# A Heuristic Algorithm for Locating Line-to-Line Faults in Photovoltaic Systems
## 5 Conclusions  
This paper successfully developed and validated a heuristic algorithm for line-to-line fault location based on module group voltage measurement, aimed at addressing the problem of locating line-to-line short-circuit faults in PV arrays, achieving the following key outcomes:  
1. By utilizing the characteristic that line-to-line short-circuit faults do not create multiple maximum power points in the P-V curve, this study investigates the phenomenon of line-to-line short-circuit faults at maximum power generation in the array by extracting the P-V curve.
2. Using a 21 \(\times\) 2 PV module array configuration, this study examines six cases of two types of line-to-line short-circuit faults: intra-string and cross-string. Based on empirical rules, a heuristic algorithm for line-to-line fault location based on module group voltage measurement is proposed.
3. Simulation tests conducted through MATLAB/Simulink reveal that the heuristic line-to-line fault location algorithm can successfully locate most line-to-line short-circuit faults, reducing the troubleshooting scope to within a single module group, with a success rate of approximately 97.56%.
4. The line-to-line fault location method proposed in this paper is intuitive, simple, and fast. Although the location process is illustrated using a 21 \(\times\) 2 PV array, it can be adapted for different applications and various array sizes. Moreover, the module group size for voltage measurement can be adjusted based on the required location accuracy.
5. The importance of this work lies in its practical applicability and economic benefits. By enabling precise fault localization using only module group voltage measurements, maintenance teams can reduce inspection time by approximately 80% compared to manual whole-array inspection. This translates to significant cost savings for large-scale PV installations, where arrays may contain thousands of modules spread over vast areas. Furthermore, the algorithm's simplicity and low computational requirements make it suitable for integration into existing PV monitoring systems without substantial hardware upgrades. As the global PV capacity continues to grow, such efficient fault localization methods become increasingly critical for maintaining system reliability and safety.
6. Despite the high success rate, the proposed algorithm has certain limitations: * It cannot locate faults when both array terminals are short-circuited, causing all voltages to read 0 V. * It assumes relatively uniform voltage distribution among modules, which may not hold under severe partial shading. * It is designed for single line-to-line faults and may not accurately locate multiple simultaneous faults.  
* The threshold determination requires prior knowledge of array configuration and environmental conditions.
* Future research should focus on extending the algorithm to handle multiple fault scenarios, integrating machine learning for adaptive threshold determination, and field validation in large-scale PV installations. The proposed method represents a significant step toward automated, efficient PV system maintenance, with potential applications in utility-scale solar farms where rapid fault location is critical for minimizing revenue losses.  
Conceptualization, C.-C.K. and J.-Z.J.; methodology, B.-H.L. and H.-T.C.; validation, J.-Z.J., B.-H.L. and H.-C.C.; formal analysis, H.-T.C. and H.-C.C.; investigation, B.-H.L.; resources, H.-T.C.; data curation, J.-Z.J.; writing--original draft preparation, J.-Z.J.; writing--review and editing, H.-C.C. and C.-C.K.; supervision, C.-C.K.; project administration, H.-C.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflicts of interest.