Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization

Transmission line congestion is more severe and persistent in deregulated power systems than it is in traditionally controlled power systems. In a deregulated power market (DPM) scenario, transmission line congestion is one of the most critical problems. To guarantee the electricity system framework runs consistently and securely, the independent system operator (ISO) controls congestion. Congestion management (CM), which takes into account the inherent uncertainties of the restructured power system, is essential to the functioning and security of DPM. This article demonstrates how to control congestion with generation rescheduling. The system is designed in such a way that it helps the traders to compete and trade using the bid prices. Network security is maintained by keeping all constraints within the allowed limits via the Newton-Raphson load flow. An innovative Cheetah Optimizer is employed to handle the congestion management challenge. The weighted sum approach is used instead of multiobjective optimization to simplify the problem as a single-objective optimization, solve the issue for multiple instances of congestion, and be tested in an IEEE 30 bus system. The MATLAB software serves as a tool for modeling the full process, and the results acquired with the Cheetah optimizer give better results than the conventional optimization technique.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-03-01
Primary Topic
Electric Power System Optimization
Type
article
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article

Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization

SHILAP Revista de lepidopterología
Electric Power System Optimization
article

Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization

article en

Abstract

Transmission line congestion is more severe and persistent in deregulated power systems than it is in traditionally controlled power systems. In a deregulated power market (DPM) scenario, transmission line congestion is one of the most critical problems. To guarantee the electricity system framework runs consistently and securely, the independent system operator (ISO) controls congestion. Congestion management (CM), which takes into account the inherent uncertainties of the restructured power system, is essential to the functioning and security of DPM. This article demonstrates how to control congestion with generation rescheduling. The system is designed in such a way that it helps the traders to compete and trade using the bid prices. Network security is maintained by keeping all constraints within the allowed limits via the Newton-Raphson load flow. An innovative Cheetah Optimizer is employed to handle the congestion management challenge. The weighted sum approach is used instead of multiobjective optimization to simplify the problem as a single-objective optimization, solve the issue for multiple instances of congestion, and be tested in an IEEE 30 bus system. The MATLAB software serves as a tool for modeling the full process, and the results acquired with the Cheetah optimizer give better results than the conventional optimization technique.

SHILAP Revista de lepidopterología
National Institute of Technology Nagaland (IN)
Openalex Percentile: Top 53%
Electric Power System Optimization
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