Renewable Distributed Generation (RDG) is a promising alternative to conventional power generation methods because it reduces power losses and dependence on central power generation. However, when DG is deployed, it doesn’t always provide the reactive power needed for proper voltage regulation leading to low voltage on some buses. To achieve the maximum benefits of a DG unit, a combined DG and D-STATCOM allocation is evaluated. The selection of the optimal capacity and position of these compensators requires appropriate optimization methods to be solved. The real and reactive power loss reduction and voltage profile improvement was selected as objective function and the Artificial Bee Colony (ABC) optimization algorithm was used to solve the optimal allocation problem under variable load conditions. Four case studies, including combined DG / D-STATCOM at the same location (Case III) and combined DG / D-STATCOM at separate locations (case IV), were considered under different load factors of normal, light and peak loading conditions. The performance analysis of these approaches was tested on the standard IEEE 33-bus radial distribution system. The MATLAB 2021b environment was used for the simulations. The outcomes showed that applying optimal DG and D-STACOM at separate locations resulted in a better percentage real power loss reduction of (76.34%, 75.95%, and 75.41%) compared to combined DG/D-STATCOM at the same location, which recorded (72.41%, 71.62% and 71.12%) under normal, light and peak loading conditions. Similarly, optimal DG/DSTATCOM at separate locations recorded better reactive power loss reduction (72.71%, 72.71%, and 72.11%) compared to DG/D-STATCOM at the same location, which recorded (66.57%, 66.57%, and 65.98%) under the said loading conditions. However, DG/D-STATCOM at the same location offered slightly better voltage profile improvement.
Published in | American Journal of Electrical Power and Energy Systems (Volume 12, Issue 4) |
DOI | 10.11648/j.epes.20231204.12 |
Page(s) | 68-76 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2023. Published by Science Publishing Group |
Distribution Static Compensator (D-STATCOM), Distributed Generation (DG), Artificial Bee Colony, Distribution System
[1] | Marwali, Mohammad N., Jin-woo Jung, and Ali Keyhani (2004). Control of Distributed Generation Systems — Part II : Load Sharing Control. IEEE Transactions on Power Electronics 19 (6). doi: 10.1109/TPEL.2004.836634. |
[2] | Zeineldin, H. H., Ehab F. El-Saadany, and M. M. A. Salama (2006). “Impact of DG Interface Control on Islanding Detection and Nondetection Zones. IEEE Transactions on Power Delivery 21 (3) doi: 10.1109/TPWRD.2005.858773. |
[3] | J. Machowski, J. W. Bialek, J. R. Bumby (2011). Power System Dynamics: Stability and Control. Second Edion. doi: 10.1007/978-1-4471-2291-3_5.. |
[4] | Pandi, V. Ravikumar, H. H. Zeineldin, and Weidong Xiao (2012). Distributed Generation Resources Considering Harmonic and Protection Coordination Limits. IEEE Transactions on Power Systems. 8 (2) doi: 10.1109/TPWRS.2012.2209687. |
[5] | Shuaibu Hassan, Abdurrahman, Yanxia Sun, and Zenghui Wang (2020). Optimization Techniques Applied for Optimal Planning and Integration of Renewable Energy Sources Based on Distributed Generation: Recent Trends. Cogent Engineering 7 (1). doi: 10.1080/23311916.2020.1766394. |
[6] | Sultana, U., Azhar B. Khairuddin, M. M. Aman, A. S. Mokhtar, and N. Zareen (2016). A Review of Optimum DG Placement Based on Minimization of Power Losses and Voltage Stability Enhancement of Distribution System. Renewable and Sustainable Energy Reviews 63: 363–78. doi: 10.1016/j.rser.2016.05.056. |
[7] | Gupta, Atma Ram, and Ashwani Kumar (2015). Energy Savings Using D-STATCOM Placement in Radial Distribution System. Procedia Computer Science (70) 558–64. doi: 10.1016/j.procs.2015.10.100. |
[8] | Gupta, Atma Ram, and Ashwani Kumar (2019). Deployment of Distributed Generation with D-FACTS in Distribution System: A Comprehensive Analytical Review. IETE Journal of Research 68 (3). doi: 10.1080/03772063.2019.1644206. |
