Majority of the load forecasting literature has been on point forecasting, which provides the expected value for each step throughout the forecast horizon. In the smart grid era, the electricity demand is more active and less predictable than ever before. As a result, probabilistic load...

Although combining forecasts is well-known to be an effective approach to improving forecast accuracy, the literature and case studies on combining load forecasts are very limited. In this paper, we investigate the performance of combining so-called sister load forecasts with eight methods:...

Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore a range of new forecasting...

The answer depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years. Even more accurate forecasts, however, are obtained when allowing the forecast...

This paper introduces the concept of sister models, and proposes a sister model based load forecast combination method to enhance the point forecasting accuracy. Using the data from the Global Energy Forecasting Competition 2014, we create a case study with 4 sister forecasts from 4 sister...

Energy forecasting is one of those areas of great importance to electric grid that gets little attention - even from power industry insiders. But you need to know how to make the best of your forecasting process. Here are 13 tips to get you started.

The U.S. Energy Information Administration regularly publishes short-term forecasts of the price of crude oil. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify, and not particularly successful when compared with naïve...