TY - GEN
T1 - Effectiveness of Wind Energy Penetration in Power System for Mitigating Transmission Congestion
AU - Gautam, Anurag
AU - Sharma, Gulshan
AU - Ahmer, Mohammad F.
AU - Bokoro, Pitshou N.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Modern power systems face congestion challenges due to technology developments and de-regulation. However, non-conventional sources as wind offer a sustainable, affordable, and eco-friendly alternative. By reducing reliance on traditional generators, wind power can ease congestion in transmission networks. Generator rescheduling is an efficient method to tackle congestion but results in cost enhancement. This study examines how wind energy integration affects congestion costs. A new method employing bus sensitivity factors optimizes a 20 MW fixed speed wind turbine placement. Additionally, a pioneering Grey Wolf Optimization Algorithm is applied to minimize congestion costs incurred in generator rescheduling. Method proposed is Tested on an adapted IEEE 30 Bus system, this algorithm outperforms others, emphasizing its efficacy. The research highlights wind turbines, combined with generator rescheduling, as a viable strategy for mitigating transmission congestion economically. As renewable energy continues to evolve, leveraging wind power effectively could lead to a more efficient and sustainable power grid.
AB - Modern power systems face congestion challenges due to technology developments and de-regulation. However, non-conventional sources as wind offer a sustainable, affordable, and eco-friendly alternative. By reducing reliance on traditional generators, wind power can ease congestion in transmission networks. Generator rescheduling is an efficient method to tackle congestion but results in cost enhancement. This study examines how wind energy integration affects congestion costs. A new method employing bus sensitivity factors optimizes a 20 MW fixed speed wind turbine placement. Additionally, a pioneering Grey Wolf Optimization Algorithm is applied to minimize congestion costs incurred in generator rescheduling. Method proposed is Tested on an adapted IEEE 30 Bus system, this algorithm outperforms others, emphasizing its efficacy. The research highlights wind turbines, combined with generator rescheduling, as a viable strategy for mitigating transmission congestion economically. As renewable energy continues to evolve, leveraging wind power effectively could lead to a more efficient and sustainable power grid.
KW - bus sensitivity factor
KW - congestion
KW - Deregulation
KW - generator sensitivity factor
KW - Grey Wolf Optimization algorithm
KW - wind turbine
UR - http://www.scopus.com/inward/record.url?scp=85217873786&partnerID=8YFLogxK
U2 - 10.1109/ICAST61769.2024.10856510
DO - 10.1109/ICAST61769.2024.10856510
M3 - Conference contribution
AN - SCOPUS:85217873786
T3 - IEEE International Conference on Adaptive Science and Technology, ICAST
BT - Proceedings of the 2024 IEEE 9th International Conference on Adaptive Science and Technology, ICAST 2024
PB - IEEE Computer Society
T2 - 9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024
Y2 - 24 October 2024 through 26 October 2024
ER -