Enhancing Distribution Network Efficiency and Symmetry via Optimal Sizing and Location of Photovoltaic DG Using PSO
Keywords:
Distributed generators (DG), Enhancement of voltage profiles, Economic benefits, Reduction of power losses, Particle Swarm Optimization (PSO) algorithm, photovoltaic distributed generators (PVDG).Abstract
With the increasing integration of Distributed Generators (DGs) into distribution networks, their effectiveness in reducing power losses, stabilizing voltage levels, and improving power supply reliability is being widely acknowledged. This paper employs a Particle Swarm Optimization (PSO) algorithm, specifically adapted to handle random constraints, for the optimal sizing and placement of photovoltaic DG (PVDG) units to minimize phase asymmetries within the grid. The proposed approach is designed to enhance system performance by reducing losses, maximizing cost-effectiveness, and supporting voltage symmetry. The model’s performance is validated on an IEEE 33-bus radial distribution network using MATLAB simulations, both with and without PVDG, showing encouraging results. The PSO-based PVDG model outperforms other methods, including the Teaching-Learning Artificial Bee Colony (TLABC) algorithm, by achieving active power loss reductions of 17.60%. Additionally, it reduces reactive power losses by 23.16% compared to TLABC and provides cost savings of 15.21% over TLABC. Significantly, it improves the voltage profile of the distribution system by 3.48%.
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Mohammedi, R.D.; Hellal, A.; Arif, S.; Mosbah, M. Optimal DG Placement and Sizing in Radial Distribution Systems Using NSGA-II for Power Loss Minimization and Voltage Stability Enhancement. Int. Rev. Electr. Eng. 2013, 8, 6.
Barik, S.; Das, D. A novel Q-PQV bus pair method of biomass DGs placement in distribution networks to maintain the voltage of remotely located buses. Energy 2020, 194, 116880.
Wang, Q.; Yao,W.; Fang, J.; Ai, X.;Wen, J.; Yang, X.; Xie, H.; Huang, X. Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers. Appl. Energy 2019, 259, 114132.
Layadi, T.M.; Champenois, G.; Mostefai, M. Economic and ecological optimization of multi-source systems under the variability in the cost of fuel. Energy Convers. Manag. 2018, 177, 161–175.
Vita, V. Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks. Energies 2017, 10, 1433.
Duong, M.Q.; Pham, T.D.; Nguyen, T.T.; Doan, A.T.; Van Tran, H. Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems. Energies 2019, 12, 174.
Remha, S.; Chettih, S.; Arif, S. Optimal DG location and sizing for minimum active power loss in radial distribution system using firefly algorithm. Int. J. Energetica 2017, 4, 6–10.
Matlokotsi, T.; Chowdhury, S. Optimal Placement and Sizing of Renewable Distributed Generation in Electricity Networks Considering Different Load Models. IEEE Conf. 2017, 1, 1–6.
Prakash, D.; Lakshminarayana, C. Multiple DG placements in radial distribution system for multi objectives using Whale Optimization Algorithm. Alex. Eng. J. 2018, 57, 2797–2806.
Kumar, M.; Nallagownden, P.; Elamvazuthi, I. Optimal Placement and Sizing of Renewable Distributed Generations and Capacitor Banks into Radial Distribution Systems. Energies 2017, 10, 811.
Shaheen, A.M.; Elsayed, A.M.; Ginidi, A.R.; El-Sehiemy, R.A.; Elattar, E. A heap-based algorithm with deeper exploitative feature for optimal allocations of distributed generations with feeder reconfiguration in power distribution networks. Knowl. -Based Syst. 2022, 241, 108269.
Jamil Mahfoud, R.; Sun, Y.; Faisal Alkayem, N.; Haes Alhelou, H.; Siano, P.; Shafie-Khah, M. A Novel Combined Evolutionary Algorithm for Optimal Planning of Distributed Generators in Radial Distribution Systems section. Appl. Sci. 2019, 9, 3394.
Tamoor, M.; Bhatti, A.R.; Farhan, M.; Zaka, M.A.; ZakaUllah, P. Solar Energy Capacity Assessment and Performance Evaluation of Designed Grid-Connected Photovoltaic Systems. Appl. Sci. 2023, 37, 39.
Urinboy, J.; Hasanov, M. Improvement Performance of Radial Distribution System by Optimal Placement of Photovoltaic Array. Int. J. Eng. Inf. Syst. 2021, 5, 157–159.
Janamala, V. A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system inmulti-lateral distribution system for improving resilience. SN Appl. Sci. 2021, 3, 118.
Ali, E.S.; Abd Elazim, S.M.; Abdelaziz, A.Y. Ant Lion optimization algorithm for optimal location and sizing of renewable distrib-uted generations. Renew Energy 2017, 101, 1311–1324.
Eberhart, R.; Kennedy, J. A new optimizer using particle swarm theory. In Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, 4–6 October 1995; pp. 39–43.
Bohre, A.K.; Agnihotri, G.; Dubey, M. Hybrid butterfly-based particle swarm optimization for optimization problems. In Proceedings of the First International Conference on Networks and Soft Computing (ICNSC), Guntur, India, 19–20 August 2014; pp. 172–177.
Zeinalzadeh, A.; Mohammadi, Y.; Moradi, M.H. Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks simultaneously considering load uncertainty via MOPSO approach. Int. J. Electr. Power Energy Syst. 2015, 67,336–349.
Haque, M. Efficient load flow method for distribution systems with radial or mesh configuration. IEE Proc. Gener. Transm. Distrib.1996, 143, 33–38.
Salkuti, S.R.; Battu, N.R. An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement. Bull. Electr. Eng. Informatics 2021, 10, 1819–1827.
Eberhart, R.C.; Shi, Y. Comparing inertial weights and constriction factor in particle swarm optimization. In Proceedings of the International Congress on Evaluating Computation, La Jolla, CA, USA, 16–19 July 2000; pp. 84–89.
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