Optimal Positioning and Sizing of Distributed Energy Sources in Distribution System Using Hunter-Prey Optimizer Algorithm
Abstract The integration of distributed generation (DG) based on renewable energy (RE), in distribution power networks (DPN) has become indispensable for reducing power losses and voltage deviation along the DPN. Typical DGs are placed adjacent to the load in DPN and locally distribute adequate active and reactive power. However, the appropriate placement of DG in DPN at the right location and size is essential to achieve the desired objectives. In this paper, DG is optimized into radial DPN with the aid of a recent bio-inspired hunter-prey optimization (HPO) algorithm. HPO is a bio-inspired and population-based optimization algorithm that mimics the hunting action of an animal. The HPO algorithm evades the local optimal stagnation and reaches the optimal solution rapidly. HPO optimizes solar photovoltaic (PV) and wind turbine (WT) DG systems to minimize multi-objective functions (MOFs) including active power loss (APL) and voltage deviation (VD), and to enhance voltage stability (VS). An optimized solution has been obtained for a standard IEEE 69-bus radial DPN and the optimized simulation result of HPO has been compared with other optimization algorithms with the aim of assessing its effectiveness. The optimized PV and WT DG integration via the proposed HPO algorithm has yielded a power loss reduction of 67.10 % and 90.4 %, respectively. Furthermore, a considerable enhancement in bus voltage and voltage stability has been seen in radial DPN after the inclusion of DG.
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Abdel-Mawgoud, H., Kamel, S., Yu, J., & Jurado, F. (2022). Hybrid Salp Swarm Algorithm for integrating renewable distributed energy resources in distribution systems considering annual load growth. Journal of King Saud University-Computer and Information Sciences, 34(1), 1381-1393. DOI: 10.1016/j.jksuci.2019.08.011.
Abdul Kadir, A. F., Khatib, T., Lii, L. S., & Hassan, E. E. (2019). Optimal placement and sizing of photovoltaic based distributed generation considering costs of operation planning of monocrystalline and thin-film technologies. Journal of Solar Energy Engineering, 141(1), 011017. DOI: 10.1115/1.4041105.
Abou El-Ela, A. A., El-Sehiemy, R. A., & Abbas, A. S. (2018). Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm. IEEE Systems Journal, 12(4), 3629-3636. DOI: 10.1109/JSYST.2018.2796847.
Abu-Mouti, F. S., & El-Hawary, M. E. (2011). Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Transactions on Power Delivery, 26(4), 2090-2101. DOI: 10.1109/TPWRD.2011.2158246.
Ali, M. H., Mehanna, M., & Othman, E. (2020a). Optimal network reconfiguration incorporating with renewable energy sources in radial distribution networks. International Journal of Advanced Science and Technology, 29, 3114-3133.
Ali, M. H., Mehanna, M., & Othman, E. (2020b). Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6153-6163. DOI: 10.11591/ijece.v10i6.pp6153-6163.
Dash, S. K., Mishra, S., Pati, L. R., & Satpathy, P. K. (2021). Optimal Allocation of Distributed Generators Using Metaheuristic Algorithms - An Up to Date Bibliographic Review. Green Technology for Smart City and Society: Proceedings of GTSCS 2020, 553-561. DOI: 10.1007/978-981-15-8218-9_45.
Dinakara Prasasd Reddy, P., Veera Reddy, V.C., Gowri Manohar, T. A. (2018). Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems. Journal of Electrical Systems and Information Technology, 5(3), 663-680. DOI: 10.1016/j.jesit.2017.06.001.
Essallah, S., Khedher, A., & Bouallegue, A. (2019). Integration of distributed generation in electrical grid: Optimal placement and sizing under different load conditions. Computers & Electrical Engineering, 79, 106461. DOI: 10.1016/j.compeleceng.2019.106461.
Gandomkar, M., Vakilian, M., & Ehsan, M. J. E. P. C. (2005). A genetic–based tabu search algorithm for optimal DG allocation in distribution networks. Electric Power Components and Systems, 33(12), 1351-1362. DOI: 10.1080/15325000590964254.
