Volume 21, Issue 1 (March 2025)                   IJEEE 2025, 21(1): 3310-3310 | Back to browse issues page

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Debbarma S, Sarkar D. Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization. IJEEE 2025; 21 (1) :3310-3310
URL: http://ijeee.iust.ac.ir/article-1-3310-en.html
Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization
Sajal Debbarma , Dipu Sarkar
Abstract:   (309 Views)
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.
Keywords: Congestion management, cheetah optimizer, deregulated power system
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Type of Study: Research Paper | Subject: Heuristics and Metaheuristics
Received: 2024/06/01 | Revised: 2025/01/12 | Accepted: 2024/10/30
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.