Abstract
Abstract Participation of low-voltage users in demand response is one of the most important ways to mitigate the mismatch between power supply and demand. However, existing smart metering devices cannot support the low-delay and high-reliability transmission of massive power data. 5G communication technology provides a new communication transmission structure for load aggregators to communicate with low-voltage users and power grid companies. This paper combines 5G communication slicing technology and edge computing technology to rationally allocate computing and communication resources through deep Q-learning algorithms. The scheme proposed in this paper has a lower delay than the equal resource allocation scheme and is suitable for high-speed transmission of massive interactive response data from low-voltage users.
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