Ho, Y. C., & Pepyne, D. L. (2002). Simple explanation of the no free lunch theorem of optimization. Cybernetics and Systems Analysis, 38, 292-298. DOI: 10.1023/A:1016355715164.
Injeti, S. K. (2018). A Pareto optimal approach for allocation of distributed generators in radial distribution systems using improved differential search algorithm. Journal of Electrical Systems and Information Technology, 5(3), 908-927. DOI: 10.1016/j.jesit.2016.12.006.
Kamel, S., Awad, A., Abdel-Mawgoud, H., & Jurado, F. (2019). Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer. Turkish Journal of Electrical Engineering and Computer Sciences, 27(4), 2947-2961. DOI: 10.3906/elk-1805-66.
Kansal, S., Kumar, V., & Tyagi, B. (2016). Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems, 75, 226-235. DOI: 10.1016/j.ijepes.2015.09.002.
Kayal, P., & Chanda, C. K. (2013). Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, 795-809. DOI: 10.1016/j.ijepes.2013.05.047.
Khasanov, M., Kamel, S., & Abdel-Mawgoud, H. (2019). Minimizing power loss and improving voltage stability in distribution system through optimal allocation of distributed generation using electrostatic discharge algorithm. In 2019 21st International Middle East Power Systems Conference (MEPCON) (pp. 354-359). IEEE. DOI: 10.1109/MEPCON47431.2019.9007943.
Khasanov, M., Kamel, S., Rahmann, C., Hasanien, H. M., & Al‐Durra, A. (2021). Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Generation, Transmission & Distribution, 15(24), 3400-3422. DOI: 10.1049/gtd2.12230.
Kowsalya, M. (2014). Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization. Swarm and Evolutionary Computation, 15, 58-65. DOI: 10.1016/j.swevo.2013.12.001.
Kumar, S., Mandal, K. K., & Chakraborty, N. (2019). Optimal DG placement by multi-objective opposition based chaotic differential evolution for techno-economic analysis. Applied Soft Computing, 78, 70-83. DOI: 10.1016/j.asoc.2019.02.013.
Naruei, I., Keynia, F., & Sabbagh Molahosseini, A. (2022). Hunter–prey optimization: Algorithm and applications. Soft Computing, 26(3), 1279-1314. DOI: 10.1007/s00500-021-06401-0.
Nowdeh, S. A., Davoudkhani, I. F., Moghaddam, M. H., Najmi, E. S., Abdelaziz, A. Y., Ahmadi, A., & Gandoman, F. H. (2019). Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Applied Soft Computing, 77, 761-779. DOI: 10.1016/j.asoc.2019.02.003.
Oree, V., Hassen, S. Z. S., & Fleming, P. J. (2017). Generation expansion planning optimisation with renewable energy integration: A review. Renewable and Sustainable Energy Reviews, 69, 790-803. DOI: 10.1016/j.rser.2016.11.120.
Palanisamy, R., & Muthusamy, S. K. (2021). Optimal siting and sizing of multiple distributed generation units in radial distribution system using ant lion optimization algorithm. Journal of Electrical Engineering & Technology, 16, 79-89. DOI: 10.1007/s42835-020-00569-5.
Sa’ed, J. A., Amer, M., Bodair, A., Baransi, A., Favuzza, S., & Zizzo, G. (2019). A simplified analytical approach for optimal planning of distributed generation in electrical distribution networks. Applied Sciences, 9(24), 5446. DOI: 10.3390/app9245446.
Saha, S., & Mukherjee, V. (2021). A novel multi-objective modified symbiotic organisms search algorithm for optimal allocation of distributed generation in radial distribution system. Neural Computing and Applications, 33, 1751-1771. DOI: 10.1007/s00521-020-05080-6.
Samala, R. K., & Kotapuri, M. R. (2020). Optimal allocation of distributed generations using hybrid technique with fuzzy logic controller radial distribution system. SN Applied Sciences, 2(2), 191. DOI: 10.1007/s42452-020-1957-3.