[9] | Sirjani, Reza, and Ahmad Rezaee Jordehi (2017). Optimal Placement and Sizing of Distribution Static Compensator (D-STATCOM) in Electric Distribution Networks: A Review. Renewable and Sustainable Energy Reviews 77 (October 2016). doi: 10.1016/j.rser.2017.04.035. |
[10] | Duong, Minh Quan, Thai Dinh Pham, Thang Trung Nguyen, Anh Tuan Doan, and Hai Van Tran. (2019). Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems. Energies 12 (1). doi: 10.3390/en12010174. |
[11] | Zadehbagheri, Mahmoud (2013). Optimal DG Placement in Distribution Networks Using Shuffled Frog Leap Algorithm. in Proceedings of 4th International Graduate Conference on Engineering, Science and Humanities IGCESH. |
[12] | Tan, Zhukui, Ming Zeng, and Liming Sun (2021). Optimal Placement and Sizing of Distributed Generators Based on Swarm Moth Flame Optimization. Frontiers in Energy Research. 9. doi: 10.3389/fenrg.2021.676305. |
[13] | Umar Musa, Ganiyu Ayinde Bakare, Mohammed Aminu Shehu, and Umar Abubakar (2017). D-STATCOM Placement in Distribution Systems Using Weighted Artificial Fish Swarm Algorithm. IEEE 3rd International Conference on Electro-Technology for National Development (NIGERCON). |
[14] | Yuvaraj, T., K. Ravi, and K. R. Devabalaji. (2015). D-STATCOM Allocation in Distribution Networks Considering Load Variations Using Bat Algorithm.” Ain Shams Engineering Journal 8 (3). doi: 10.1016/j.asej.2015.08.006. |
[15] | Taher, Seyed Abbas, and Seyed Ahmadreza Afsari (2014). Optimal Location and Sizing of DSTATCOM in Distribution Systems by Immune Algorithm. International Journal of Electrical Power and Energy Systems 60: 34–44. doi: 10.1016/j.ijepes.2014.02.020. |
[16] | Oloulade, A., A. Moukengue Imano, A. Viannou, and H. Tamadaho (2018). Optimization of the Number, Size and Placement of D-STATCOM in Radial Distribution Network Using Ant Colony Algorithm. American Journal of Engineering Research and Reviews 1–13. doi: 10.28933/AJOERR. |
[17] | Mela Lashiru Lele, Aliyu Usman Otaru, Ganiyu Ayinde Bakare and Musa Mustapha (2022). Application of Firefly Algorithm to the Optimal Siting and Sizing of D-STATCOM in Distribution Networks. IEEE 4th International Conference on Disruptive Technologies for Sustainable Development, NIGERCON 2022 - Proceedings. |
[18] | Prabu, J., and S. Muthuveerapan (2016). Optimum Placement and Sizing Determination of Distributed Generation and DSTATCOM Using Penguins Search. International Journal of Innovative Research in Science, Engineering and Technology 6675–80. doi: 10.15680/IJIRSET.2016.0505010. |
[19] | Salkuti, Surender Reddy. (2022). An Efficient Allocation of D-STATCOM and DG with Network Reconfiguration in Distribution Networks. International Journal of Advanced Technology and Engineering Exploration 9 (88). doi: http://dx.doi.org/10.19101/IJATEE.2021.874812 |
[20] | Gupta, Atma Ram (2018). Effect of Optimal Allocation of Multiple DG and D-STATCOM in Radial Distribution System for Minimizing Losses and THD. 2017 7th International Symposium on Embedded Computing and System Design, ISED. doi: 10.1109/ISED.2017.8303936. |
[21] | Sannigrahi, Surajit, Sriparna Roy Ghatak, and Parimal Acharjee (2019). Multi-Objective Optimisation-Based Active Distribution System Planning with Reconfiguration, Intermittent RES, and D-STATCOM. IET Renewable Power Generation 13 (13). doi: 10.1049/iet-rpg.2018.6060. |
[22] | Hariprasad, C H, R. Kayalvizhi, N. Karthik (2022). Optimum Restructuring of Radial Distribution Network with Integration of DG and D-STATCOM Using Artificial Fish Swarm Optimization Technique. IEEE International Conference on Sustainable Energy and Future Electric Transportation. |
[23] | Tejaswini, V., and D. Susitra. (2020). Optimal Placement of D-STATCOM Using Artificial Bee Colony Algorithm. International Journal of Advanced Science and Technology 29 (6 Special Issue). |
[24] | Kaswan Kuldeep, Singh, Choudhary, Sunita Sharrma, Kapil (2017). Applications of Artificial Bee Colony Optimization Technique Survey. 2nd International Conference on Computing for Sustainable Global Development (INDIACom). |
