4.6 Article Proceedings Paper

Optimal schedule of 100% renewable energy microgrid considering demand response of EVs

Journal

ENERGY REPORTS
Volume 9, Issue -, Pages 1743-1750

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2023.04.223

Keywords

EV; Source-grid-load-storage; 100% renewable energy microgrid; Hierarchical scheduling; Pumped storage

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This research establishes a hierarchical scheduling model for microgrid, which is 100% powered by renewable energy and considers the demand response characteristics of electric vehicle users. It includes an EV layer and a REMG layer, and achieves system optimization and cost reduction by adjusting the load and various energy outputs.
With the breakthrough of key technologies of renewable energy, microgrid is gradually developing towards 100% renewable energy. However, aiming at the characteristics of renewable energy power such as randomness and intermittency, the microgrid needs to cope with the double fluctuations from the power source side and the load side, which will pay more costs for absorbing renewable energy. To implement source-grid-load-storage integration, this research establishes a hierarchical scheduling model for microgrid, which considers the demand response (DR) characteristics of electric vehicle (EV) users and is 100% powered by renewable energy. The model includes two layers, EV layer and renewable energy microgrid (REMG) layer. The first layer is EV layer. This layer formulates an appropriate charging price according to the user's price response characteristics, and initially regulates the fluctuation of the original load while taking into account the customer satisfaction. The second layer is REMG layer. Based on the preliminarily optimized load, this layer adjusts the renewable energy rejection, the interactive power of main grid, and the output of pumped storage and battery storage under grid connection mode and island mode. The REMG layer can reduce system operating costs, while suppressing interactive power fluctuations and increasing the utilization rate of renewable energy. Simulation shows that the proposed optimal scheduling model can achieve win-win between EV and users. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCBYlicense (http://creativecommons.org/licenses/by/4.0/).

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