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This paper aims to exhibit of optimal location and capacity of energy storage (ES) in electricity development planning, including transmission expansion planning (TEP) and generation expansion planning (GEP). Renewable energy sources are being developed in the world in order to replace the increasingly exhausting and polluting fossil energy sources. However, the energy generation of these types cannot be intentionally controlled but depends on natural conditions. To support the defects that renewable energy causes, energy storage systems have been studied and applied. Developing energy storage to charge cheap energy and provide higher prices in the electricity market is one of the issues that have being attention recently. Although choosing the proper location to place is a great challenge. A number of algorithms have been researched for a long time to find suitable locations for GEP; heuristic algorithms have been used in recent years because of their flexibility and wide range. The heuristic approaches, although being varied over time to become more and more effective search engines, but the problem is withheld into local extremes during searching, the number of too many loops when applied to large network systems... are still being researched and overcome by scientists for heuristic algorithms. On the other hand, the Max-Flow-Min-Cut (MFMC) algorithm has been applied to determine thyristor controlled series compensation (TCSC) to manage congestion that also has been of interest to many researchers but it has some limitations. The MFMC algorithm will be improved more effectively to eliminate congestion collaborate with a heuristic in the paper, and the simulation results tested to determine the position and power of ES on the 24 bus IEEE system showed the algorithm's feasibility.

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Article Details

Issue: Vol 3 No 1 (2020)
Page No.: 339-351
Published: Mar 31, 2020
Section: Research article

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Creative Commons License

Copyright: The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License CC-BY 4.0., which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 How to Cite
Sang, Đinh, Long, D., Anh, T., & Thuận, N. (2020). Determine the location and capacity of energy storage in the power system using the improved Min-Cut algorithm. Science & Technology Development Journal - Engineering and Technology, 3(1), 339-351.

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