On-Demand Webinar

How AI Is Powering Accurate, Scalable Load and Generation Forecasting

Join us as we discuss how energy planners at utilities can take advantage of advances in AI to gain insights into advanced forecasting models in the cloud.

About the webinar

There’s never been anything easy about being an energy planner for any utility.

But as regional power market supply and demand continue to evolve, planners have little choice but to search for new ways forward.

And just as in almost any essential business today, utilities are being forced to dig deeper into the data to determine the best path.

We will discuss:

  • How to take advantage of advanced forecasting models in the cloud.
  • How AI-driven models used in operations, trading and integrated resource planning can provide benefits to power and utility companies and produce a significant ROI.
  • Why investments in cloud-enabled AI-powered forecasting tools are expected to grow in the power and utilities sectors.

Sie haben bereits ein SAS Profil? Dieses Formular automatisch ausfüllen: Einloggen


Wir behandeln Ihre persönlichen Daten gemäß dem SAS Privacy Statement.

  Ja, ich möchte von SAS Institute Inc. und seinen Tochterunternehmen per E-Mail Informationen zu SAS Produkten, Studien, White Paper und Veranstaltungen erhalten. Mir ist bekannt, dass ich meine Einwilligung jederzeit widerrufen kann, indem ich die Abmeldefunktion in den E-Mails nutze.
Nach dem Absenden dieses Formulars erhalten Sie eine E-Mail, in der wir Sie bitten, Ihre Einwilligung zu bestätigen (Double-Optin-Verfahren). Bitte schauen Sie in Ihrem Posteingang nach einer entsprechenden Nachricht von SAS und klicken den Bestätigungslink. Herzlichen Dank.

About the Experts

Arnie de Castro
Product Manager, SAS

Arnie de Castro is a Product Manager for industry products at SAS. He has more than 35 years’ experience in electric utility operations and resource management. Prior to his work at SAS, de Castro managed the development of enterprise market analytics software applications widely used in industry for electrical power system optimization, electrical price forecasting and energy transaction risk analysis. He developed and maintained software for long-term capacity planning, mid-term resource optimization and short-term unit commitment and economic dispatch.

John Villali
Research Director, IDC

John Villali is a Research Director for IDC Energy Insights, primarily responsible for thought leadership in utility digital transformation. He joined the IDC Energy Insights group with an impressive background in the power and natural gas markets. Villali's expansive experience within the energy industry includes providing superior market insight and having firsthand experience with the needs and desires of energy industry customers. Villali works out of the IDC offices in Framingham, MA. He is a regular contributor to the IDC Community energy blog.

Tao Hong, PhD
Duke Energy Distinguished Professor, UNC-Charlotte

Tao Hong is a Professor of systems engineering and engineering management (SEEM) and an Associate Professor of the Energy Production Infrastructure Center (EPIC) at the University of North Carolina at Charlotte. He has applied various statistical and optimization techniques to the development of algorithms and tools for utility applications of analytics, such as energy forecasting, power system planning, renewable integration, reliability planning and risk management. Hong provides consulting and education services to hundreds of organizations in all sectors of the utility industry.

Jennifer Whaley
Principal Systems Engineer, US Energy, SAS

Jennifer Whaley's experience includes industry and consulting in the electric utility sector, with a focus on generation planning, load forecasting, environmental policy impacts and economic analyses. She is an IEEE Senior Member and patent holder. She enjoys collaborating with customers and colleagues to solve business problems using advanced analytics – particularly emerging topics about load forecasting and the challenges of incorporating distributed energy resources on the grid and improving renewable forecasts for the energy needs of the future.