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Journals / Mühendislik Bilimleri ve Tasarım Dergisi / 2025 / Cilt: 13 Sayı: 4

IMPACT OF DISTRIBUTED GENERATION ON THE ELECTRICAL DISTRIBUTION NETWORK OF TEXTILE FACILITIES: A SIMULATION-BASED APPROACH

DAĞITIK ÜRETİMİN TEKSTİL TESİSLERİNİN ELEKTRİK DAĞITIM ŞEBEKESİNE ETKİSİ: SİMÜLASYON TABANLI BİR YAKLAŞIM

Bekir Dursun(Trakya University)0000-0002-7741-8873
Pages
1146–1164
Publication Date
2025-12-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results are presented and analyzed comparatively.

📌 3 Key Takeaways

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Objective & Hypothesis:As global energy demand continues to rise rapidly, traditional centralized generation and long-distance transmission systems are becoming increasingly insufficient.
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Key Findings & Data:In this context, distributed generation (DG), which brings energy production closer to consumption points, is gaining prominence.
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Conclusion & Impact:The results are presented and analyzed comparatively.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Dağıtık Üretim Sistemleri · Yenilenebilir Enerji Entegrasyonu · Yük Akış Analizi

Abstract

As global energy demand continues to rise rapidly, traditional centralized generation and long-distance transmission systems are becoming increasingly insufficient. In this context, distributed generation (DG), which brings energy production closer to consumption points, is gaining prominence. One of the major advantages of DG systems is the local utilization of renewable energy sources such as solar and wind power. While centralized systems are more vulnerable to natural disasters and technical failures, distributed generation diversifies energy supply and enhances grid resilience. In the near future, energy production is expected to be largely managed by consumers in a more flexible and interactive system. Accordingly, DG systems not only meet current energy needs but also play a key role in creating a sustainable, equitable, and robust energy supply. This study investigates the impact of distributed generation on the distribution grid of a textile factory. Using DIgSILENT PowerFactory software, load flow and short-circuit fault analyses were conducted to evaluate the technical effects of DG integration. The results are presented and analyzed comparatively.

Özet

Küresel enerji talebindeki hızlı artış, merkezi üretim ve uzun mesafeli iletim hatlarına dayalı geleneksel sistemlerin yetersizliklerini gün yüzüne çıkarmaktadır. Bu bağlamda, enerji üretimini tüketim noktalarına yakınlaştıran dağıtık üretim sistemleri giderek daha önemli hâle gelmektedir. Güneş ve rüzgâr gibi yenilenebilir enerji kaynaklarının yerel ölçekte değerlendirilmesi, bu sistemlerin en büyük avantajlarından biridir. Merkezi üretim altyapısı, doğal afetler veya teknik arızalar karşısında yüksek düzeyde kırılganlık gösterirken; dağıtık üretim, enerji arzını çeşitlendirerek şebeke dayanıklılığının artırılmasına katkı sağlar. Önümüzdeki yıllarda, enerji üretim süreçlerinin büyük ölçüde tüketiciler tarafından yönetildiği, daha esnek ve etkileşimli bir yapının hâkim olması beklenmektedir. Bu doğrultuda, dağıtık üretim yalnızca mevcut enerji gereksinimlerini karşılamamakta, aynı zamanda sürdürülebilir, adil ve dirençli bir enerji geleceğinin temel bileşenlerinden biri olarak öne çıkmaktadır. Bu çalışmada, bir tekstil fabrikasına ait dağıtım şebekesinde dağıtık üretimin etkileri araştırılmıştır. DIgSILENT PowerFactory yazılımı kullanılarak gerçekleştirilen yük akışı ve kısa devre analizleriyle, dağıtık üretim sisteminin şebeke üzerindeki teknik etkileri değerlendirilmiştir. Elde edilen sonuçlar karşılaştırmalı olarak sunulmuş ve analiz edilmiştir.

