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Welcome to EPRI's Load Shape Library version (LSL)^TM , a load data platform and repository developed and updated by Program 170 – Customer Technologies with guidance from utility membership. The updated version supersedes the preceding version developed in .

The platform houses:

• Load Shape Library (LSL)^TM , a publicly available load data repository of end use, building load profiles.
• Library PLUS 1.0 (available to project funders), an enhanced library of baseline and emerging end use load profiles leveraged from recent field demonstration projects.
• Load Disaggregation Model & Tool 1.0 (available to project funders), a customer end-use load profile prediction model and tool, availing building (or AMI) data

The objective of the LSL is to facilitate data sharing, compilation, and application of electric and natural gas load shapes. The load shapes are cataloged by climate zone, building, end use load and geography. End use load shape collection using statistically representative sample sizes are challenging and expensive. While EPRI and utilities work towards acquiring end use load shapes which are national and regionally representative, the LSL serves to provide best-available end-use load data. The databases in the Load Shape Library include electric end-use data aggregated over NERC regions, whole premise electric data by U.S city, residential efficient electric technology measures end-use load data from the Pacific Northwest and the Energy Management Circuit Breaker demo project. Each of these databases have been acquired either through EPRI and utility collaborated field pilots, utility studies with regional stakeholders or through historical project activities such as the EPRI CEED (Center for End-Use Energy Data) PowerShape™ data of 2000-01. Until statistical sample size driven representative load data by climate zone, customer class and building type are acquired, EPRI continues to revise the public LSL and the Library PLUS versions with annual updates of new load data additions or new feature enhancements.

Key Findings

• The LSL presents best-available data which does not represent statistically valid usage.
• Accuracy and vintage of load data determine the value and risk for use in utility applications. Users should treat the LSL data as a sample reference. Confidence and precision levels of the data are unknown.
• End-Use data from engineering models does not capture behavioral and other unobservable effects, thus rendering metered data as the preferred choice of the industry.
• End-use metered data acquired through a statistical sampling frame is widely preferred. High cost and intrusive nature of sub metering on customers continue to be key deterrents to broader utility efforts.
• EPRI’s collaborative research is focused on driving down the cost of end-use metering through innovative, non-intrusive metering alternatives. Disaggregation techniques like NILM (Non-Intrusive Load Monitoring) and Conditional Demand Analysis using AMI data are under research and pilot testing.
• Other low-cost intrusive metering methods such as smart breaker panels and distributed sensors are also being researched.