Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction

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dc.contributor.advisorFolly, Komla
dc.contributor.advisorAwodele, Kehinde
dc.contributor.authorSkunana, Nkululeko Skunana
dc.date.accessioned2026-01-27T11:08:30Z
dc.date.available2026-01-27T11:08:30Z
dc.date.issued2025
dc.date.updated2026-01-27T11:06:07Z
dc.description.abstractThis dissertation investigates the optimal placement of Battery Energy Storage Systems (BESS) in a modified 16-bus Witzenberg radial distribution network incorporating renewable energy sources, particularly photovoltaic (PV) systems. As the distribution networks increasingly integrate intermittent renewable energy sources, the strategic deployment of BESS becomes crucial for maintaining system stability and efficiency. This dissertation aims to investigate the most effective location for BESS placement to minimize total system costs associated with active power losses and voltage profile deviations. The methodology employs a dual-software approach, utilizing MATLAB for optimization algorithms and DigSilent PowerFactory for load flow analyses. Initial assessments establish a baseline scenario without BESS, followed by the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to identify optimal BESS locations. The study conducts comprehensive simulations with BESS at various buses, including algorithm to identify optimal location and other strategic positions within the network. Performance evaluation incorporates a percentage voltage deviation index (PVDI) to quantify improvements in voltage deviations. The research also compares the effectiveness of PSO and GA in minimizing the objective function, providing insights into their applicability for BESS placement optimization. Results demonstrate significant improvements in voltage profiles and reductions in active power losses through strategic BESS placement. Two key results include: • BESS placement at the optimal location (bus 13) led to a substantial reduction in active power losses from 8 MW to 3.3 MW, representing a significant 58.75% decrease. • The overall percentage voltage deviation index (PVDI) was reduced from 11.98% to 5.24% with optimal BESS placement, indicating a 56.26% improvement in voltage stability across the network. These results highlight the potential of BESS in enhancing the performance of distribution networks with high renewable energy penetration. The dissertation results demonstrates that strategic BESS placement can simultaneously address both research aims: reducing active power losses and improving voltage deviations profile.
dc.identifier.apacitationSkunana, N. S. (2025). <i>Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction</i>. (). University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/42699en_ZA
dc.identifier.chicagocitationSkunana, Nkululeko Skunana. <i>"Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction."</i> ., University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2025. http://hdl.handle.net/11427/42699en_ZA
dc.identifier.citationSkunana, N.S. 2025. Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction. . University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. http://hdl.handle.net/11427/42699en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Skunana, Nkululeko Skunana AB - This dissertation investigates the optimal placement of Battery Energy Storage Systems (BESS) in a modified 16-bus Witzenberg radial distribution network incorporating renewable energy sources, particularly photovoltaic (PV) systems. As the distribution networks increasingly integrate intermittent renewable energy sources, the strategic deployment of BESS becomes crucial for maintaining system stability and efficiency. This dissertation aims to investigate the most effective location for BESS placement to minimize total system costs associated with active power losses and voltage profile deviations. The methodology employs a dual-software approach, utilizing MATLAB for optimization algorithms and DigSilent PowerFactory for load flow analyses. Initial assessments establish a baseline scenario without BESS, followed by the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to identify optimal BESS locations. The study conducts comprehensive simulations with BESS at various buses, including algorithm to identify optimal location and other strategic positions within the network. Performance evaluation incorporates a percentage voltage deviation index (PVDI) to quantify improvements in voltage deviations. The research also compares the effectiveness of PSO and GA in minimizing the objective function, providing insights into their applicability for BESS placement optimization. Results demonstrate significant improvements in voltage profiles and reductions in active power losses through strategic BESS placement. Two key results include: • BESS placement at the optimal location (bus 13) led to a substantial reduction in active power losses from 8 MW to 3.3 MW, representing a significant 58.75% decrease. • The overall percentage voltage deviation index (PVDI) was reduced from 11.98% to 5.24% with optimal BESS placement, indicating a 56.26% improvement in voltage stability across the network. These results highlight the potential of BESS in enhancing the performance of distribution networks with high renewable energy penetration. The dissertation results demonstrates that strategic BESS placement can simultaneously address both research aims: reducing active power losses and improving voltage deviations profile. DA - 2025 DB - OpenUCT DP - University of Cape Town KW - Battery Energy Storage Systems KW - Photovoltaic Systems KW - Particle Swarm Optimization (PSO) KW - Genetic (GA) Algorithm KW - Voltage Profile Deviation KW - Power losses LK - https://open.uct.ac.za PB - University of Cape Town PY - 2025 T1 - Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction TI - Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction UR - http://hdl.handle.net/11427/42699 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/42699
dc.identifier.vancouvercitationSkunana NS. Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction. []. University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2025 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/42699en_ZA
dc.language.isoen
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Electrical Engineering
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subjectBattery Energy Storage Systems
dc.subjectPhotovoltaic Systems
dc.subjectParticle Swarm Optimization (PSO)
dc.subjectGenetic (GA) Algorithm
dc.subjectVoltage Profile Deviation
dc.subjectPower losses
dc.titleOptimal placement of battery energy storage system for voltage profile improvement and power loss reduction
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc
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