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Cite This Article

Dursun, B. (2025). IMPACT OF DISTRIBUTED GENERATION ON THE ELECTRICAL DISTRIBUTION NETWORK OF TEXTILE FACILITIES: A SIMULATION-BASED APPROACH. Mühendislik Bilimleri ve Tasarım Dergisi, Cilt: 13 Sayı: 4, 1146–1164. https://doi.org/10.21923/jesd.1753057

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References (31)

  1. Ahmed, A., Khan, M. F. N., Khan, I., Alquhayz, H., Khan, M. A., & Kiani, A. T. (2021). A novel framework to determine the impact of time varying load models on wind DG planning. IEEE Access, 9, 11342-11357. doi: 10.1109/ACCESS.2021.3050307.
  2. Ali, A. H., Youssef, A. R., George, T., & Kamel, S. (2018). Optimal DG allocation in distribution systems using Ant lion optimizer. 2018 International Conference on Innovative Trends in Computer Engineering (ITCE) (pp. 324-331), Aswan: IEEE. doi: 10.1109/ITCE.2018.8316645.
  3. Ali, M. H., Kamel, S., Hassan, M. H., Tostado-Véliz, M., & Zawbaa, H. M. (2022). An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks. Energy Reports, 8, 582-604. doi: 10.1016/j.egyr.2021.12.023.
  4. Alizadeh, M.I., Moghaddam, M.P., Amjady, N., Siano, P., & Sheikh‐El‐Eslami, M.K. (2016). Flexibility in future power systems with high renewable penetration: A review. Renewable & Sustainable Energy Reviews, 57, 1186-1193. https://doi.org/10.1016/j.rser.2015.12.200.
  5. Aman, M. M., Jasmon, G. B., Bakar, A. H. A., & Mokhlis, H. (2014). A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm. Energy, 66, 202-215. doi: 10.1016/j.energy.2013.12.037.
  6. Bergh, K.V., & Delarue, E. (2015). Cycling of conventional power plants: technical limits and actual costs. Energy Conversion and Management, 97, 70-77. https://doi.org/10.1016/j.enconman.2015.03.026.
  7. Eftekharnejad, S., Vittal, V., Heydt, G.T., Keel, B., & Loehr, J. (2013). Impact of increased penetration of photovoltaic generation on power systems. IEEE Transactions on Power Systems, 28, 893-901. https://doi.org/10.1109/TPWRS.2012.2216294.
  8. Hamdan, I., Alfouly, A., & Ismeil, M.A. (2023). A literature review on hosting capacity methodologies and inverter control technologies for photovoltaic system. 2023 IEEE Conference on Power Electronics and Renewable Energy (CPERE), 1-7.
  9. Hecker, L., Zhou, Z., Osborn, D., & Lawhorn, J. (2009). Value based transmission planning process for joint coordinated system plan. 2009 IEEE Power & Energy Society General Meeting, 1-6. https://doi.org/10.1109/PES.2009.5275807.
  10. Henderson, C. (2014). Increasing the flexibility of coal-fired power plants. IEA Clean Coal Centre.
  11. Holttinen, H., Tuohy, A., Milligan, M.R., Lannoye, E., Silva, V., Muller, S., & Soder, L. (2013). The Flexibility Workout: Managing Variable Resources and Assessing the Need for Power System Modification. IEEE Power and Energy Magazine, 11, 53-62. https://doi.org/10.1109/MPE.2013.2278000.
  12. Hsu, C., Lee, C., & Cheng, P. (2011). A low voltage ride-through technique for grid-connected converters of distributed energy resources. 2010 IEEE Energy Conversion Congress and Exposition, 3388-3395.
  13. Impram, S., Neşe, S.V., & Oral, B. (2020). Challenges of renewable energy penetration on power system flexibility: A survey. Energy Strategy Reviews, 31, 100539. doi: 10.1016/j.esr.2020.100539.
  14. Kundur, P., Paserba, J., Ajjarapu, V., Andersson, G., Bose, A., Cañizares, C.A., Hatziargyriou, N.D., Hill, D.J., Stanković, A.M., Taylor, C.W., Cutsem, T.V., & Vittal, V. (2004). Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions. IEEE Transactions on Power Systems, 19, 1387-1401. https://doi.org/ 10.1109/TPWRS.2004.825981.
  15. Lefton, S.A., Besuner, P.M., Grimsrud, G.P., & Strauss, S.D. (1997). Understand what it really costs to cycle fossil-fired units. Power, 141, 41-46.
