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Xu, Y., Zhang, R., Zhao, J., Dong, Z.Y., Wang, D., Yang, H., et al. (2016) Assessing Short-Term Voltage Stability of Electric Power Systems by a Hierarchical Intelligent System. IEEE Transactions on Neural Networks and Learning Systems, 27, 1686-1696.
https://doi.org/10.1109/tnnls.2015.2441706

has been cited by the following article:

• TITLE: Feedback on the Impact of Renewable Energies on the Senelec Network

  AUTHORS: Mohammed Abdoulaye Sall, Fabé Idrissa Barro, Babacar Mbow, Cheikh Sene, Bassirou Ba

  KEYWORDS: Renewable Energy, Installed Capacity, Grid Integration, Frequency Stability, Voltage Stability, Power Quality, Carbon Credit Valuation, Economic Impact

  JOURNAL NAME: Smart Grid and Renewable Energy, Vol.16 No.4, April 30, 2025

  ABSTRACT: Renewable energies are a source of energy with extremely interesting potential and advantages; to be able to take advantage of them, they need to be integrated into the traditional distribution network. This integration is usually achieved via power converters, unfortunately, these converters generate non-linear currents with high levels of harmonics, despite the use of filters. Integrating renewable energies into the electricity grid will lead to disturbances linked to both the quality of the converter’s output and the variability and intermittence of renewable energy sources. This paper explores the feedback from integrating renewable energy into Senegal’s national grid (Senelec) and the broader West African interconnected grid. We analyze the impacts on voltage stability, frequency stability, economic performance, current carbon credit valuation, and the impact of considering the total production output achieved with the total installed capacity of renewable energy power plants, providing practical insights for future leaders in energy policy and grid management.