TY - JOUR
T1 - Investigating the Effectiveness of Wind Turbine and Salp Swarm Optimization in Alleviating Transmission Congestion of Power System
AU - Gautam, Anurag
AU - Nasiruddin, Ibraheem
AU - Sharma, Gulshan
AU - Ahmer, Mohammad F.
AU - Çelik, Emre
AU - Bekiroğlu, Erdal
N1 - Publisher Copyright:
© 2024 Taylor & Francis Group, LLC.
PY - 2024
Y1 - 2024
N2 - The current power system grapples with congestion challenges arising from technological advancements and deregulation. Conversely, renewable energy sources like wind offer an inexhaustible, cost-effective, and environmentally friendly solution, potentially alleviating congestion in the modern transmission network by reducing the need for conventional generators to reschedule. This article conducts a thorough analysis of how the penetration of wind power impacts congestion costs in conventional energy systems. To address this, a novel approach utilizing the bus sensitivity factor is introduced for precise wind turbine placement. To efficiently mitigate congestion costs, a pioneering Salp Swarm Optimization Algorithm is proposed and validated on a modified IEEE 30 Bus system, demonstrating superior performance compared to other algorithms. The findings underscore the effectiveness of the proposed algorithm and highlight wind turbines, coupled with generator rescheduling, as a potent and cost-effective solution for alleviating transmission network congestion.
AB - The current power system grapples with congestion challenges arising from technological advancements and deregulation. Conversely, renewable energy sources like wind offer an inexhaustible, cost-effective, and environmentally friendly solution, potentially alleviating congestion in the modern transmission network by reducing the need for conventional generators to reschedule. This article conducts a thorough analysis of how the penetration of wind power impacts congestion costs in conventional energy systems. To address this, a novel approach utilizing the bus sensitivity factor is introduced for precise wind turbine placement. To efficiently mitigate congestion costs, a pioneering Salp Swarm Optimization Algorithm is proposed and validated on a modified IEEE 30 Bus system, demonstrating superior performance compared to other algorithms. The findings underscore the effectiveness of the proposed algorithm and highlight wind turbines, coupled with generator rescheduling, as a potent and cost-effective solution for alleviating transmission network congestion.
KW - bus sensitivity factor
KW - deregulated power system
KW - generator sensitivity factor
KW - renewable energy source
KW - salp swarm optimization
UR - http://www.scopus.com/inward/record.url?scp=85186211919&partnerID=8YFLogxK
U2 - 10.1080/15325008.2024.2314202
DO - 10.1080/15325008.2024.2314202
M3 - Article
AN - SCOPUS:85186211919
SN - 1532-5008
JO - Electric Power Components and Systems
JF - Electric Power Components and Systems
ER -