A schedule method of battery energy storage system (BESS) to track day-ahead photovoltaic output power schedule based on short-term photovoltaic power prediction

In order to maximize the ability to improve the photovoltaic (PV) system tracking schedule output, based on the short-term prediction power of PV and randomness of prediction error, an energy storage day-ahead scheduling policy that adopts chance-constrained programming is proposed. The PV/energy storage output within the upper and lower range of schedule plan is taken as the objective function, the energy storage charge and discharge power and the state of charge (SOC) constraints are considered. In order to get each time charge and discharge power, the method adopts improved adaptive particle swarm optimization (PSO) algorithm based on Monte Carlo simulation. With typical output of PV power station as an example, the simulation results verify the feasibility and flexibility of the proposed strategy, it also provides effective reference scheme for day-ahead control of battery energy storage systems.