Examining The Impact of Distributed Generation Size and Location on The Distribution Network

Abstract

Decisions and incentives regarding renewable energy resources increase the number of distributed generation (DG) in the distribution system. It is inevitable to use energy storage systems in order to benefit more from them. However, the installation of energy storage systems is delayed due to high invesment costs. Distribution system planners replace a certain DG capacity in the distribution system to avoid negative effects on the distribution system. This prevents having enough DG in the distribution system. In this study, it is investigated how much DG can be located by maintaining or improving the current state of the distribution system without any energy storage system. For two different purposes which preserves the existing active power loss of the distribution system and reduces the active power loss, DG sizes are obtained. In addition to these, for two different purposes which preserves the existing voltage profile of the distribution system and improves the voltage profile, other DG sizes are obtained, It is examined how the obtained DG sizes affect power losses and busbar voltages of the distribution system. Then which of these objectives improves the distribution system, which negatively affects it, and which increases the YES hosting capacity is discussed. This study shows that the positive effect of DG on the distribution system changes according to its size, its location and the distribution system structure. It offers distribution system planners the notion that the maximum DG capacity for any distribution system may be established in accordance with the distribution system advantages.

Keywords

• Dağıtım sistemi
• Yerel elektrik santrali
• Güç kayıpları
• Gerilim profili
• Uygun büyüklük
• Azami büyüklük

Project Number

116E107

Yerel Elektrik Santral Büyüklüğünün ve Konumunun Dağıtım Şebekesine Etkisi

Abstract

Yenilenebilir enerji kaynaklarının artırılması için alınan kararlar ve teşvikler ile dağıtım sistemindeki yerel elektrik santraller (YES) artmaktadır. Artan YES’lerden daha çok faydalanmak için enerji depolama sistemlerinin kullanılması kaçınılmaz hale gelmektedir. Ancak yüksek yatırım maliyetleri nedeniyle enerji depolama sistemleri kurulumundaki gecikmeye rağmen YES’ler artmaya devam etmektedir. Dağıtım sistemi planlayıcıları, YES’in olumlu etkisinin hangi büyüklükten sonra dağıtım sistemini olumsuz etkilemeye başlayacağını kestiremediğinden dolayı dağıtım sistemine belli oranda YES yerleştirirler. Bu da sisteminde daha büyük oranlarda YES barındırmayı engeller. Bu çalışmada; enerji depolama sistemi olmadan, dağıtım sisteminin mevcut durumunu koruyarak veya iyileştirerek ne kadar YES yerleştirilebileceği araştırılmaktadır. YES'in dağıtım sistemindeki güç kayıplarını ve bara gerilimlerini nasıl etkilediği incelenmektedir. Bu incelemede dağıtım sisteminin mevcut aktif güç kaybını koruyan ve aktif güç kaybını azaltan iki farklı YES büyüklüğü elde edilir. Ayrıca, dağıtım sisteminin mevcut gerilim profilini koruyan ve gerilim profilini iyileştiren iki farklı YES büyüklüğü daha elde edilir. Başka bir deyişle, aktif güç kaybı ve gerilim profili için maksimum ve optimal YES büyüklükleri elde edilmekte ve tartışılmaktadır. Bu çalışma ile YES’in dağıtım sistemi üzerindeki olumlu etkisinin; YES büyüklüğüne, konumuna ve dağıtım sistemi yapısına göre değiştiğini gösterilmektedir. Dağıtım sistemi planlayıcılarına, dağıtım sistemine göre maksimum YES kapasitesi belirlenebileceği fikri sunulmaktadır.

Keywords

• Dağıtım sistemi
• Yerel elektrik santrali
• Güç kayıpları
• Gerilim profili
• Uygun büyüklük
• Azami büyüklük

Supporting Institution

TÜBİTAK

Project Number

116E107

Thanks

Bu çalışma; TÜBİTAK 116E107 nolu “Yüksek Oranda Yerel Elektrik Santralleriyle Beslenmekte Olan Dağıtım Şebekelerinin Etki Haritalarının Çıkarılması” isimli araştırma projesi kapsamında desteklenmiştir. Bu çalışmada kullanılan veriler Sakarya Dağıtım Elektrik A.Ş.’inden temin edilmiştir.

