ARIMA time series modeling for forecasting thermal rating of transmission lines

While utilities use customer demand estimates to predict load on their network, it is important to know if the thermal constraints of the transmission line will allow them to meet their contractual power delivery obligations. The data provided by real-time tension monitoring systems gives valuable information about the line behavior under differing weather and load conditions. This resource has also allowed statistical prediction under real conditions instead of traditional nonstatistical methods that can be subjective, judgmental, or based on a series of unrealistic assumptions about future conditions. Information collected from real-time tension monitoring systems enabled the creation of more elaborate models, which can dynamically approximate and track thermal rating patterns and capture behavioral changes. These new models can be used to generate forecasts of future rating patterns.