TY - GEN
T1 - Optimal Placement of Static Var Compensator using Hybrid Optimization Technique
AU - Muchindu, Titus
AU - Ogudo, K. A.
AU - Bokoro, P. N.
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This paper discusses the effectiveness of hybrid optimization for the placement of Static Var Compensator (SVC) within electricity networks. The ultimate goal is to minimize transmission losses and enhance voltage stability by strategically positioning SVCs. The challenge of identifying the most suitable locations for SVC installation is addressed through a hybrid optimization framework. The practicality of the recommended framework is evaluated using the IEEE 14 and 30 Bus networks under various circumstances of loading. The evaluation involves comparing the performance of the traditional approach, which operates without (SVCs) with the results obtained from applying the hybrid optimization algorithm implemented in MATLAB R2020a. Results show that the hybrid approach demonstrated better system stability by achieving a voltage stability index that was around 2% lower than that of the traditional approach. Additionally, it showed improved energy efficiency by reducing real power losses by roughly 0.5%. Significantly more stable load voltages were ensured by the hybrid technique, which reduced load voltage variance by more than 50%. Its overall goal function decreased by about 0.1%, indicating improved system optimization. Furthermore, the hybrid approach was a more economical alternative because its hourly operating costs were about 0.03% lower. SVCs enhance voltage stability, reducing grid unpredictability and facilitating the integration of renewable energy sources. They contribute to climate objectives, support sustainable transitions, and manage complex, high-capacity networks while ensuring their reliability and resilience.
AB - This paper discusses the effectiveness of hybrid optimization for the placement of Static Var Compensator (SVC) within electricity networks. The ultimate goal is to minimize transmission losses and enhance voltage stability by strategically positioning SVCs. The challenge of identifying the most suitable locations for SVC installation is addressed through a hybrid optimization framework. The practicality of the recommended framework is evaluated using the IEEE 14 and 30 Bus networks under various circumstances of loading. The evaluation involves comparing the performance of the traditional approach, which operates without (SVCs) with the results obtained from applying the hybrid optimization algorithm implemented in MATLAB R2020a. Results show that the hybrid approach demonstrated better system stability by achieving a voltage stability index that was around 2% lower than that of the traditional approach. Additionally, it showed improved energy efficiency by reducing real power losses by roughly 0.5%. Significantly more stable load voltages were ensured by the hybrid technique, which reduced load voltage variance by more than 50%. Its overall goal function decreased by about 0.1%, indicating improved system optimization. Furthermore, the hybrid approach was a more economical alternative because its hourly operating costs were about 0.03% lower. SVCs enhance voltage stability, reducing grid unpredictability and facilitating the integration of renewable energy sources. They contribute to climate objectives, support sustainable transitions, and manage complex, high-capacity networks while ensuring their reliability and resilience.
KW - FACTS Devices
KW - Genetic Search Algorithm (GSA)
KW - Hybrid Optimization Framework
KW - Power Transfer Capability
KW - Static Var Compensators (SVCs)
KW - Swarm Intelligence Optimization (SIO)
KW - Voltage Stability
UR - http://www.scopus.com/inward/record.url?scp=105002690847&partnerID=8YFLogxK
U2 - 10.1109/SAUPEC65723.2025.10944410
DO - 10.1109/SAUPEC65723.2025.10944410
M3 - Conference contribution
AN - SCOPUS:105002690847
T3 - Proceedings of the 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025
BT - Proceedings of the 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Southern African Universities Power Engineering Conference, SAUPEC 2025
Y2 - 29 January 2025 through 30 January 2025
ER -