Monthly Archives: May 2015
The Climate is Changing Rapidly – Are your Evaluations Keeping up?
A rapidly changing climate is causing the energy efficiency industry to rethink energy savings assumptions and parameters that reference outdated weather data. Many Technical Reference Manuals (TRMs) and engineering algorithms rely on static assumptions created using weather data that are several years, or even decades, old. Accounting for more recent changes in climate may influence the claimed savings for different types of efficiency measures by up to 5%. These changes may lead stakeholders to reconsider the incentivized measure mix in their portfolio to ensure they are incentivizing the most cost-effective measures moving forward.
We know that nine out of the ten warmest years on record have occurred this century. Even with all indicators pointing toward a climate that is changing rapidly, most energy efficiency programs estimate savings using weather data that does not take into account these recent increases in temperature.
Weather data plays a direct role in the calculation of energy savings for various energy efficiency measures. Increases in temperatures due to climate change may require cooling equipment installed in 2015 to operate more hours than equipment installed at the same location 10 years ago, leading to increased electricity savings for efficient cooling measures. Additionally, increases in temperatures may decrease the potential savings from heating measures as less heating is required in a warmer climate. When evaluators reference “outdated” weather data, it leads to inaccurate estimates of energy consumption. These inaccuracies can be significant in certain locations for specific measures.
In the absence of actual metering, most present day methods for modeling energy and demand rely on historical weather data (e.g., Typical Meteorological Year (TMY)) rather than the most recent or future projected weather scenarios. TMY data is a collection of weather data from localized weather stations spanning multiple years. The most recent TMY data available (TMY3) uses weather data collected between 1976 and 2005. The intent of a TMY is to represent the range of possible weather while still providing averages for a given localized weather station. However, because 7 of the 10 warmest years on record have occurred since TMY3 data became available, we believe it is no longer an accurate proxy for estimating present-day or future weather scenarios.
A rapidly changing climate requires our industry to leverage the latest tools and methods to incorporate changes to climate as close to “real-time” as possible. Two methods that we endorse to account for changes in climate include:
- Updating Weather Files: Software programs exist that allow users to generate climate change weather files by transforming local weather files (e.g., TMY data) into future climate predictions for their individual location. One example is the Climate Change World Weather File Generator (CCWorldWeatherGen). This free software allows users to generate “present-day” weather files as well as future weather files for a given weather station. We found that using this method with a chiller upgrade in South Carolina increased energy savings by 2-3% compared to using the unadjusted TMY3 data. Other proprietary software programs exist that can also create weather files to account for climate change impacts.
- Updating Parameters: One approach for updating a specific parameter (e.g., cooling degree-days) is to create a linear regression of published data over the course of multiple years for a specific location. Using a regression model allows us to more accurately predict current and future cooling degree-days for a specific location or region rather than using a static assumption as found in most TRMs. We can then update the linear regression model annually for a given location to account for ongoing changes to climate.
As energy efficiency program administrators are forced to rely less on lighting for savings (due to increasing efficiency standards), working to increase energy and demand impacts has become even more difficult. Changes in climate affect HVAC measures and those measures that rely on the operation of HVAC equipment to estimate savings such as programmable thermostats, insulation, infiltration reduction, and HVAC motors. We believe looking at changes in climate can help to more accurately measure savings for both cooling and heating measures. While a warmer climate will likely increase the potential savings for cooling measures (typically electric), it can simultaneously decrease savings from heating measures (electric and/or gas). Using the latest “typical” weather data allows program planners and evaluators to be confident that estimates align more accurately with the “new normal” range of weather.