Research on multi-time scale optimization of integrated energy system based on multiple energy storage

To address the challenge of source-load imbalance arising from the low consumption of renewable energy and fluctuations in user load, this study proposes a multi-time scale optimization strategy for an integrated energy system equipped with multiple energy storage components. The strategy introduces a comprehensive three-stage optimization method labeled "Day-ahead- Day-intra rolling- Real-time peak regulation and frequency modulation." This approach systematically optimizes the output plans for each equipment within the system across distinct stages. The time-scale of day-ahead optimization is 4 h, day-intra optimization is 15 min, and real-time refinement is 1 min. In real-time planning, SC equipment is incorporated into the output plan for each day-intra equipment schedule, employing VMD frequency division technology and a fuzzy control strategy. The system's differential power is segregated into high-frequency and low-frequency signals, and both energy storage and power storage equipment are recalibrated. Through this process, the study determines the optimal storage capacity for the entire system. The results show that the charge and discharge cost of the lithium battery can be saved 89.45 % by increasing the SC in the real-time optimization stage, and the charge and discharge times are reduced from 268 to 23 times. Under the optimal storage device capacity solved, the capacity of the SC can reach the upper and lower limits several times by working for 24 h on a 1 min time scale. To the greatest extent, the capacity waste problem caused by excessive capacity setting is avoided. The optimized configuration and operation method designed in this paper can effectively reduce the capacity redundancy of the system energy storage equipment, and reduce the daily operation cost of the whole system.