# Enhanced Solar Photovoltaic System Management and Integration: The Digital Twin Concept
## 3 Digital Twins for Solar Photovoltaics
### PV-DT Based on Developmental Stage
#### 3.1.5 PV Installation Monitoring and Maintenance  
PV-DT provides a very efficient approach for continuous monitoring and maintenance. This application is effective for fault detection, classification, and rectification. Faults can occur in a single module, string, array, multiple strings, inverters, and other electronics. DTs can make overall site assessment easier after adverse weather events in extreme circumstances. In Table 3, we analyze academic research examining the use of PV-DT for PV monitoring and maintenance. Most of the research considered fault detection and classification for the solar modules and the associated electronics (inverters, load-line, and more). It should be noted that PV-DTs in operations and maintenance are not only designed for fault detection and classification. Other issues such as energy production and load-demand matching, new strategy implementation, energy storage integration, environmental impact assessments (CO\({}_{2}\) emissions saved), safety and compliance with the interconnected utility grid, and degradation analysis can also be addressed. However, due to the early stage development of PV-DT, there is limited industrial and academic literature in this respect.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Application** & **Methodology** & **Aim** \\ \hline \multirow{2}{*}{[56]} & BIPV system power estimation & DT + artificial neural networks processing & Real-time power production monitoring for fast identification of poor system performance \\  & Distributed PV such as rooftop installations & Error residual vector analysis of physical twin voltage and current output & Fault detections such as shading and associated electronic converter/sensor faults \\  & Utility PV fault detection & Continuous monitoring of the semiconductor switch’s diode voltage & Fault detection of semiconductor switches in PV electronic converters PV array string-level faults + fault classification + notification \\  & Fault diagnostics & Machine Learning and Clarke Transformation & Rapid solar array string-level fault detection such as shading, dust, and open-circuits \\  & Solar module fault detection for distributed solar installations & DT + data-driven statistical analysis & Solar module-level fault detection such as shading, dust, and open-circuits \\  & Fault remediation in PV installation & DT + Fault remediation algorithms & For managing inverter output based on module level fault type \\  & Operation and maintenance of large PV installation & DT + Extended memory particle swarm optimization BP neural network & String-level fault detection and aging of solar modules \\  & & 3 different machine learning algorithms to build different subsets of the overall DT DT DT + DL based shifted window (SWIN) transformer optimized by particle swarm optimization (PSO) & Power estimation and anomaly detection both at string level and module level \\  & Fault detection and classification in PV distribution systems & DT + Generative adversarial networks (GANs) + Social spider optimization & String level faults and converter line-to-line faults \\ \hline \hline \end{tabular}
\end{table}
Table 3: DTs PV monitoring and maintenance.