Observer-based sliding mode frequency control for micro-grid with photovoltaic energy integration

In recent years, renewable energy has been largely integrated into power grids as well as micro-grids. The intermittent power injection will affect the stability of the systems, especially for the small-scale ones, such as the micro-grids. Among all the stability issues, load frequency control (LFC) of smart grid with renewable energy integration has become critical in the community. This paper studies the LFC for the island micro-grid with photovoltaic (PV) renewable energy integration, in which electric vehicles (EVs) are treated as distributed energy storage. With the changing load demand and PV power, the frequency of the micro-grid would deviate from the prescribed level. A observer-based sliding mode control is proposed to address this problem, where neural networks are used to implement the online observation of the PV power generation. Simulation analysis is carried out on the benchmark micro-grid, and the proposed frequency control method is effective for stabilizing the frequency to the command value over the PI and fuzzy control.