Cost Optimization for Sustainable Economy with Heuristic Algorithms in Power System
Yazarlar (2)
Dr. Öğr. Üyesi Serkan İŞCAN Sinop Üniversitesi, Türkiye
Gürcan Lokman
Milli Savunma Üniversitesi, Türkiye
Milli Savunma Üniversitesi, Türkiye
| Makale Türü |
Özgün Makale
(Diğer hakemli uluslarası dergilerde yayınlanan tam makale)
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| Dergi Adı | Turkish Journal of Engineering Research and Education | ||
| Dergi Tarandığı Indeksler | Directory of Research Journals Indexing | ||
| Makale Dili | İngilizce | Basım Tarihi | 04-2024 |
| Cilt / Sayı / Sayfa | 3 / 1 / 26–37 | DOI | – |
| Makale Linki | https://dergipark.org.tr/en/download/article-file/3589705 | ||
| UAK Araştırma Alanları |
Elektrik Enerjisi ve Güç Sistemleri
Elektrik Tesisleri
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| Özet |
| Economically transmitting the energy obtained from power generation units through transmission and distribution lines is critical for environmentally friendly and sustainable energy management. The component that plays an important role in delivering electrical energy from production units to distribution and consumption units is the transmission/distribution network. At this stage, economic sustainability of the generated active and reactive power is possible by keeping operating costs and loss expenses under control. Insufficient power generation units or increased losses increase the operating costs in power systems. Capacity excess and cost increase affect stability by reducing system reliability. These negativities can cause problems in power systems and negatively affect consumers by making the power transmission network unusable. Developing technology and increasing energy demands bring quality problems in power systems. The operating costs of existing power generation units, which will provide the increasing demand power with the most appropriate cost and power generation, need to be revised with optimization techniques. Thus, the efficiency of power systems can be increased. If power systems are inadequate, new and renewable power generation units should be included in the power system. In this study, power system operation and cost optimizations were carried out with Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms that use swarm intelligence on IEEE 30-bus test systems. Significant differences in the results were observed when the number of population and re-runs were selected as … |
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