Frequency control using on-line learning method for island smart grid with EVs and PVs
Date of Original Version
Due to the intermittent power generation from renewable energy in the smart grid (i.e., photovoltaic (PV) or wind farm), large frequency fluctuation occurs when the load-frequency control (LFC) capacity is not enough to compensate the unbalance of generation and load demand. This problem may become worsen when the system is in island operating. Meanwhile, in the near future, electric vehicles (EVs) will be widely used by customers, where the EV station could be treated as dispersed battery energy storage. Therefore, the vehicle-to-grid (V2G) power control can be applied to compensate for inadequate LFC capacity, thus improving the island smart grid frequency stability. In this paper, an on-line learning method, called goal representation adaptive dynamic programming (GrADP), is adopted to coordinate control of units in an island smart grid. In the controller design, adaptive supplementary control signals are provided to proportional-integral (PI) controllers by online GrADP according to the utility function. Simulations on a benchmark smart grid with micro turbine (MT), EVs and PVs demonstrate the superior control effect and robustness of the proposed coordinate controller over the original PI controller and fuzzy controller.
Proceedings of the International Joint Conference on Neural Networks
Tang, Yufei, Jun Yang, Jun Yan, Zhili Zeng, and Haibo He. "Frequency control using on-line learning method for island smart grid with EVs and PVs." Proceedings of the International Joint Conference on Neural Networks , (2014): 1440-1446. doi:10.1109/IJCNN.2014.6889829.