In order to achieve the goals of carbon neutrality, large-scale storage of renewable energy sources has been integrated into the power grid. Under these circumstances, the power grid faces the challenge of peak shaving. Therefore, this paper proposes a coordinated variable-power control strategy for multiple battery energy storage stations (BESSs), improving the performance of peak shaving. Firstly, the strategy involves constructing an optimization model incorporating load forecasting, capacity constraints, and security indices to design a coordination mechanism tracking the target load band with the equivalent power. Secondly, it establishes a quantitative evaluation system using metrics such as peak–valley difference and load standard deviation. Comparison based on typical daily cases shows that, compared with the constant power strategy, the coordinated variable-power control strategy has a more obvious and comprehensive improvement in overall peak-shaving effects. Furthermore, it employs a “dynamic dispatch of multiple BESS” mode, effectively mitigating the risks and flexibility issues associated with single BESSs. This strategy provides a reliable new approach for large-scale energy storage to participate in high-precision peaking.

Lithium-ion battery energy storage systems (BESSs) face significant safety challenges arising from internal short-circuit (ISC) faults, which can ultimately trigger thermal runaway. To address this, this paper proposes an ISC fault diagnosis method based on multivariate information entropy (MIE). The proposed approach fuses voltage and temperature time series from battery cells to extract fault features via MIE. Furthermore, a hierarchical diagnosis framework incorporating statistical confidence intervals is developed to enable robust ISC fault diagnosis. Experiments were conducted on 180 Ah lithium iron phosphate batteries, utilizing external resistors to simulate ISC faults of varying severity. The method was further validated using real-world fault data from an electric vehicle accident. Results demonstrate that the proposed method effectively distinguishes between normal and faulty cells, with MIE values exhibiting a monotonic increase as fault severity intensifies. In the real-world dataset, the method identifies the faulty cell 240 s before a discernible voltage drop, demonstrating its capability for early ISC detection.

Conventional control strategies for battery energy storage systems (BESSs) fail to achieve symmetrical and coordinated control between the DC/DC and DC/AC conversion stages, resulting in unsatisfactory DC capacitor voltage fluctuation suppression and threatening the safe and stable operation of the system. To address this issue, this study proposes an improved model predictive control (MPC)-based control method that explicitly considers DC capacitor voltage fluctuation suppression. First, a dynamic mathematical model of the BESS is established by jointly considering its DC/DC and DC/AC energy conversion stages. The model is then discretized using the first-order forward Euler method to facilitate controller implementation. Second, the cost function of the proposed MPC-based control method is designed to simultaneously incorporate DC capacitor voltage fluctuation suppression and output current tracking errors on both the DC and AC sides. Finally, the switching states of the DC and AC converters are selected as the control set, and the optimal switching signals for the BESS are determined by optimizing the aforementioned cost function. Verification results demonstrate that, compared with traditional control strategies, the proposed strategy achieves more symmetrical stable and dynamic performance and reduces DC side capacitor voltage fluctuation by approximately 80%, thereby effectively ensuring the safe and stable operation of the system.

The open-winding dual inverter topology has the advantages of a multilevel output, high DC voltage utilization, large modulation freedom, and easy fault tolerance, and is widely used in photovoltaic grid-connected systems. The open-winding photovoltaic–energy-storage converter system studied in this paper adopts this topology. The system consists of photovoltaic and energy-storage units, and the two converters can independently deliver active power to the grid when the DC-bus voltages on both sides are balanced. To achieve active-power regulation and distribution between the photovoltaic side and the energy-storage side, this paper constructs a mathematical model of the open-winding dual-inverter photovoltaic–energy-storage system and proposes a power-allocation strategy for steady-state operation. Compared with the conventional SPWM, the proposed strategy introduces a reference-voltage allocation layer before the SPWM modules, enabling flexible power sharing while retaining the simple implementation of the conventional SPWM. The proposed strategy effectively guarantees the operational stability and grid-connected power quality of the photovoltaic–energy-storage converter. Finally, its feasibility and effectiveness are verified through simulation analysis and experimental testing.