[25] | Nabil, Mohd, Bin Muhtazaruddin, Jamani Jasrul, Jamian, and Goro Fujita. (2014). Determination of Optimal Output Power and Location for Multiple Distributed Generation Sources Simultaneously by Using Artificial Bee Colony. IEEJ Transactions on Electrical and Electronics Engineering 9 (4): 351–59. doi: 10.1002/tee.21979. |
[26] | Altwaijry, Najwa, Malak Almasoud, Areej Almalki, and Isra Al-Turaiki (2020). Multiple Sequence Alignment Using a Multiobjective Artificial Bee Colony Algorithm. ICCAIS 2020 - 3rd International Conference on Computer Applications and Information Security. doi: 10.1109/ICCAIS48893.2020.9096734. |
[27] | Ghambari, Soheila, and Amin Rahati. (2018). An Improved Artificial Bee Colony Algorithm and Its Application to Reliability Optimization Problems. Applied Soft Computing (62) 736-767. doi: 10.1016/j.asoc.2017.10.040. |
[28] | Muhtazaruddin, M. N. B., Bani, N. A., Mohd Aris, S. A., Jalil, S. Z. A., Mad Kaidi, H., Abd Fatah, A. Y., Jamian, J. J., Muhammad-Sukki, F. And Abu-Bakar, S. H. (2017). Distribution Power Loss Minimization via Distributed Generation, Capacitor and Network Reconfiguration. International conference on electrical, electronic, communication and control engineering, (ICEECC2016). Johor Bahru, Malaysia. |
[29] | Karaboga, D., and B. Bastur (2008). On the Performance of Artificial Bee Colony (ABC) Algorithm. Applied Soft Computing Journal 8 (1). doi: 10.1016/j.asoc.2007.05.007. |
[30] | Linh, Nguyen Tung, and Dam Xuan Dong (2013). Optimal Location and Size of Distributed Generation in Distribution System by Artificial Bees Colony Algorithm. International Journal of Information and Electronics Engineering 3 (1): doi: 10.7763/IJIEE.2013.V3.267. |
[31] | Kefayat, M., A. Lashkar Ara, and S. A. Nabavi Niaki (2015). A Hybrid of Ant Colony Optimization and Artificial Bee Colony Algorithm for Probabilistic Optimal Placement and Sizing of Distributed Energy Resources. Energy Conversion and Management. (92) 149-161. doi: 10.1016/j.enconman.2014.12.037. |
[32] | Vita, Vasiliki (2017). Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks. Energies 10 (9) doi: 10.3390/en10091433. |
APA Style
Musa Mustapha, Ganiyu Ayinde Bakare, Yau Shuaibu Haruna, Babagana Mallambe Mustapha, Musa Baba Lawan, et al. (2023). Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations. American Journal of Electrical Power and Energy Systems, 12(4), 68-76. https://doi.org/10.11648/j.epes.20231204.12
ACS Style
Musa Mustapha; Ganiyu Ayinde Bakare; Yau Shuaibu Haruna; Babagana Mallambe Mustapha; Musa Baba Lawan, et al. Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations. Am. J. Electr. Power Energy Syst. 2023, 12(4), 68-76. doi: 10.11648/j.epes.20231204.12
AMA Style
Musa Mustapha, Ganiyu Ayinde Bakare, Yau Shuaibu Haruna, Babagana Mallambe Mustapha, Musa Baba Lawan, et al. Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations. Am J Electr Power Energy Syst. 2023;12(4):68-76. doi: 10.11648/j.epes.20231204.12
@article{10.11648/j.epes.20231204.12, author = {Musa Mustapha and Ganiyu Ayinde Bakare and Yau Shuaibu Haruna and Babagana Mallambe Mustapha and Musa Baba Lawan and Abdulkadir Abubakar Sadiq}, title = {Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations}, journal = {American Journal of Electrical Power and Energy Systems}, volume = {12}, number = {4}, pages = {68-76}, doi = {10.11648/j.epes.20231204.12}, url = {https://doi.org/10.11648/j.epes.20231204.12}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20231204.12}, abstract = {Renewable Distributed Generation (RDG) is a promising alternative to conventional power generation methods because it reduces power losses and dependence on central power generation. However, when DG is deployed, it doesn’t always provide the reactive power needed for proper voltage regulation leading to low voltage on some buses. To achieve the maximum benefits of a DG unit, a combined DG and D-STATCOM allocation is evaluated. The selection of the optimal capacity and