Bi-level Optimal Control Strategy of Energy Storage Participating in Power Grid Frequency Regulation Based on Multi ObjectiveGenetic Algorithm

With the growing penetration of renewable energy sources such as wind and solar in the grid, intermittence and volatility bring many problems to the power grid, which makes the power grid lack of frequency modulation capacity and poor effect of frequency regulation. In this situation, the traditional automatic generation control (AGC), as one of the main measures of power grid frequency control, is not enough to meet the challenge of current frequency regulation. Therefore, this research proposes a new optimal control strategy. Firstly, in view of the comparative evaluation of the technical traits of conventional units and energy storage units participating in frequency modulation of grid, the frequency regulation model of energy storage combined units is established. Then, based on this, a two-level control strategy is proposed. The upper level takes economy and state of charge (SOC) as constraints, and the power is allocated based on multi-objective genetic algorithm. The lower level uses model predictive control to realize frequency optimization control. Finally, the simulation effects exhibit the effectiveness of the proposed manipulate method on MATLAB/Simulink platform.