Electric Vehicle Load Forecasting in Rural Areas: A Systematic Review

The growing adoption of electric vehicles, combined with increasing interdependence between urban and rural areas, raises concerns about the resilience of electrical networks, particularly in rural regions where infrastructure is less robust and more limited in complexity. Accurate load forecasting is therefore essential to support effective planning and mitigate potential stress on the grid. This study aims to evaluate and synthesize methodologies for predicting electrical loads generated by electric vehicles in rural areas, with the objective of identifying current practices, data characteristics, and methodological gaps. Following a systematic review approach, the work compiles and analyzes recent literature to provide a structured reference framework for researchers and practitioners. The findings reveal a growing research interest in this field, particularly in Europe and North America, with both model-based and data-driven approaches used in comparable proportions, and short-term forecasting emerging as the most common horizon. However, a lack of standardization in the documentation of network characteristics remains a significant limitation across studies. The review contributes by clarifying the state of research, highlighting critical gaps, and offering guidance for future work. These results underscore the importance of developing standardized criteria for documenting network properties and integrating diverse data sources to enhance the accuracy and applicability of load forecasting in rural distribution networks.