
Abstract: In order to optimise the coordinated control of micro-grid complex energy storage including photovoltaic and wind power, improve the absorption ability of distributed energy generation and reduce the cost, this paper proposes a Double Deep Q-Network reinforcement learning algorithm to train agents to interact with the microgrid environment and learn the optimal scheduling control mechanism. [pdf]

Active distribution network hybrid collaborative energy storage configuration refers to the combination of different types of energy storage technologies (such as battery energy storage, supercapacitors, compressed air energy storage, etc.) with traditional power distribution network systems, achieving flexible scheduling and optimized operation of the power grid through intelligent control and collaborative management (Du et al., 2023). [pdf]

The project has carefully planned four core sections: New Materials Energy Storage Technology Research Institute, focusing on cutting-edge technology exploration; New Energy Storage Materials and Engineering Technology Center, promoting technological innovation and application; Source-grid-load-storage integrated smart data platform to achieve intelligent upgrades in energy management; and new energy industry supply chain company to build an efficient and coordinated supply chain system. [pdf]
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