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Research Article | Open Access |

Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants

Author 1: Hui Sun
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 14, No. 12 · Published 2023

DOI: https://doi.org/10.14569/IJACSA.2023.0141289

Abstract

The proliferation of renewable energy sources, particularly wind farms, is rapidly gaining momentum owing to their numerous benefits. Consequently, it is imperative to account for the impact of wind farms on transmission expansion planning (TEP), which is a crucial aspect of power system planning. This article presents a multi-objective optimization model that utilizes DC load flow to address the TEP challenge while also incorporating wind farm uncertainties into the model. The present study aims to optimize the expansion and planning of the TEP in the power system by considering investment and maintenance costs as objective functions. To achieve this, a multi-objective approach utilizing the shuffled frog leaping algorithm (SFLA) is proposed and implemented. The proposed objectives are simulated on the RTS-IEEE 24-bus test network. The results obtained from the proposed algorithm are compared with those of the Genetic Algorithm (GA) to assess and validate the proposed approach.

Keywords

How to Cite this Article

Sun, H. (2023). Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants. International Journal of Advanced Computer Science and Applications, 14(12). https://doi.org/10.14569/IJACSA.2023.0141289

Sun, Hui. "Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants." International Journal of Advanced Computer Science and Applications, vol. 14, no. 12, 2023, https://doi.org/10.14569/IJACSA.2023.0141289.

@article{Sun2023,
  title     = {Planning and Expansion of the Transmission Network in the Presence of Wind Power Plants},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {12},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Hui Sun},
  doi       = {10.14569/IJACSA.2023.0141289},
  url       = {https://doi.org/10.14569/IJACSA.2023.0141289}
}

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