Edge computing based optical storage building integrated energy management system
By collecting and analyzing inverter operating status data in real time through edge computing, evaluating its performance and making optimization decisions, the problem of inverter performance affecting energy loss is solved, and the power generation efficiency of the building-integrated photovoltaic and energy storage system is improved.
CN122155635APending Publication Date: 2026-06-05STATE GRID (BEIJING) INTEGRATED ENERGY SERVICES CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- STATE GRID (BEIJING) INTEGRATED ENERGY SERVICES CO LTD
- Filing Date
- 2026-02-06
- Publication Date
- 2026-06-05
AI Technical Summary
Technical Problem
Existing building-integrated photovoltaic and energy storage management systems do not consider the impact of inverter performance on energy loss, resulting in low energy utilization.
Method used
By collecting real-time operating status data from inverters and current sensors through edge computing, and combining this data with illumination data, the system can evaluate inverter performance and determine whether operation optimization is needed to reduce energy loss.
Benefits of technology
By evaluating the inverter's operating status and performance in real time, anomalies can be detected and optimized in a timely manner, thereby improving power generation efficiency and maximizing energy utilization.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122155635A_ABST
Abstract
The application relates to the technical field of energy management, and particularly discloses an integrated energy management system of a light storage building based on edge computing, which comprises a data acquisition module, which is used for collecting inverter operation state data, current sensor operation state data and light data in the energy management system in real time through edge computing. The operation state of the inverter can be analyzed by combining the data collected in the data acquisition module, and whether the operation state of the inverter is abnormal can be analyzed. Then, the performance of the inverter can be evaluated in real time by combining the real-time collected energy storage system data, and whether the performance change of the inverter will cause additional energy loss and reduce the power generation efficiency can be further analyzed. Then, whether the inverter optimization operation is needed is decided based on the analysis result, that is, the inverter can be optimized to avoid the occurrence of the condition of reducing energy loss, so that the power generation efficiency is improved and the energy utilization is maximized.
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