Optimal allocation of energy storage capacity for hydro-wind-solar multi-energy renewable energy system with nested multiple time scales

Multi-energy supplemental renewable energy system with high proportion of wind-solar power generation is an effective way of “carbon neutral”, but the randomness and volatility of wind-solar power generation seriously affects the safe and stable operation of power grid. With the development of energy storage technology, this problem can be effectively solved by configuring energy storage, but how to reasonably configure energy storage is one of the key issues due to the expensive energy storage. To this end, a multi-timescale nested energy storage capacity optimization model for multi-energy supplemental renewable energy system with pumped storage hydro plant based on a three-battery group control operation strategy is proposed. First, the electrochemical energy storage is added to the supplemental renewable energy system containing hydro-wind-solar to form a hybrid energy storage system with pumped storage hydro units, and its group control strategy and charging/discharging coordinated operation are investigated. Then, a double-layer energy storage capacity optimization model nested in multiple time scales is developed. The inner layer optimizes hydropower and pumped storage output to smooth out the more fluctuating wind power output with large time scales. The outer layer optimizes energy storage taking into account factors such as output deviation, cost, attenuation, and dynamic prediction life to smooth out the less volatile and smaller time-scale wind power. Finally, simulation demonstrates that the proposed model can make full use of the flexible regulation capability of pumped storage hydro units and the fast response capability of batteries to maximize the fluctuation of the supplemental system into the grid, and further reduce the peaking pressure of the receiving end of the grid. In addition, the superiority of the proposed three-battery grouping strategy over the traditional battery control method in terms of saving investment cost and mitigating battery life loss is also verified. The advantages of the strategy in terms of carbon reduction and cleaner production are also illustrated in quantifiable terms.