimal location and rating of flexible AC transmission system (FACTS) devices. Therefore, in order to obtain the optimal solution for the problem, it is necessary to use the most suitable meta-heuristic search (MHS) algorithm for the structure of OPF problem. In this paper, an up-to-date and strong MHS algorithm known as partial reinforcement optimizer (PRO) were used to solve the OPF problem considering optimal location and rating of the multi-types FACTS devices. The objectives considered in the study were minimization of total cost, minimization of total cost with valve-point loading effect, and minimization of the real power loss. In the simulation studies, four case studies were solved by PRO algorithm and its three rivals such as dingo optimization algorithm, evolutionary mating algorithm, and snow geese algorithm. According to the results of the case studies, PRO algorithm obtained the best solution among them. The performance of PRO algorithm were evaluated using Friedman and Wilcoxon tests. The Friedman test results show that PRO algorithm achieved the best rank first with 1.2333 score value among them. In summary, PRO algorithm achieved a superior performance in solving these case studies.
Optimization Partial reinforcement optimizer Optimal power flow FACTS devices
Birincil Dil | İngilizce |
---|---|
Konular | Elektrik Enerjisi Üretimi (Yenilenebilir Kaynaklar Dahil, Fotovoltaikler Hariç) |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Erken Görünüm Tarihi | 23 Ağustos 2024 |
Yayımlanma Tarihi | 30 Haziran 2024 |
Gönderilme Tarihi | 6 Mayıs 2024 |
Kabul Tarihi | 13 Haziran 2024 |
Yayımlandığı Sayı | Yıl 2024 Cilt: 14 Sayı: 1 |
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