DG, SOP, and EVCS deployment in a distribution system: Multi-Scenario analysis using HHO and TLBO

Abstract

The rapid integration of distributed energy resources and power-electronic-interfaced loads requires sophisticated planning techniques for modern radial distribution systems (RDS). In this paper, we propose a comprehensive multi-objective optimization framework for the coordinated placement and size of electric vehicle charging stations (EVCS), distributed generations (DGs), and soft open points (SOPs) in RDS. The developed objective function concurrently minimizes loss, improves the voltage profile, enhances the power factor, reduces harmonic distortion, and maximizes the utilization of substation capacity, subject to operational and technical constraints. Teaching Learning Based Optimization (TLBO) and Harris Hawks Optimization (HHO) were used and compared to evaluate solution resilience and convergence efficiency. The outcomes showed that system coordination consistently improved network efficiency, voltage stability, feeder balance, and power quality. Coordinated multi-device integration delivered better technical performance and ensured steady operation within regulatory voltage and harmonic limits. The robustness and dependability of the suggested optimization framework were validated through statistical analysis, which showed that HHO outperformed TLBO in terms of convergence behavior and solution quality. In addition to improving technical performance, the suggested framework supports the development of sustainable power systems by encouraging the integration of renewable energy sources, grid modernization, and the adoption of electrified transportation. The study supports SDGs 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure), 11 (Sustainable Cities and Communities), and 13 (Climate Action). Overall, the suggested coordinated optimization approach offers a scalable and long-lasting solution for active distribution networks prepared for the future.

Keywords

distributed generation / soft open point / electric vehicle charging station / vehicle-to-grid / multi-objective optimization / Harris Hawks Optimization / Teaching Learning Based Optimization

References

[1] Selim A, Kamel S, Alghamdi AS, et al. (2020) Optimal placement of DGs in distribution system using an improved Harris Hawks Optimizer based on single-and multi-objective approaches. IEEE Access 8: 52815-52829. https://doi.org/10.1109/ACCESS.2020.2980245

[2] Akdag O, Ates A, Yeroglu C (2021) Modification of Harris Hawks optimization algorithm with random distribution functions for optimum power flow problem. Neural Comput Appl 33: 1959-1985. https://doi.org/10.1007/s00521-020-05073-5

[3] Alabool HM, Alarabiat D, Abualigah L, et al. (2021) Harris Hawks optimization: A comprehensive review of recent variants and applications. Neural Comput Appl 33: 8939-8980. https://doi.org/10.1007/s00521-021-05720-5

[4] Bhatt PK (2022) Harmonics mitigated multi-objective energy optimization in PV integrated rural distribution network using modified TLBO algorithm. Renewable Energy Focus 40: 13-22. https://doi.org/10.1016/j.ref.2021.11.001

[5] Kc B, Alkhwaildi H (2021) Multi-objective TLBO and GWO-based optimization for placement of renewable energy resources in distribution system. Comput Res Prog Appl Sci Eng 7: 1-13. https://doi.org/10.52547/crpase.7.2.2356

[6] Cong Y, Yang B, Wei J (2025) A novel meta-heuristic algorithm based on candidate cooperation and competition. Sci Rep 15: 24971. https://doi.org/10.1038/s41598-025-08894-3

[7] Khan MH, Ulasyar A, Khattak A, et al. (2022) Optimal sizing and allocation of distributed generation in the radial power distribution system using honey badger algorithm. Energies 15: 5891. https://doi.org/10.3390/en15165891

[8] Babu PVK, Swarnasri K (2020) Optimal integration of different types of DGs in radial distribution system by using Harris Hawk optimization algorithm. Cogent Eng 7: 1823156. https://doi.org/10.1080/23311916.2020.1823156

[9] M'hamdi B, Teguar M, Tahar B (2020) Optimal DG unit placement and sizing in radial distribution network for power loss minimization and voltage stability enhancement. Period polytech Electr Eng Comput Sci 64: 157-169. https://doi.org/10.3311/PPee.15057

[10] Murty VV, Kumar A (2015) Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth. Int J Electr Power Energy Syst 69: 246-256. https://doi.org/10.1016/j.ijepes.2014.12.080

[11] Patel H, Bohre AK, Yadav O (2025) Enhancing distribution system performnce with concurrent planning of DG and soft open point. 2025 IEEE North-East India International Energy Conversion Conference and Exhibition (NE-IECCE), IEEE, 1-6. https://doi.org/10.1109/NE-IECCE64154.2025.11183424

[12] Adegoke SA, Sun Y, Adegoke AS, et al. (2024) Optimal placement of distributed generation to minimize power loss and improve voltage stability. Heliyon, 10. https://doi.org/10.1016/j.heliyon.2024.e39298

