Data-Driven Network Latency Processing for Auxiliary Services in Virtual Power Plant

Nowadays, with the increasingly prominent contradiction between environment and development, renewable energy technology has received extensive attention. However, due to natural fluctuation, there are many challenges in safety and stationarity in an electric power system with a large-scale portion of renewable energy. Meanwhile, the conventional electric power system in which the power supply follows the load change paradigm is gradually broken. Thanks to advanced information and communication technology, energy storage technology, and automatic control technology, the power supply, grid, load, and energy storage interactive electric power system regulation paradigm came into being. A virtual power plant (VPP) is a concrete realization of this regulation paradigm. In this paper, based on the characteristics of VPP service requirements, we propose a data-driven method to estimate and predict the network latency. First, we investigate and summarize the characteristics of a VPP participating in various auxiliary services and their demand for communication networks. Second, the practical implementation of a VPP network architecture, which combines the local network and the backhaul network, is presented based on a secure access gateway and VPP monitoring and scheduling platform for flexible resource aggregation and regulation. Then, based on a delay probe, a network latency acquisition method is proposed for a public backhaul network. Finally, a data-driven network latency processing method is proposed to support the VPP’s participation in different communication requirements of auxiliary services.