Available Transfer Capability Determination for the Electricity Market using Cuckoo Search Algorithm


  • T. L. Duong Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Vietnam
  • T. T. Nguyen Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Vietnam
  • N. A. Nguyen Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, Vietnam
  • T. Kang College of Electrical and Information Engineering, Hunan University, China
Volume: 10 | Issue: 1 | Pages: 5340-5345 | February 2020 | https://doi.org/10.48084/etasr.3338


In the electricity market, power producers and customers share a common transmission network for wheeling power from generation to consumption points. All parties in this open access environment may try to produce energy from cheaper sources for greater profit margin, which may lead to transmission congestion, which could lead to violation of voltage and thermal limits, threatening the system security. To solve this, available transfer capability (ATC) must be accurately estimated and optimally utilized. Thus, accurate determination of ATC to ensure system security while serving power transactions is an open and trending research topic. Many optimization approaches to deal with the problem have been proposed. In this paper, Cuckoo Search Algorithm (CSA) is applied for determining ATC problem between the buses in deregulated power systems without violating system constraints such as thermal, voltage constraints. The suggested methodology is tested on IEEE 14 and IEEE 24-bus for normal and contingency cases. The simulation results are compared with the corresponding results of EP, PSO, and GWO and show that the CSA is an effective method for determining ATC.


CSA, ATC, congestion, electricity market


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How to Cite

T. L. Duong, T. T. Nguyen, N. A. Nguyen, and T. Kang, “Available Transfer Capability Determination for the Electricity Market using Cuckoo Search Algorithm”, Eng. Technol. Appl. Sci. Res., vol. 10, no. 1, pp. 5340–5345, Feb. 2020.


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