RIS ID

144631

Publication Details

M. Islam, H. Lu, M. J. Hossain & L. Li, "An IoT- Based Decision Support Tool for Improving the Performance of Smart Grids Connected With Distributed Energy Sources and Electric Vehicles," IEEE Transactions on Industry Applications, vol. 56, (4) pp. 4552-4562, 2020.

Abstract

vThe growing penetration of distributed energy sources (DES), such as photovoltaic (PV) solar power, battery energy systems and electric vehicles (EVs) into low voltage distribution networks is creating serious challenges for distribution network operators. Uncertain nature of these DES and EV charging is a key factor to cause unbalance, which degrade network performance in terms of energy loss, voltage unbalance, and voltage profile of the distribution network, etc. Some methods were proposed to mitigate such negative impact of these uncertain DES and EV charging from both centralized and decentralized approaches by controlling charging or discharging power of EVs. However, these methods involve all active EVs to participate in coordination and this causes significant inconvenience to EV owners along with requirements of complex communication infrastructure and huge data processing overhead. This article proposes an Internet of Things -based centralized control strategy to coordinate EV and DES distribution by using the differential evolution (DE) optimization algorithm. The obtained results show that the proposed control strategy can improve network performance (voltage imbalance, neutral current, energy loss, and node voltage) significantly. In addition, the control strategy is less demanding on communication infrastructure and convenient for EV owners as well as having a lighter data processing overhead.

Available for download on Friday, April 22, 2022

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Link to publisher version (DOI)

http://dx.doi.org/10.1109/TIA.2020.2989522