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Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction
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 r...
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| Format: | Thesis |
| Language: | English English |
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Department of Electrical Engineering
2026
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| _version_ | 1867613270610804736 |
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| access_status_str | Open Access |
| author | Skunana, Nkululeko Skunana |
| author2 | Folly, Komla |
| author_browse | Folly, Komla Skunana, Nkululeko Skunana |
| author_facet | Folly, Komla Skunana, Nkululeko Skunana |
| author_sort | Skunana, Nkululeko Skunana |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/42699 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:33:28.738Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/42699 Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction Skunana, Nkululeko Skunana Folly, Komla Awodele, Kehinde Battery Energy Storage Systems Photovoltaic Systems Particle Swarm Optimization (PSO) Genetic (GA) Algorithm Voltage Profile Deviation Power losses 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. 2026-01-27T11:08:30Z 2026-01-27T11:08:30Z 2025 2026-01-27T11:06:07Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/42699 en eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Battery Energy Storage Systems Photovoltaic Systems Particle Swarm Optimization (PSO) Genetic (GA) Algorithm Voltage Profile Deviation Power losses Skunana, Nkululeko Skunana Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| thesis_degree_str | Master's |
| title | Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| title_full | Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| title_fullStr | Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| title_full_unstemmed | Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| title_short | Optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| title_sort | optimal placement of battery energy storage system for voltage profile improvement and power loss reduction |
| topic | Battery Energy Storage Systems Photovoltaic Systems Particle Swarm Optimization (PSO) Genetic (GA) Algorithm Voltage Profile Deviation Power losses |
| url | http://hdl.handle.net/11427/42699 |
| work_keys_str_mv | AT skunanankululekoskunana optimalplacementofbatteryenergystoragesystemforvoltageprofileimprovementandpowerlossreduction |