References

1. 1 IEA (2022), Renewables 2022, IEA, Paris https://www.iea.org/reports/renewables-2022, License: CC BY 4.0.
2. 2 Abdmouleh, Z.; Gastli, A.; Ben-Brahim, L.; Haouari, M.; Al-Emadi, N. A. Review of Optimization Techniques Applied for the Integration of Distributed Generation from Renewable Energy Sources. Renew. Energy 2017, 113, 266–280. https://doi.org/10.1016/j.renene.2017.05.087.
3. 3 Sultana, U.; Khairuddin, A. B.; Aman, M. M.; Mokhtar, A. S.; Zareen, N. A Review of Optimum DG Placement Based on Minimization of Power Losses and Voltage Stability Enhancement of Distribution System. Renew. Sustain. Energy Rev. 2016, 63, 363–378. https://doi.org/10.1016/j.rser.2016.05.056.
4. 4 Akorede, M. F.; Hizam, H.; Aris, I.; Ab Kadir, M. Z. A. A Review of Strategies for Optimal Placement of Distributed Generation in Power Distribution Systems. Res. J. Appl. Sci. 2010, 5 (2), 137–145.
5. 5 Kumar, M.; Soomro, A. M.; Uddin, W.; Kumar, L. Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review. Energies 2022, 15 (21). https://doi.org/10.3390/en15217850.
6. 6 Viral, R.; Khatod, D. K. Optimal Planning of Distributed Generation Systems in Distribution System: A Review. Renew. Sustain. Energy Rev. 2012, 16 (7), 5146–5165. https://doi.org/10.1016/j.rser.2012.05.020.
7. 7 Yang, B.; Yu, L.; Chen, Y.; Ye, H.; Shao, R.; Shu, H.; Yu, T.; Zhang, X.; Sun, L. Modelling, Applications, and Evaluations of Optimal Sizing and Placement of Distributed Generations: A Critical State-of-the-Art Survey. Int. J. Energy Res. 2021, 45 (3), 3615–3642. https://doi.org/https://doi.org/10.1002/er.6104.
8. 8 Willis, H. L. Analytical Methods and Rules of Thumb for Modeling DG-Distribution Interaction. In 2000 power engineering society summer meeting (Cat. No. 00CH37134); 2000; Vol. 3, pp 1643–1644.