[13] Qian J, Wei M, Wang P, et al. (2025) Optimal distributed generation allocation in radial distribution networks using a modified seagull optimization algorithm with elite reserve strategy. Energy Convers Manage: X 28: 101228. https://doi.org/10.1016/j.ecmx.2025.101228

[14] Patel H, Saw BK, Bohre AK. et al. (2023) Analyze the impact of distributed generation units on distribution system performances. System 1: 5. https://doi.org/10.1109/PESGRE58662.2023.10404345

[15] Das RK, Patel H, Bohre AK (2025) Optimal allocation of DG to enhance system reliability, resiliency and power quality using optimization. 2025 IEEE North-East India International Energy Conversion Conference and Exhibition (NE-IECCE), IEEE, 1-6. https://doi.org/10.1109/NE-IECCE64154.2025.11182889

[16] Sa’ed JA, Amer M, Bodair A, et al. (2019) A simplified analytical approach for optimal planning of distributed generation in electrical distribution networks. Appl Sci 9: 5446. https://doi.org/10.3390/app9245446

[17] Singh B, Sharma J (2017) A review on distributed generation planning. Renewable Sustainable Energy Rev 76: 529-544. https://doi.org/10.1016/j.rser.2017.03.034

[18] Bohre AK, Agnihotri G, Dubey M (2016) Optimal sizing and sitting of DG with load models using soft computing techniques in practical distribution system. IET Gener, Transm Distrib 10: 2606-2621. https://doi.org/10.1049/iet-gtd.2015.1034

[19] Malika BK, Pattanaik V, Panda S, et al. (2025) A critical review of distribution system planning: Optimal placement and sizing of distributed generation and energy storage devices in microgrids. Energy Strategy Rev 62: 101947. https://doi.org/10.1016/j.esr.2025.101947

[20] Suvarchala K, Yuvaraj T, Balamurugan P (2018) A brief review on optimal allocation of Distributed Generation in distribution network. 2018 4th International Conference on Electrical Energy Systems (ICEES) , IEEE, 391-396. https://doi.org/10.1109/ICEES.2018.8443294

[21] Cong P, Hu Z, Tang W, et al. (2020) Optimal allocation of soft open points in an active distribution network with high penetration of renewable energy generation. IET Gener, Transm Distrib 14: 6732-6740. https://doi.org/10.1049/iet-gtd.2020.0704

[22] Wang J, Zhou N, Tao A, et al. (2021) Optimal operation of soft-open-point-based energy storage in active distribution networks considering battery lifetime. Front Energy Res 8: 633401. https://doi.org/10.3389/fenrg.2020.633401

[23] Jiang X, Zhou Y, Ming W, et al. (2022) An overview of soft open points in electricity distribution networks. IEEE Trans Smart Grid 13: 1899-1910. https://doi.org/10.1109/TSG.2022.3148599

[24] Fuad KS, Hafezi H, Kauhaniemi K, et al. (2020) Soft open point in distribution networks. IEEE Access 8: 210550-210565. https://doi.org/10.1109/ACCESS.2020.3039552

[25] Ma Z, Cao F (2024) Optimization of active distribution network operation with SOP considering reverse power flow. Appl Sci 14: 11797. https://doi.org/10.3390/app142411797

[26] Behbahani MR, Jalilian A (2024) Optimal operation of soft open point devices and distribution network reconfiguration in a harmonically polluted distribution network. Electr Power Syst Res 237: 110967. https://doi.org/10.1016/j.epsr.2024.110967

[27] Elazab R, Salama S, Abo-Adma M, et al. (2026) Soft open point integration in active distribution networks and microgrids for sustainable grid planning. Electr Power Syst Res 252: 112362. https://doi.org/10.1016/j.epsr.2025.112362

[28] Fang Jie, Wenwu Li, Chen D (2025) Electric vehicle and soft open points co-planning for active distribution grid flexibility enhancement. Energies 18: 694. https://doi.org/10.3390/en18030694

[29] Razavi SM, Sebtahmadi SS, Momeni HR, et al. (2025) A self-adaptive modified backward forward sweep method: Application to dynamic flow direction changes. Int J Electr Power Energy Syst 166: 110567. https://doi.org/10.1016/j.ijepes.2025.110567

[30] Goli P, Gampa SR, Kumar NM, et al. (2023) Strategic planning of the distribution network integrated with EV charging stations using fuzzy Pareto optimality for performance improvement and grid-side emission reduction benefits. Sustainable Energy, Grids Networks 36: 101199. https://doi.org/10.1016/j.segan.2023.101199

[31] Rene EA, Fokui WST, Kouonchie PKN (2023) Optimal allocation of plug-in electric vehicle charging stations in the distribution network with distributed generation. Green Energy Intell Transp 2: 100094. https://doi.org/10.1016/j.geits.2023.100094

