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Development of An IoT-Enabled Photovoltaic-Battery Renewable Energy System
- Source :
- International Journal of Intelligent Systems and Applications in Engineering; Vol. 11 No. 8s (2023): Advances on Machine Learning and Artificial Intelligence in Computer Technology; 355-361
- Publication Year :
- 2023
- Publisher :
- International Journal of Intelligent Systems and Applications in Engineering, 2023.
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Abstract
- Solar energy is considered as a prominent source of renewable energy, mainly due to the vast abundance of sunlight and rapid advancements of photovoltaic (PV) technology. The performance, reliability and lifespan of PV systems are severely affected by numerous environmental factors and fault occurrences, which include: (1) extreme swing in the operating temperature; (2) low solar irradiation levels which appear undetected in PV systems, resulting in energy losses and degradation of PV panels; and (3) non-homogenous shading and accumulation of dirt on PV panels, causing thermal imbalance and hotspots on the panels. Therefore, it is important to monitor the operating temperature and homogeneous detection of sunlight on the PV modules to guarantee efficient energy production. In this paper, we present the development and demonstration of a sensor-assisted Internet of Things (IoT)-based photovoltaic-battery renewable energy system. The adoption of the IoT solution for monitoring the real-time variations in environmental factors and system performance is discussed here. For the PV-battery hardware module, solar panels along with rechargeable batteries are constructed to supply the system. Inverters and controllers are used to synchronize the voltage level and transformation of AC power from DC power. In the design of the IoT system, the Arduino Mega microcontroller and ESP32 TTGO board are used along with sensors for recording the temperature, presence of dust/dirt, and voltage and current levels. The working prototype enables real-time data to be captured and sent to the cloud database for data collection, performance analysis, and diagnosis/detection of faults in the proposed system.
Details
- Language :
- English
- ISSN :
- 21476799
- Database :
- OpenAIRE
- Journal :
- International Journal of Intelligent Systems and Applications in Engineering
- Accession number :
- edsair.issn21476799..01e272b54965cb0a87f3406b2c49209c