Congestion Management using the Circulatory System Based Optimization Algorithm


  • Gia Tue Tang Faculty of Engineering & Technology, Nguyen Tat Thanh University, Vietnam
  • Nguyen Duc Huy Bui Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Vietnam
  • Duong Thanh Long Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Vietnam
Volume: 14 | Issue: 3 | Pages: 14361-14366 | June 2024 |


Congestion management is one of the most important issues in power system operation, especially in competitive electricity markets. The main aim of Congestion Management (CM) is to eliminate congestion in transmission lines. The most common technique to deal with the CM problem is re-dispatching the generator. However, finding an optimal solution for the CM problem constitutes a challenge for many researchers. Recently, a new biologically inspired metaheuristic algorithm, called Circulatory System Based Optimization (CSBO), was developed and proven to be effective in handling optimization issues. The CSBO algorithm was applied to solve the CM problem for the IEEE-30 bus system in two different cases. The former was compared with the Crayfish Optimization Algorithm (COA), Artificial Rabbits Optimization (ARO), Improved Grey Wolf Optimizer (I-GWO), and other existing methods. The simulation results revealed that the cost obtained from the proposed CSBO algorithm was lower than 14.5%, 11.31%, 9.97%, and 4% compared to PSO, FPA, FFA, and ALO. In addition, the stability of the proposed algorithm was higher than that of the other methods after 30 trials.


optimization algorithm, re-dispatching generator, congestion management, circulatory system based optimization, IEEE-30 bus system


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J. R. Chintam and M. Daniel, "Real-Power Rescheduling of Generators for Congestion Management Using a Novel Satin Bowerbird Optimization Algorithm," Energies, vol. 11, no. 1, Jan. 2018, Art. no. 183.

H. Y. Yamina and S. M. Shahidehpour, "Congestion management coordination in the deregulated power market," Electric Power Systems Research, vol. 65, no. 2, pp. 119–127, May 2003.

G. Yesuratnam and D. Thukaram, "Congestion management in open access based on relative electrical distances using voltage stability criteria," Electric Power Systems Research, vol. 77, no. 12, pp. 1608–1618, Oct. 2007.

C. Venkaiah and D. M. Vinod Kumar, "Fuzzy adaptive bacterial foraging congestion management using sensitivity based optimal active power re-scheduling of generators," Applied Soft Computing, vol. 11, no. 8, pp. 4921–4930, Dec. 2011.

K. Pandiarajan and C. K. Babulal, "Transmission Line Management Using Hybrid Differential Evolution with Particle Swarm Optimization.," Journal of Electrical Systems, vol. 10, no. 1, 2014.

N. P. Padhy, "Congestion management under deregulated fuzzy environment," in 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings, Hong Kong, China, Apr. 2004, vol. 1, pp. 133-139 Vol.1.

J. Hazra and A. K. Sinha, "Congestion Management Using Multiobjective Particle Swarm Optimization," IEEE Transactions on Power Systems, vol. 22, no. 4, pp. 1726–1734, Aug. 2007.

S. Balaraman and N. Kamaraj, "Transmission congestion management using particle swarm optimization," Journal of Electrical Systems, vol. 7, no. 1, pp. 54–70, 2011.

S. Verma, S. Saha, and V. Mukherjee, "Optimal rescheduling of real power generation for congestion management using teaching-learning-based optimization algorithm," Journal of Electrical Systems and Information Technology, vol. 5, no. 3, pp. 889–907, Dec. 2018.

S. Deb and A. K. Goswami, "Congestion management by generator rescheduling using Artificial Bee Colony optimization Technique," in 2012 Annual IEEE India Conference (INDICON), Kochi, India, Dec. 2012, pp. 909–914.

S. Gope, A. K. Goswami, and P. K. Tiwari, "Transmission Congestion Management using a Wind Integrated Compressed Air Energy Storage System," Engineering, Technology & Applied Science Research, vol. 7, no. 4, pp. 1746–1752, Aug. 2017.

V. P. Rajderkar and V. K. Chandrakar, "Security Enhancement through the Allocation of a Unified Power Flow Controller (UPFC) in a Power Network for Congestion Management," Engineering, Technology & Applied Science Research, vol. 13, no. 4, pp. 11490–11496, Aug. 2023.

T. L. Duong, T. T. Nguyen, N. A. Nguyen, and T. Kang, "Available Transfer Capability Determination for the Electricity Market using Cuckoo Search Algorithm," Engineering, Technology & Applied Science Research, vol. 10, no. 1, pp. 5340–5345, Feb. 2020.

K. Paul, P. Sinha, Y. Bouteraa, P. Skruch, and S. Mobayen, "A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network," IEEE Access, vol. 11, pp. 10288–10307, 2023.

I. Batra and S. Ghosh, "A Novel Approach of Congestion Management in Deregulated Power System Using an Advanced and Intelligently Trained Twin Extremity Chaotic Map Adaptive Particle Swarm Optimization Algorithm," Arabian Journal for Science and Engineering, vol. 44, no. 8, pp. 6861–6886, Aug. 2019.

S. Verma and V. Mukherjee, "A novel flower pollination algorithm for congestion management in electricity market," in 2016 3rd International Conference on Recent Advances in Information Technology (RAIT), Dhanbad, India, Mar. 2016, pp. 203–208.

S. Verma and V. Mukherjee, "Firefly algorithm for congestion management in deregulated environment," Engineering Science and Technology, an International Journal, vol. 19, no. 3, pp. 1254–1265, Sep. 2016.

S. Verma and V. Mukherjee, "Optimal real power rescheduling of generators for congestion management using a novel ant lion optimiser," IET Generation, Transmission & Distribution, vol. 10, no. 10, pp. 2548–2561, 2016.

S. Verma, S. Saha, and V. Mukherjee, "A novel symbiotic organisms search algorithm for congestion management in deregulated environment," Journal of Experimental & Theoretical Artificial Intelligence, vol. 29, no. 1, pp. 59–79, Jan. 2017.

M. Ghasemi et al., "Circulatory System Based Optimization (CSBO): an expert multilevel biologically inspired meta-heuristic algorithm," Engineering Applications of Computational Fluid Mechanics, vol. 16, no. 1, pp. 1483–1525, Dec. 2022.

H. Jia, H. Rao, C. Wen, and S. Mirjalili, "Crayfish optimization algorithm," Artificial Intelligence Review, vol. 56, no. 2, pp. 1919–1979, Nov. 2023.

L. Wang, Q. Cao, Z. Zhang, S. Mirjalili, and W. Zhao, "Artificial rabbits optimization: A new bio-inspired meta-heuristic algorithm for solving engineering optimization problems," Engineering Applications of Artificial Intelligence, vol. 114, Sep. 2022, Art. no. 105082.

M. H. Nadimi-Shahraki, S. Taghian, and S. Mirjalili, "An improved grey wolf optimizer for solving engineering problems," Expert Systems with Applications, vol. 166, Mar. 2021, Art. no. 113917.

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How to Cite

G. T. Tang, N. D. H. Bui, and D. T. Long, “Congestion Management using the Circulatory System Based Optimization Algorithm”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 3, pp. 14361–14366, Jun. 2024.


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