Huafeng Mao

With the ever-growing integration of renewable energy sources (RESs) into the power grid to meet escalating power demand, the intermittent and volatile nature of these sources poses significant challenges to the stability of power grid. To address the unstable output power resulting from the inherent randomness and fluctuation of RES, this paper introduces a novel cooperative control strategy designed for a photovoltaic-based grid-connected system. This proposed strategy leverages both battery energy storage system (BESS) and superconducting magnetic energy storage (SMES) within the hybrid energy storage system (HESS) framework. At top-level control (TLC), the control strategy employs a fuzzy control-based low-pass filter (LPF) to dynamically regulate filtration coefficient and realize transient power allocation optimization. Simultaneously, at the underlayer level control (ULC), a fast Model Predictive Control (MPC) method is implemented to maintain DC bus voltage by one-step prediction horizon. The feasibility and superiority of the proposed control strategy are systematically validated under diverse operating conditions, demonstrating its efficacy in enhancing the stability and performance of the grid-connected system.

Power impact frequently occurs during operation of shock loads, such as fusion devices, threatening the stable operation of the power system. Meanwhile, both short-time high pulse and long-time steady power exist, which have distinct time scales and amplitude characteristics. Currently, the capacity of power supply system is designed according to the maximum impulse power, causing the large redundancy and high cost. Aiming at this issue, hybrid power supply scheme based on energy storage technology with high power density provides a potential approach. However, little research focuses on the reasonable static configuration for different type of power supply. This paper presents the non-dominated sorting genetic algorithm (NSGA) algorithm to divide the two kinds of power, where impulse power can be treated by high-density energy storage and stable power is sustained by substation devices. In specific, taking the static investment and dynamic response of energy storage as the objectives, the critical optimal power can be determined. Finally, power scenario based on a typical Tokamak fusion device, international thermos-nuclear experimental reactor (ITER), is applied as case study of the proposed algorithm. The results show that the obtained crucial power can reasonably decrease the static capacity for substation to achieve the optimal economy and satisfy the mentioned objectives, providing the basis for other static capacity allocation circumstances and assisting accurate and high-efficiency smart control for power converters.