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New Frontiers in Time and Space: The Technical Challenges of Modeling New Resources

At a webinar last week, The Changing Face of Electric Resource Planning,” Dr. Jeremy Fisher and Patrick Luckow explored the changing functions of integrated resource plans across the United States. Dr. Elizabeth A. Stanton and Dr. Ariel Horowitz moderated the webinar. Dr. Horowitz continues the conversation here with a post on the technical challenges of modeling new energy resources.

Historically, utility operations have been based on large, centralized generators supplying power to meet the ever-increasing demands of consumers. As consumption patterns shift and new resources (including renewable energy and demand-side strategies) gain ground, the paradigms of the past no longer describe our best future. Regulators and utilities are increasingly seeking to encourage, plan for, or simply engage with an energy future that relies on these new resources. The integrated resource plans (IRPs) made by utilities are starting to reflect this shift, with some utilities showing a new focus on integration of renewable energy and incorporation of energy efficiency. However, modeling technology has yet to catch up with this new reality.

New types of energy resources have characteristics that differ in important ways from traditional fossil-fired generators. The modeling tools that are conventionally used for IRPs were designed around generation technologies that are completely dispatchable (that is, can increase or decrease their output on demand – even if ramping up or down may take hours), located only on the utility side of the grid, and operate similarly no matter the weather or time of day. These models consider a great deal of detail about individual units, so long as those details don’t change over time and space. For example, a model might allow for a new unit to be built, with detailed descriptions of the unit’s minimum operational time, maximum ramp rate, costs, and outage patterns. But, when deciding where to place this new unit, the model may not be able to be more specific than identifying a state or a utility’s service area. Planning models generally represent time in hour-long chunks and make only limited use of the idea of randomness, representing a unit’s capabilities in any year as basically similar to the year before and the year after.

While these simplifications were sufficient in the past, new energy resources require new complexity. The availability of renewable resources such as solar and wind power varies widely through both space and time and can fluctuate rapidly and change from year to year or season to season. Using rough approximations of the behavior of these resources gets riskier as we rely on them more and more. Appropriate valuation of resources like battery storage also requires sub-hour modeling, as many battery installations are used primarily for ancillary services (which occur on the scale of seconds or less). Modeling distributed generation and other demand-side resources requires tools that understand the distribution system as well as the transmission system. Although the increased spatiotemporal granularity demanded by new energy resources is a challenge to the makers and operators of planning models, venturing into these new frontiers can open up new opportunities to find creative ways to build the energy systems of our future.

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Eager for more information on the future of the Clean Power Plan, integrated resource planning, and renewable energy generation? We invite you to join us today--Wednesday, June 22, 2016--for the last webinar of our Spring Webinar Series. If you missed previous webinars in the series, you can visit our webinars page to watch recordings of each installment.