Thursday, March 19, 2015

EISPC Update: Electric Load Forecasting Finds Its New Life in the Smart-Grid Era

Source: NARUC Bulletin 3/16/2015

A new report sheds light on how regulators and the utility industry can develop and evaluate load forecasts in an era of uncertainty with the electricity sector. The report also offers insights and findings from three case studies in 10 States.

The Energy Production and Infrastructure Center of University of North Carolina at Charlotte and the Robert W. Galvin Center for Electricity Innovation of Illinois Institute of Technology collaborated on this report, entitled ‘”Load Forecasting Case Study.” Commissioned by the Eastern Interconnection States’ Planning Council, the report provides a comprehensive review of load forecasting topics for States, planning coordinators, and others.

Additionally, the report presents three case studies in different jurisdictions (ISO New England, Exelon and North Carolina Electric Membership Corporation) to assist planning coordinators and their relevant States with applying innovative concepts, tools, and analysis to their forecasting regime.

“Load forecasting has been an integral part of the utility business for over a century, though the practice has not changed much since 1990s,” said Dr. Tao Hong, the lead author of the report and Chair of IEEE Working Group on Energy Forecasting, “Smart grid technologies bring a great opportunity for improvement of the load forecasting practice.”

The Eastern Interconnection States’ Planning Council and the National Association of Regulatory Utility Commissioners commissioned the study. EISPC is a consortium of State-level government agencies responsible for siting electric transmission across the 39 States, including the District of Columbia and City of New Orleans, located within the Eastern Interconnection. The group is funded by the U.S. Department of Energy.

The report demystifies the many complex concepts, terms, and statistics that are used in load forecasting. It serves as both a primer on load forecasting and also provides an in-depth discussion of load forecasting topics with a real-world demonstration that will be useful to state commissioners, planning coordinators, utilities, legislators, researchers, and others.

Some of the key takeaways from the study include:
  1. Load forecasting is the foundation for utility planning, but utilities still face challenges in getting accurate load forecasts. Particularly in light of significant change in the resource mix resulting from environmental regulation, aging infrastructure, the projected low cost of natural gas, and decreasing costs of renewable technologies, it is crucial for utilities to have accurate load forecasts for resource planning, rate cases, designing rate structures, and financial planning.   
  2. Many factors influence the load forecasting accuracy, such as geographic diversity, data quality, forecast horizon, forecast origin, and customer segmentation. A model that works well in one region may not be the best model for another.   
  3. Deployment of smart-grid technologies has made high granular data available for load forecasting. An emerging topic, hierarchical load forecasting, which provides forecasts at various levels in the system, is of great importance in the smart grid era. Each sub-region or utility may need a customized model to maximize the forecast accuracy. Meanwhile, the accuracy gained at a lower level can be often translated to the enhanced forecasts at the aggregated levels.  
  4. Within the same utility, a model that forecasts well in one year may not generate a good forecast for another year. In order to establish the credibility in load forecasting, utilities have to follow forecasting principles to develop a consistent load forecasting methodology.   
  5. Long-term load forecasts should be in the form of scenarios, intervals or density functions, rather than point estimates (one number per time interval throughout the forecast horizon). The evaluation should also be based on probabilistic scoring rules.   
  6. All forecasts are wrong. It would be ideal to predict the future with as much accuracy as possible, but it is more realistic to predict the future while taking into consideration the insights on various risks that a utility may be faced with. Load forecasting is not a static process. Rather, utilities and policymakers should be continually looking for ways to improve the process, the databases, and advance the state-of-the-art in forecasting tools. It is imperative that utilities devote substantial time and resources to the effort to develop credible load forecasts.
The report (in PDF) can be found HERE.

1 comment:

  1. I'm hosting a webinar to discuss this report on April 6, 2015. The registration is open here: If you have any questions for me to answer, please leave them in this comment field.


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