[32] Seilabi SE, Pourgholamali M, Miralinaghi M, et al. (2025) Sustainable planning of electric vehicle charging stations: A bi-level optimization framework for reducing vehicular emissions in urban road networks. Sustainability 17: 1. https://doi.org/10.3390/su17010001

[33] Ji J, Chen H, Zhang J, et al. (2025) Planning method for electric vehicle charging stations considering dynamic traffic load demand prediction. Energy Internet 2: 241-254. https://doi.org/10.1049/ein2.70005

[34] Danese A, Torsæter BN, Sumper A, et al. (2022). Planning of high-power charging stations for electric vehicles: A review. Appl Sci 12: 3214. https://doi.org/10.3390/app12073214

[35] Pal A, Bhattacharya A, Chakraborty AK (2023) Planning of EV charging station with distribution network expansion considering traffic congestion and uncertainties. IEEE Trans Ind Appl 59: 3810-3825. https://doi.org/10.1109/TIA.2023.3237650

[36] Wang J, Kaushik HD, Zhang J (2024) Optimal planning of electric vehicle charging stations: Integrating public charging networks and transportation congestion. 2024 IEEE Kansas Power and Energy Conference (KPEC), IEEE, 1-6. https://doi.org/10.1109/KPEC61529.2024.10676118

[37] Saw BK, Bohre AK (2025) Sustainable deployment of EV charging stations in distribution network supported with hybrid solar-DG integrated DSTACOM. IEEE Trans Ind Appl 61: 7750-7765. https://doi.org/10.1109/TIA.2025.3550143

[38] Tripathy S, Nandi S, Ghatak SR, et al. (2025) Concurrent planning of ultra-fast EV charging infrastructure, intermittent PV, and DSTATCOM in a reconfigured three-phase unbalanced distribution system. Int J Ambient Energy 46: 2596226. https://doi.org/10.1080/01430750.2025.2596226

[39] Ran Y, Liao H, Liang H, et al. (2024) Optimal scheduling strategies for EV charging and discharging in a coupled power-transportation network with V2G scheduling and dynamic pricing. Energies 17: 6167. https://doi.org/10.3390/en17236167

[40] Saw BK, Bohre AK (2025) Solar integrated DSTATCOM-based charging stations planning for EVs addressing sustainable development goals: Techno-economic and environmental. IEEE Trans Ind Appl 62: 2161-2171. https://doi.org/10.1109/TIA.2025.3604759

[41] Shaheen HI, Rashed GI, Yang B, et al. (2024) Optimal electric vehicle charging and discharging scheduling using metaheuristic algorithms: V2G approach for cost reduction and grid support. J Energy Storage 90: 111816. https://doi.org/10.1016/j.est.2024.111816

[42] Sortomme E, El-Sharkawi MA (2010) Optimal charging strategies for unidirectional vehicle-to-grid. IEEE Trans Smart Grid 2: 131-138. https://doi.org/10.1109/TSG.2010.2090910

[43] Habib S, Kamran M, Rashid U (2015) Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks-A review. J Power Sources 277: 205-214. https://doi.org/10.1016/j.jpowsour.2014.12.020

[44] Liang Z, Chung CY, Wang Q, et al. (2025) Fortifying renewable-dominant hybrid microgrids: A bi-directional converter-based interconnection planning approach. 51: 130-143. Engineering https://doi.org/10.1016/j.eng.2025.02.020

[45] Liang Z, Chung CY, Zhang W, et al. (2024) Enabling high-efficiency economic dispatch of hybrid AC/DC networked microgrids: Steady-state convex bi-directional converter models. IEEE Trans Smart Grid 16: 45-61. https://doi.org/10.1109/TSG.2024.3454050

[46] Baran ME, Wu FF (1989) Optimal capacitor placement on radial distribution systems. IEEE Trans Power Delivery 4: 725-734. https://doi.org/10.1109/61.19265

[47] Acharya N, Mahat P, Mithulananthan N (2006) An analytical approach for DG allocation in primary distribution network. Int J Electr Power Energy Syst 28: 669-678. https://doi.org/10.1016/j.ijepes.2006.02.013

[48] Zhang J, Foley A, Wang S (2021) Optimal planning of a soft open point in a distribution network subject to typhoons. Int J Electr Power Energy Syst 129: 106839. https://doi.org/10.1016/j.ijepes.2021.106839

[49] Patel H, Saw BK, Bohre AK, et al. (2023) Harmonics and reliability analysis of distribution network in presence of Multi-DG using PSO and DigSILENT. 2023 IEEE 3rd International Conference on Smart Technologies for Power, Energy and Control (STPEC) , IEEE, 1-6. https://doi.org/10.1109/STPEC59253.2023.10431093