- Investor Relations
- Careers
- Blog
-
-
- Algeria
- Angola
- Benin
- Botswana
- Burkina Faso
- Burundi
- Cabo Verde
- Cameroon
- Central African Republic
- Chad
- Comoros
- Congo, Democratic Republic of the
- Cote d'Ivoire
- Djibouti
- Equatorial Guinea
- Eritrea
- Eswatini
- Ethiopia
- Gabon
- Gambia
- Ghana
- Guinea
- Guinea-Bissau
- Kenya
- Lesotho
- Liberia
- Libya
- Madagascar
- Malawi
- Mali
- Mauritania
- Mauritius
- Morocco
- Mozambique
- Namibia
- Niger
- Nigeria
- Rwanda
- São Tomé and Principe
- Senegal
- Seychelles
- Sierra Leone
- Somalia
- South Africa
- South Sudan
- Sudan
- Tanzania
- Togo
- Tunisia
- Uganda
- Zambia
- Zimbabwe
-
-
-
Itron Customers
Access Orders, Product Knowledge & Support
Itron Partners
Grow your business with Itron's Tools, Training & Technology
How do you want to primarily partner with Itron?
Itron Suppliers
Access Problem Solving Tools, Reports & Analysis
-
Trouble Signing In?View FAQ
-
Forecasting
Developing Net Load Uncertainty Forecasts to Support System Operations
Today, the deep penetration of renewable generation resources system operators are requiring new tools to place reasonable confidence bands around the Net Load forecasts driving operational decisions. In many cases, separate vendors are used to supply real-time forecasts of load and grid-connected solar and wind generation. With multiple vendors, each utilizing a different meteorological forecast, it is unclear how to incorporate uncertainty about loads with the uncertainty about the solar and wind generation forecasts.
For more information, download a paper that presents a general, unifying statistical framework for developing Net Load forecast uncertainty bands that account for load and generation forecast uncertainty.
This statistical approach is based on Professor Robert F. Engle’s seminal paper, Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometric 50(4): 987-1008. 1982
Director of Forecasting Solutions
Dr. Frank A. Monforte is Director of Forecasting Solutions at Itron, where he is an internationally recognized authority in the areas of real-time load and generation forecasting, retail portfolio forecasting, and long-term energy forecasting. Dr. Monforte’s real-time forecasting expertise includes authoring the load forecasting models used to support real-time system operations for the North American system operators, the California ISO, the New York ISO, the Midwest ISO, ERCOT, the IESO, and the Australian system operators AEMO and Western Power. Recent efforts include authoring embedded solar, solar plant, and wind farm generation forecast models used to support real-time operations at the California ISO. Dr. Monforte founded the annual ISO/TSO Forecasting Summit that brings together ISO/TSO forecasters from around the world to discuss forecasting challenges unique to their organizations. He directs the implementation of Itron’s Retail Forecasting System, including efforts for energy retailers operating in the United Kingdom, Netherlands, France, Belgium, Italy, Australia, and the U.S. These systems produce energy forecasts for retail portfolios of interval metered and non-interval metered customers. The forecast models he has developed support forecasting of power, gas and heat demand and forecasting of wind, solar, landfill gas, and mine gas generation. Dr. Monforte presides over the annual Itron European Energy Forecasting Group meeting that brings together European Energy Forecasters for an open exchange of ideas and solutions. Dr. Monforte directed the development of Itron’s Statistically Adjusted End-Use Forecasting model and supporting data. He founded the Energy Forecasting Group, which directs primary research in the area of long-run end-use forecasting. Recent efforts include designing economic indices that provide long-run forecast stability during periods of economic uncertainty. Email Frank at frank.monforte@itron.com, or click here to connect on LinkedIn.