position of these compensators requires appropriate optimization methods to be solved. The real and reactive power loss reduction and voltage profile improvement was selected as objective function and the Artificial Bee Colony (ABC) optimization algorithm was used to solve the optimal allocation problem under variable load conditions. Four case studies, including combined DG / D-STATCOM at the same location (Case III) and combined DG / D-STATCOM at separate locations (case IV), were considered under different load factors of normal, light and peak loading conditions. The performance analysis of these approaches was tested on the standard IEEE 33-bus radial distribution system. The MATLAB 2021b environment was used for the simulations. The outcomes showed that applying optimal DG and D-STACOM at separate locations resulted in a better percentage real power loss reduction of (76.34%, 75.95%, and 75.41%) compared to combined DG/D-STATCOM at the same location, which recorded (72.41%, 71.62% and 71.12%) under normal, light and peak loading conditions. Similarly, optimal DG/DSTATCOM at separate locations recorded better reactive power loss reduction (72.71%, 72.71%, and 72.11%) compared to DG/D-STATCOM at the same location, which recorded (66.57%, 66.57%, and 65.98%) under the said loading conditions. However, DG/D-STATCOM at the same location offered slightly better voltage profile improvement.}, year = {2023} }
TY - JOUR T1 - Impact Assessment of Optimal Integration of Combined DG and D-STATCOM Allocation for Active Distribution System Enhancement with Loading Variations AU - Musa Mustapha AU - Ganiyu Ayinde Bakare AU - Yau Shuaibu Haruna AU - Babagana Mallambe Mustapha AU - Musa Baba Lawan AU - Abdulkadir Abubakar Sadiq Y1 - 2023/08/04 PY - 2023 N1 - https://doi.org/10.11648/j.epes.20231204.12 DO - 10.11648/j.epes.20231204.12 T2 - American Journal of Electrical Power and Energy Systems JF - American Journal of Electrical Power and Energy Systems JO - American Journal of Electrical Power and Energy Systems SP - 68 EP - 76 PB - Science Publishing Group SN - 2326-9200 UR - https://doi.org/10.11648/j.epes.20231204.12 AB - Renewable Distributed Generation (RDG) is a promising alternative to conventional power generation methods because it reduces power losses and dependence on central power generation. However, when DG is deployed, it doesn’t always provide the reactive power needed for proper voltage regulation leading to low voltage on some buses. To achieve the maximum benefits of a DG unit, a combined DG and D-STATCOM allocation is evaluated. The selection of the optimal capacity and position of these compensators requires appropriate optimization methods to be solved. The real and reactive power loss reduction and voltage profile improvement was selected as objective function and the Artificial Bee Colony (ABC) optimization algorithm was used to solve the optimal allocation problem under variable load conditions. Four case studies, including combined DG / D-STATCOM at the same location (Case III) and combined DG / D-STATCOM at separate locations (case IV), were considered under different load factors of normal, light and peak loading conditions. The performance analysis of these approaches was tested on the standard IEEE 33-bus radial distribution system. The MATLAB 2021b environment was used for the simulations. The outcomes showed that applying optimal DG and D-STACOM at separate locations resulted in a better percentage real power loss reduction of (76.34%, 75.95%, and 75.41%) compared to combined DG/D-STATCOM at the same location, which recorded (72.41%, 71.62% and 71.12%) under normal, light and peak loading conditions. Similarly, optimal DG/DSTATCOM at separate locations recorded better reactive power loss reduction (72.71%, 72.71%, and 72.11%) compared to DG/D-STATCOM at the same location, which recorded (66.57%, 66.57%, and 65.98%) under the said loading conditions. However, DG/D-STATCOM at the same location offered slightly better voltage profile improvement. VL - 12 IS - 4 ER -