Four best practices of load forecasting for electric cooperatives

Several characteristics of electric cooperatives, such as large territories with varied climate, small customer density, high granularity load data, complex forecasting requirements and a small forecasting team, bring both opportunities and challenges to their load forecasting practices. This paper discusses four best practices from the electric cooperative sector using case studies from North Carolina Electric Membership Corporation (NCEMC), one of the largest Generation and Transmission Cooperatives in the nation. These best practices include taking advantage of hierarchical weather and load information to enhance forecasting accuracy, deploying an integrated load forecasting methodology to do more with less, and developing scenario based forecasts to mitigate risk.