Subbaramaiah, K., & Sujatha, P. (2023). Optimal DG unit placement in distribution networks by multi-objective whale optimization algorithm & its techno-economic analysis. Electric Power Systems Research, 214, 108869. DOI: 10.1016/j.epsr.2022.108869.
Suresh, M. C. V., & Edward, J. B. (2020). A hybrid algorithm based optimal placement of DG units for loss reduction in the distribution system. Applied Soft Computing, 91, 106191. DOI: 10.1016/j.asoc.2020.106191.
Truong, K. H., Nallagownden, P., Elamvazuthi, I., & Vo, D. N. (2020). A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for optimal allocation of DG in radial distribution networks. Applied Soft Computing, 88, 106067. DOI: 10.1016/j.asoc.2020.106067.
Abdul Kadir, A. F., Khatib, T., Lii, L. S., & Hassan, E. E. (2019). Optimal placement and sizing of photovoltaic based distributed generation considering costs of operation planning of monocrystalline and thin-film technologies. Journal of Solar Energy Engineering, 141(1), 011017. DOI: 10.1115/1.4041105.
Abou El-Ela, A. A., El-Sehiemy, R. A., & Abbas, A. S. (2018). Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm. IEEE Systems Journal, 12(4), 3629-3636. DOI: 10.1109/JSYST.2018.2796847.
Abu-Mouti, F. S., & El-Hawary, M. E. (2011). Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Transactions on Power Delivery, 26(4), 2090-2101. DOI: 10.1109/TPWRD.2011.2158246.
Ali, M. H., Mehanna, M., & Othman, E. (2020a). Optimal network reconfiguration incorporating with renewable energy sources in radial distribution networks. International Journal of Advanced Science and Technology, 29, 3114-3133.
Ali, M. H., Mehanna, M., & Othman, E. (2020b). Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6153-6163. DOI: 10.11591/ijece.v10i6.pp6153-6163.
Dash, S. K., Mishra, S., Pati, L. R., & Satpathy, P. K. (2021). Optimal Allocation of Distributed Generators Using Metaheuristic Algorithms - An Up to Date Bibliographic Review. Green Technology for Smart City and Society: Proceedings of GTSCS 2020, 553-561. DOI: 10.1007/978-981-15-8218-9_45.
Dinakara Prasasd Reddy, P., Veera Reddy, V.C., Gowri Manohar, T. A. (2018). Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems. Journal of Electrical Systems and Information Technology, 5(3), 663-680. DOI: 10.1016/j.jesit.2017.06.001.
Essallah, S., Khedher, A., & Bouallegue, A. (2019). Integration of distributed generation in electrical grid: Optimal placement and sizing under different load conditions. Computers & Electrical Engineering, 79, 106461. DOI: 10.1016/j.compeleceng.2019.106461.
Gandomkar, M., Vakilian, M., & Ehsan, M. J. E. P. C. (2005). A genetic–based tabu search algorithm for optimal DG allocation in distribution networks. Electric Power Components and Systems, 33(12), 1351-1362. DOI: 10.1080/15325000590964254.
Ho, Y. C., & Pepyne, D. L. (2002). Simple explanation of the no free lunch theorem of optimization. Cybernetics and Systems Analysis, 38, 292-298. DOI: 10.1023/A:1016355715164.
Injeti, S. K. (2018). A Pareto optimal approach for allocation of distributed generators in radial distribution systems using improved differential search algorithm. Journal of Electrical Systems and Information Technology, 5(3), 908-927. DOI: 10.1016/j.jesit.2016.12.006.
Kamel, S., Awad, A., Abdel-Mawgoud, H., & Jurado, F. (2019). Optimal DG allocation for enhancing voltage stability and minimizing power loss using hybrid gray wolf optimizer. Turkish Journal of Electrical Engineering and Computer Sciences, 27(4), 2947-2961. DOI: 10.3906/elk-1805-66.
Kansal, S., Kumar, V., & Tyagi, B. (2016). Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems, 75, 226-235. DOI: 10.1016/j.ijepes.2015.09.002.
Kayal, P., & Chanda, C. K. (2013). Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. International Journal of Electrical Power & Energy Systems, 53, 795-809. DOI: 10.1016/j.ijepes.2013.05.047.
