Energy Consumption Data: Enlightened and Encrypted
Access to energy data is essential to creating energy efficiency benchmarking and energy management
Utility companies use meters to collect data on the amount of electricity and fuel a building uses, which in turn is used to bill customers. When tracked over time, the data provide information on trends in energy use. To address data aggregation issues associated with the public release of building-level energy consumption data, staff at PNNL completed an empirical analysis using data from six participating utility companies. Tracking and analysis of energy data is valuable because it can be used to evaluate energy costs and improve building performance.
To address data aggregation issues associated with the public release of building-level energy consumption data, staff at PNNL completed an empirical analysis using data from six participating utility companies. Tracking and analysis of energy data is valuable because it can be used to evaluate energy costs and improve building performance.
For this study, the participating utility companies released anonymous monthly electricity and/or gas consumption data by meter to PNNL, under a non-disclosure agreement. The data contained monthly consumption profiles of nearly 715,000 non-residential meters, representing about 129,000 individual commercial buildings from geographically and climatically diverse regions of the country.The tradeoff between incremental gains in protection versus losses in building coverage resulting from increasing the threshold was described in detail in the final PNNL report titled,
Commercial Building Tenant Energy Usage Data Aggregation and Privacy. The report provides material designed to inform decision-making related to streamlining energy data access.
Aggregating Data Protects Privacy
Tracking requires the building owner to acquire monthly whole-building energy usage information. This can be challenging for buildings in which individual tenants have their own utility meters and accounts with the utility. While utilities can supply anonymous consumption data, this alone does not afford sufficient privacy protection for individual tenants.
Some utilities and utility regulators have turned to aggregation of customer energy use data (CEUD) as a way to give building owners whole-building energy usage data while protecting customer privacy. Meter profile aggregation adds a layer of protection that decreases the risk of revealing CEUD as the number of meters aggregated increases.
The PNNL study statistically characterized the similarity between individual energy usage patterns and whole-building totals at various levels of meter aggregation. The study established a quantitative approach for providing practitioners, such as utilities, public utility commissions, and other policy-makers, with a defensible aggregation threshold selection method, which will protect tenant privacy and ensure that data on the greatest number of buildings can be reported.
PNNL Research Team: Olga Livingston, Dave Anderson, Trenton Pulsipher, Nora Wang