  16. Ma, J.D., Silva, V., Belhomme, R., Kirschen, D.S., & Ochoa, L.F. (2013). Evaluating and planning flexibility in sustainable power systems. 2013 IEEE Power & Energy Society General Meeting, 1-11. https://doi.org/10.1109/TSTE.2012.2212471.
  17. Mohseni, M., Masoum, M.A., & Islam, S.M. (2011). Low and high voltage ride-through of DFIG wind turbines using hybrid current controlled converters. The Lancet. https://doi.org/10.1016/j.epsr.2011.02.010.
  18. Mulenga, E., Bollen, M.H., & Etherden, N. (2020). A review of hosting capacity quantification methods for photovoltaics in low-voltage distribution grids. International Journal of Electrical Power & Energy Systems, 115, 105445.
  19. Nguyen, T. P. & Vo, D. N. (2019). Improved stochastic fractal search algorithm with chaos for optimal determination of location, size, and quantity of distributed generators in distribution systems. Neural Computing and Applications, 31(11), 7707-7732. doi: 10.1007/s00521-018-3603-1.
  20. Qamar, N., Arshad, A., Mahmoud, K., & Lehtonen, M. (2023). Hosting capacity in distribution grids: A review of definitions, performance indices, determination methodologies, and enhancement techniques. Energy Science & Engineering, 11, 1536 - 1559.
  21. Ravichandran, S., Dasan, S.G., & Devi, R.P. (2011). Small signal stability analysis of grid connected Photo Voltaic distributed generator system. 2011 International Conference on Power and Energy Systems, 1-6. https://doi.org/10.1109/ICPES.2011.6156620.
  22. Seneviratne, C., & Ozansoy, C.R. (2016). Frequency response due to a large generator loss with the increasing penetration of wind/PV generation – A literature review. Renewable & Sustainable Energy Reviews, 57, 659-668.
  23. Tamimi, B., Cañizares, C.A., & Bhattacharya, K. (2013). System Stability Impact of Large-Scale and Distributed Solar Photovoltaic Generation: The Case of Ontario, Canada. IEEE Transactions on Sustainable Energy, 4, 680-688. https://doi.org/10.1109/TSTE.2012.2235151.
  24. Tielens, P., & Hertem, D.V. (2016). The relevance of inertia in power systems. Renewable & Sustainable Energy Reviews, 55, 999-1009. https://doi.org/10.1016/j. rser.2015.11.016.
  25. Troy, N., Denny, E., & O’Malley, M.J. (2010). Base-Load Cycling on a System With Significant Wind Penetration. IEEE Transactions on Power Systems, 25, 1088-1097. doi: 10.1109/TPWRS.2009.2037326.
  26. Ullah, Z., Wang, S. & Radosavljević, J. (2019). A novel method based on PPSO for optimal placement and sizing of distributed generation. IEEJ Transactions on Electrical and Electronic Engineering, 14(12), 1754-1763. doi: 10.1002/tee.23001.
  27. Ullah, Z., Elkadeem, M. R., Wang, S., Sharshir, S. W. & Azam, M. (2020). Planning optimization and stochastic analysis of RE-DGs for techno-economic benefit maximization in distribution networks. Internet of Things, 11, 100210. doi: 10.1016/j.iot.2020.100210.
  28. Umoh, V.B., Davidson, I.E., Adebiyi, A.A., & Ekpe, U.M. (2023). Methods and Tools for PV and EV Hosting Capacity Determination in Low Voltage Distribution Networks—A Review. Energies.
  29. Vittal, V. (2010). The impact of renewable resources on the performance and reliability of the electricity grid. Bridge, 40, 5-12.
  30. Yang, L., Xu, Z., Østergaard, J., Dong, Z.Y., & Wong, K.P. (2012). Advanced Control Strategy of DFIG Wind Turbines for Power System Fault Ride Through. IEEE Transactions on Power Systems, 27, 713-722. https://doi.org/10.1109/TPWRS.2011.2174387.
  31. Zhang, Y., Zhu, S., Sparks, R., & Green, I. (2012). Impacts of solar PV generators on power system stability and voltage performance. 2012 IEEE Power and Energy Society General Meeting, 1-7. https://doi.org/10.1109/PESGM.2012.6344990.