Khasanov, M., Kamel, S., & Abdel-Mawgoud, H. (2019). Minimizing power loss and improving voltage stability in distribution system through optimal allocation of distributed generation using electrostatic discharge algorithm. In 2019 21st International Middle East Power Systems Conference (MEPCON) (pp. 354-359). IEEE. DOI: 10.1109/MEPCON47431.2019.9007943.
Khasanov, M., Kamel, S., Rahmann, C., Hasanien, H. M., & Al‐Durra, A. (2021). Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Generation, Transmission & Distribution, 15(24), 3400-3422. DOI: 10.1049/gtd2.12230.
Kowsalya, M. (2014). Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization. Swarm and Evolutionary Computation, 15, 58-65. DOI: 10.1016/j.swevo.2013.12.001.
Kumar, S., Mandal, K. K., & Chakraborty, N. (2019). Optimal DG placement by multi-objective opposition based chaotic differential evolution for techno-economic analysis. Applied Soft Computing, 78, 70-83. DOI: 10.1016/j.asoc.2019.02.013.
Naruei, I., Keynia, F., & Sabbagh Molahosseini, A. (2022). Hunter–prey optimization: Algorithm and applications. Soft Computing, 26(3), 1279-1314. DOI: 10.1007/s00500-021-06401-0.
Nowdeh, S. A., Davoudkhani, I. F., Moghaddam, M. H., Najmi, E. S., Abdelaziz, A. Y., Ahmadi, A., & Gandoman, F. H. (2019). Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Applied Soft Computing, 77, 761-779. DOI: 10.1016/j.asoc.2019.02.003.
Oree, V., Hassen, S. Z. S., & Fleming, P. J. (2017). Generation expansion planning optimisation with renewable energy integration: A review. Renewable and Sustainable Energy Reviews, 69, 790-803. DOI: 10.1016/j.rser.2016.11.120.
Palanisamy, R., & Muthusamy, S. K. (2021). Optimal siting and sizing of multiple distributed generation units in radial distribution system using ant lion optimization algorithm. Journal of Electrical Engineering & Technology, 16, 79-89. DOI: 10.1007/s42835-020-00569-5.
Sa’ed, J. A., Amer, M., Bodair, A., Baransi, A., Favuzza, S., & Zizzo, G. (2019). A simplified analytical approach for optimal planning of distributed generation in electrical distribution networks. Applied Sciences, 9(24), 5446. DOI: 10.3390/app9245446.
Saha, S., & Mukherjee, V. (2021). A novel multi-objective modified symbiotic organisms search algorithm for optimal allocation of distributed generation in radial distribution system. Neural Computing and Applications, 33, 1751-1771. DOI: 10.1007/s00521-020-05080-6.
Samala, R. K., & Kotapuri, M. R. (2020). Optimal allocation of distributed generations using hybrid technique with fuzzy logic controller radial distribution system. SN Applied Sciences, 2(2), 191. DOI: 10.1007/s42452-020-1957-3.
Subbaramaiah, K., & Sujatha, P. (2023). Optimal DG unit placement in distribution networks by multi-objective whale optimization algorithm & its techno-economic analysis. Electric Power Systems Research, 214, 108869. DOI: 10.1016/j.epsr.2022.108869.
Suresh, M. C. V., & Edward, J. B. (2020). A hybrid algorithm based optimal placement of DG units for loss reduction in the distribution system. Applied Soft Computing, 91, 106191. DOI: 10.1016/j.asoc.2020.106191.
Truong, K. H., Nallagownden, P., Elamvazuthi, I., & Vo, D. N. (2020). A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for optimal allocation of DG in radial distribution networks. Applied Soft Computing, 88, 106067. DOI: 10.1016/j.asoc.2020.106067.
Rajakumar, P., Senthil Kumar, M., Karunanithi, K., Prakash, S. V. J., Baburao, P., & Raja, S. P. (2024). Optimal Positioning and Sizing of Distributed Energy Sources in Distribution System Using Hunter-Prey Optimizer Algorithm. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 13(1), e31639. https://doi.org/10.14201/adcaij.31639
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