Ningbo University of Technology has recently launched an innovative project titled “Energy Storage with Purpose”, which focuses on interactive operation and maintenance (O&M) for power sources based on digital twins. This initiative aims to enhance the operational efficiency of energy storage systems, optimize scheduling strategies, and improve equipment safety, providing robust technical support for various sectors including new energy power plants, commercial energy storage, and smart grids.
The project constructs a comprehensive intelligent O&M system that integrates digital twins, artificial intelligence, big data analysis, and cloud-edge collaborative computing. Compared to traditional energy storage O&M models, this system employs AI to optimize scheduling, achieving intelligent management of battery charging and discharging. By leveraging digital twin technology, the project team has developed a global simulation and optimization model for energy storage systems, enhancing the assessment of equipment health and predictive maintenance capabilities, ensuring that systems maintain optimal performance across different operational environments.
In terms of data collection and monitoring, the project utilizes an efficient system in conjunction with edge computing technology to process operational data of energy storage devices in real-time. The cloud-based intelligent analysis platform offers precise equipment health assessments and smart alert functions, further boosting the reliability of energy storage systems. Intelligent communication and remote monitoring features allow O&M personnel to remotely oversee the operation of energy storage sites via the cloud and achieve automated O&M scheduling, significantly reducing maintenance costs and increasing operational efficiency.
The “Energy Storage with Purpose” project demonstrates extensive application prospects. In the field of new energy power plants, the intelligent O&M system can optimize the capacity for renewable energy absorption, enhance grid stability, and minimize grid shocks caused by power fluctuations. In commercial and industrial energy storage scenarios, intelligent scheduling optimization strategies can effectively lower electricity costs for enterprises and reduce grid load fluctuations while enhancing the utilization of renewable energy alongside distributed photovoltaics. In the context of smart grid integration, the project’s intelligent energy storage system can provide rapid frequency response and dynamic voltage regulation, improving the grid’s regulation capacity and the penetration rate of renewable energy.
Statistics indicate that the innovative technologies applied in this project can improve the overall energy efficiency of energy storage systems by 5% to 10%, reduce the curtailment rate of wind and solar energy in new energy power plants by 30% to 40%, lower electricity costs for industrial energy storage by 15% to 25%, and enhance the frequency response speed of grid energy storage applications by 30% to 50%. These achievements not only provide substantial technical support for the intelligent development of the energy storage industry but also contribute to the optimization of the global energy structure and the realization of carbon neutrality goals.
Ningbo University of Technology has stated its commitment to further advancing the “Energy Storage with Purpose” project research and applications, contributing more to the intelligent transformation and sustainable development of the energy storage industry.
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