Prediction and Preventive Control Scheme for Wind and PV Power Ramp Events

As the large scale integration of photovoltaic and wind power into the grid increases, renewable energy ramp events have become a potential threat to the secure operation of the power grid. To effectively address renewable energy power ramp events, this paper proposes a prediction and preventive control scheme. First, a rolling warning approach is achieved by the long short-term memory network and fuzzy logic, which provides warning levels and guides decision-making for preventive control. Second, a two-stage optimization scheduling model is proposed, including a day-ahead and an intra-day sub-model. The two-stage scheduling model comprehensively considers power support from interconnectors and preventive control costs. Simulation results demonstrate that the proposed scheme can provide adaptive preventive control strategies for power ramp events with varying risk levels, thereby enhancing the utilization of renewable energy and improving the security of power system.