9. 9 Wang, C.; Nehrir, M. H. Analytical Approaches for Optimal Placement of Distributed Generation Sources in Power Systems. IEEE Trans. Power Syst. 2004, 19 (4), 2068–2076.
10. 10 Ali, E. S.; Abd Elazim, S. M.; Abdelaziz, A. Y. Ant Lion Optimization Algorithm for Optimal Location and Sizing of Renewable Distributed Generations. Renew. Energy 2017, 101, 1311–1324. https://doi.org/https://doi.org/10.1016/j.renene.2016.09.023.
11. 11 El-Ela, A. A. A.; El-Sehiemy, R. A.; Abbas, A. S. Optimal Placement and Sizing of Distributed Generation and Capacitor Banks in Distribution Systems Using Water Cycle Algorithm. IEEE Syst. J. 2018, 12 (4), 3629–3636. https://doi.org/10.1109/JSYST.2018.2796847.
12. 12 Niknam, T.; Taheri, S. I.; Aghaei, J.; Tabatabaei, S.; Nayeripour, M. A Modified Honey Bee Mating Optimization Algorithm for Multiobjective Placement of Renewable Energy Resources. Appl. Energy 2011, 88 (12), 4817–4830. https://doi.org/https://doi.org/10.1016/j.apenergy.2011.06.023.
13. 13 Maciel, R. S.; Rosa, M.; Miranda, V.; Padilha-Feltrin, A. Multi-Objective Evolutionary Particle Swarm Optimization in the Assessment of the Impact of Distributed Generation. Electr. Power Syst. Res. 2012, 89, 100–108. https://doi.org/https://doi.org/10.1016/j.epsr.2012.02.018.
14. 14 Hadian, A.; Haghifam, M.-R.; Zohrevand, J.; Akhavan-Rezai, E. Probabilistic Approach for Renewable Dg Placement in Distribution Systems with Uncertain and Time Varying Loads. In 2009 IEEE Power & Energy Society General Meeting; 2009; pp 1–8. https://doi.org/10.1109/PES.2009.5275458.
15. 15 Chen, Y.; Strothers, M.; Benigni, A. A Stochastic Approach to Optimum Placement of Photovoltaic Generation in Distribution Feeder. In 2016 Clemson University Power Systems Conference (PSC); 2016; pp 1–7. https://doi.org/10.1109/PSC.2016.7462847.
16. 16 Abdelkader, M. A.; Elshahed, M. A.; Osman, Z. H. An Analytical Formula for Multiple DGs Allocations to Reduce Distribution System Losses. Alexandria Eng. J. 2019, 58 (4), 1265–1280. https://doi.org/https://doi.org/10.1016/j.aej.2019.10.009.
17. 17 Farh, H. M. H.; Eltamaly, A. M.; Al-Shaalan, A. M.; Al-Shamma’a, A. A. A Novel Sizing Inherits Allocation Strategy of Renewable Distributed Generations Using Crow Search Combined with Particle Swarm Optimization Algorithm. IET Renew. Power Gener. 2021, 15 (7), 1436–1450. https://doi.org/https://doi.org/10.1049/rpg2.12107.
18. 18 Hassan, A. S.; Sun, Y.; Wang, Z. Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF). Energies 2022, 15 (6). https://doi.org/10.3390/en15062242.
19. 19 Roshan, R.; Ravishankar, B. S.; Mohan, N.; Sandeep Kumar, K. J.; Devaru, D. G. Reassessment of Power Losses and Enhancement of Techno-Economic Feasibility in a Radial Distribution System. In 2022 IEEE 2nd Mysore Sub Section International Conference (MysuruCon); 2022; pp 1–6. https://doi.org/10.1109/MysuruCon55714.2022.9972726.
20. 20 Elkadeem, M. R.; Abd Elaziz, M.; Ullah, Z.; Wang, S.; Sharshir, S. W. Optimal Planning of Renewable Energy-Integrated Distribution System Considering Uncertainties. IEEE Access 2019, 7, 164887–164907. https://doi.org/10.1109/ACCESS.2019.2947308.
21. 21 C, H. P.; Subbaramaiah, K.; Sujatha, P. Optimal DG Unit Placement in Distribution Networks by Multi-Objective Whale Optimization Algorithm & Its Techno-Economic Analysis. Electr. Power Syst. Res. 2023, 214, 108869. https://doi.org/https://doi.org/10.1016/j.epsr.2022.108869.
22. 22 Huiling, T.; Jiekang, W.; Fan, W.; Lingmin, C.; Zhijun, L.; Haoran, Y. An Optimization Framework for Collaborative Control of Power Loss and Voltage in Distribution Systems With DGs and EVs Using Stochastic Fuzzy Chance Constrained Programming. IEEE Access 2020, 8, 49013–49027. https://doi.org/10.1109/ACCESS.2020.2976510.
23. 23 Oskouei, M. Z.; Şeker, A. A.; Tunçel, S.; Demirbaş, E.; Gözel, T.; Hocaoğlu, M. H.; Abapour, M.; Mohammadi-Ivatloo, B. A Critical Review on the Impacts of Energy Storage Systems and Demand-Side Management Strategies in the Economic Operation of Renewable-Based Distribution Network. Sustainability 2022, 14 (4). https://doi.org/10.3390/su14042110.
24. 24 Kesavan, T.; Lakshmi, K. Optimization of a Renewable Energy Source-Based Virtual Power Plant for Electrical Energy Management in an Unbalanced Distribution Network. Sustainability 2022, 14 (18). https://doi.org/10.3390/su141811129.
25. 25 Hai, T.; Zhou, J.; Muranaka, K. Energy Management and Operational Planning of Renewable Energy Resources-Based Microgrid with Energy Saving. Electr. Power Syst. Res. 2023, 214, 108792. https://doi.org/https://doi.org/10.1016/j.epsr.2022.108792.
26. 26 Püvi, V.; Lehtonen, M. Evaluating Distribution Network Optimal Structure with Respect to Solar Hosting Capacity. Electr. Power Syst. Res. 2023, 216, 109019. https://doi.org/https://doi.org/10.1016/j.epsr.2022.109019.
27. 27 Tunçel, S.; Oskouei, M. Z.; \cSeker, A. A.; Gözel, T.; Hocao\uglu, M. H.; Abapour, M.; Mohammadi-Ivatloo, B. Risk Assessment of Renewable Energy and Multi-Carrier Energy Storage Integrated Distribution Systems. Int. J. Energy Res. 2022.
28. 28 Thukaram, D.; Wijekoon Banda, H. M.; Jerome, J. A Robust Three Phase Power Flow Algorithm for Radial Distribution Systems. Electr. Power Syst. Res. 1999, 50 (3), 227–236. https://doi.org/https://doi.org/10.1016/S0378-7796(98)00150-3.