Document Type

Conference Proceeding

Language

eng

Publication Date

2015

Publisher

International Institute of Forecasters

Source Publication

International Symposium on Forecasting

Abstract

Energy utilities see higher risk when forecasting for their operating areas (service territories) on days that are high-demand or difficult to forecast. These days often have unusual weather patterns (e.g., colder than normal or significant temperature fluctuation from previous days). Due to their unusual nature, data describing these days are scarce. We present a method that successfully transforms natural gas consumption data from operating areas in vastly different geographic regions and climates, with different customer bases, to make better forecasts for areas that have insufficient historical data. Our surrogate data transformation algorithm results in higher forecast accuracy, thereby reducing the risk to energy utilities.

Comments

Published version. Published as part of the proceedings of the 35th International Symposium on Forecasting, 2015. Publisher link. © International Institute of Forecasters 2015. Used with permission.

Share

COinS