A Quantile Intervals Prediction Based Power-voltage Control Method with Storage Regulation

After the large-scale integration of new energy into the power grid, the rapid changes in the output of new energy stations have led to increased system voltage fluctuations, making it difficult to coordinate and control multiple types of reactive power sources. After adopting traditional deterministic reactive voltage control, the random changes in the output of the new energy station and loads in the system may lead to exceeding voltage limits. So considering the prediction error of new energy and load in the system, the predictive quantile interval method is proposed to carry out the dynamic reactive power and voltage control of the wind, solar, hydro, thermal, and storage power system in typical scheme considering active power control of energy storage, so as to minimize the active power loss and voltage deviations of the system, and solve it by branch and bound method; in order to suppress fluctuations in new energy and loads, nodes with wind farms, photovoltaic power stations and loads are equipped with a certain capacity of energy storage, and their supporting inverter devices provide reactive power compensation; so power and energy constraints of energy storage are considered in the dynamic reactive power optimization control; special consideration is given to the climbing constraints of synchronous units and the frequency regulation effect of hydro and thermal units in actual regulation in the control model. The control effect of the proposed method is verified in IEEE 118 bus system, which greatly reduces the degree of voltage out of limit and the occurrence rate of voltage out of limit under various random scheme, and effectively responds to the random change of new energy and load.