Distributed energy storage aggregation systems refer to systems that connect multiple distributed energy storage devices together to form a unified energy storage system. This system can collect energy from multiple power sources and store and release it as needed. Its control methods and processes are as follows:
1. Selection and Configuration of Energy Storage Equipment: First, it is necessary to select energy storage equipment of appropriate capacity, typically including lithium-ion batteries and supercapacitors. Factors such as charge/discharge efficiency, lifespan, and price should be considered during selection. Then, these energy storage devices need to be configured, determining their location and connection methods.
2. System Monitoring and Data Acquisition: Sensors, meters, and other equipment are installed to monitor the output power of photovoltaic and wind power sources, as well as the power consumption of the load. It is also necessary to collect status information of energy storage devices, such as their charging and discharging status.
3. Aggregation and Management: Based on the status information and power output of the energy storage devices, algorithms are used to aggregate the energy from different energy storage devices into an energy storage aggregation system. Simultaneously, the system also needs to manage the energy storage devices, including charging, discharging, and SOC (State of Charge) management.
4. Control Strategy: To ensure the stability, reliability, and economy of the system, a suitable control strategy needs to be designed. Common control strategies include Model Predictive Control (MPC) and Maximum Power Point Tracking (MPPT).
5. Application Scenarios: Distributed energy storage aggregation systems can be applied to multiple fields, such as microgrids, smart cities, factories, and buildings. The control methods and processes will differ depending on the specific scenario. For example, in microgrids, interaction with the main grid needs to be considered; in smart cities, issues such as peak-valley pricing and load balancing need to be taken into account.
