Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance

TitleUnderstanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance
Publication TypeConference Paper
Year of Publication2013
AuthorsNathan J Addy, Johanna L Mathieu, Sila Kiliccote, Duncan S Callaway
Conference NameASME 2013 International Mechanical Engineering Congress & Exposition
Conference LocationHouston, TX
Abstract

Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric demand against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed calculations. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed predictions. We focused on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.

LBNL Report Number

LBNL-5560E