Bottom-Up Energy Analysis System – Methodology and Results

The Bottom-Up Energy Analysis System (BUENAS) is a stock accounting model developed by Lawrence Berkeley National Laboratory (LBNL) to project energy demand and evaluate the impact of energy efficiency policies, specifically Energy Efficiency Standards and Labeling (EES&L) programs, across residential, commercial, and industrial sectors.

• BUENAS projects energy demand from a 2005 base year to 2030, focusing on the impacts of efficiency policies by comparing a 'business as usual' (BAU) case to specific policy scenarios. The BAU case generally assumes 'frozen efficiency' from 2010 onwards, meaning the efficiency of new products remains constant unless market-driven improvements are specifically forecasted.
• The model covers 12 individual countries and the 27 Member States of the European Union as a single entity. These modeled economies represent 62% of global final energy demand, a figure that increases to 77% if China is included (though China is currently being adapted into the model from a separate LBNL appliance model).
• BUENAS targets end uses typically covered by EES&L programs, including residential appliances (air conditioning, refrigeration, lighting, etc.), commercial building equipment (HVAC, lighting, refrigeration), and industrial electric motors over 750 kW and distribution transformers. It is estimated that the covered end uses represent over 80% of the residential and commercial building sectors.
• The 'Recent Achievements Scenario' quantifies the impact of minimum efficiency performance standards (MEPS) implemented or announced between January 1, 2010, and April 1, 2011. For the subset of countries modeled, this scenario projects total 2030 savings of 389 TWh of electricity, 350 PJ of gas, and 219 mt of CO2.
• The 'Best Practice Scenario' assumes all countries adopt the most stringent global standards by 2015, with further improvements by 2020. This scenario projects a total 2030 savings potential of 1,583 TWh of electricity, 911 PJ of gas, and 988 mt of CO2, which is approximately 4.5 times the savings of the Recent Achievements Scenario.
• In the Best Practice Scenario, the residential sector shows the highest electricity savings potential at 27%, followed by the commercial sector at 22%. Savings for fuels are significantly lower, partly because major space and water heating technologies were not yet fully included in the model.
• The model utilizes the Long-Range Energy Alternatives Planning (LEAP) system to perform stock accounting. It calculates energy demand based on a modified Kaya identity: Energy = (Activity × Intensity) / Efficiency. Activity is driven by appliance ownership rates (residential) or floor area and industrial GDP (commercial/industrial).

APA

McNeil, M. A., Letschert, V. E., du Can, S. D. L. R., & Ke, J. (2012). Bottom-Up Energy Analysis System – Methodology and Results. Stockholm Environment Institute. https://cdn.leap.sei.org/documents/BUENAS.pdf

Chicago

McNeil, Michael A., Virginie E. Letschert, Stephane de la Rue du Can, and Jing Ke. Bottom-Up Energy Analysis System – Methodology and Results. Stockholm Environment Institute, 2012. https://cdn.leap.sei.org/documents/BUENAS.pdf.

Wikipedia

{{cite report |last1=McNeil |first1=Michael A. |last2=Letschert |first2=Virginie E. |last3=du Can |first3=Stephane de la Rue |last4=Ke |first4=Jing |title=Bottom-Up Energy Analysis System – Methodology and Results |publisher=Stockholm Environment Institute |date=April 2012 |url=https://cdn.leap.sei.org/documents/BUENAS.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{mcneil2012bottomup, author = {McNeil, Michael A. and Letschert, Virginie E. and du Can, Stephane de la Rue and Ke, Jing}, title = {{Bottom-Up Energy Analysis System – Methodology and Results}}, institution = {Stockholm Environment Institute}, year = {2012}, month = apr, url = {https://cdn.leap.sei.org/documents/BUENAS.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }