SOFTWARE MODULE FOR BATTERY MONITORING FOR A DECISION-SUPPORT SYSTEM USING A DIGITAL TWIN
DOI:
https://doi.org/10.32689/maup.it.2025.4.29Keywords:
software module, hybrid energy microgrid, monitoring, edge computing, renewable energy sourcesAbstract
The purpose of this work is the development of a software module for measuring battery capacity with monitoring via a local interface and a cloud service, for further integration into a proactive digital twin system for managing energy distribution in networks with renewable energy sources. Methodology. An analysis of current trends in the energy sector and relevant technologies for remote device access was conducted through a review of scientific literature on related topics and available software products with similar functionalities. Based on this analysis, requirements for the development of the software module were formulated in the form of UML use case and sequence diagrams. The analysis of available hardware for implementing the monitoring system allowed the selection of the appropriate sensor model and microcontroller, which meet the computational power requirements for edge computing and the necessary connection interfaces. An iterative development model was used during the software implementation, providing incremental enhancements of functional capabilities at each stage. The software part itself is based on a functionally oriented programming approach with a responsibility-separated architecture, as the software module combines three components responsible for data collection and processing, the local web interface, and cloud integration with the Blynk IoT service. The results. A review of modern approaches to the development of monitoring systems and their integration into IoT infrastructure was conducted. Use case modeling of the software module and modeling of actors’ possible actions was performed through the development of UML diagrams. The software module is written in the C programming language and is compatible with ESP32 and other similar Arduino-based microcontrollers. Algorithms for calculation and error minimization of the system’s main indicators were implemented. The design of a local web page and an interface template in the Blynk IoT application was developed. Each of these screens displays the current battery status, and cloud integration with Blynk enables archiving of values and viewing them as charts. The software module was tested with a backup power system for a private house over a period of two months. The scientific novelty of the work is that the developed software module fundamentally uses architectural solutions that provide flexibility for integration into decision-support systems with a digital twin, as a data source for usage monitoring for energy stored in batteries. Conclusion. The work demonstrates the development of a software module for local and remote user monitoring of battery status, which will provide a decision-support system with data for analyzing the condition of a similar system and for taking automated actions based on this data.
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