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Bidirectional Control of Electric Vehicles Based on Artificial Neural Network Considering Owners Convenience and Microgrid Stability


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DOI: https://doi.org/10.15866/ireaco.v13i6.19841

Abstract


The contribution of the renewable energy has been increasing rapidly. Renewable resources are intermittent in their nature, so their higher contribution into the power system increases the frequency oscillation. Electric vehicle’s sales are vastly increasing and tend to be more commercial for clients. The expansion of the electric vehicles means a change of the daily load profile, so there should be an economical and satisfying technique to charge the vehicle’s batteries without affecting the stability of the microgrid and satisfying the requirements of the owners. Smart grids promise to facilitate the integration of the electric vehicles into the electrical grid. The smart grid technology can enable vehicle’s charging or discharging to interact to the smart grid, thereby flattening the daily load curve and significantly reducing both generation and network investment needs. Electric vehicles can play a significant role in enhancing the stability of the frequency and allowing extra penetration of the renewable resources. This can be done through providing a smart control technique to charge the electric vehicles, which can be achieved by the bidirectional control of the electric vehicle’s batteries using the artificial neural network.
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Keywords


Artificial Neural Network; Bioenergy; Electric Vehicles; Frequency Stability; Genetic Algorithms; Renewable Energy; Vehicle to Grid; Zero-Emission

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