Lead Performer: Lawrence Berkeley National Laboratory – Berkeley, CA Partner: Navigant Consulting – Chicago, IL
November 20, 2018
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Lead Performer: Lawrence Berkeley National Laboratory – Berkeley, CA
Partner: Navigant Consulting – Chicago, IL
DOE Total Funding: $2.8 million
Cost Share: $90,000
Project Term: October 1, 2018 – September 30, 2021
Funding Type: Lab Award
Project Objective
This project will develop a new integrated valuation methodology based on energy efficiency (EE) and demand response (DR) measure load shapes and regional electricity features to assess the load and economic relationships of EE and DR.
This project will advance a set of analytical methods, previously developed at LBNL, to quantify the interactive effects and dynamic valuation of energy efficiency and demand response from a systems perspective. The load impacts, to be quantified in hourly increments, will explore key uncertainties about the ways in which EE and DR complement and compete with each other. The economic impacts of different EE and DR resources’ load shapes and dispatch characteristics, will be quantified with a production-cost modeling tool. The results, synthesized by region, will describe key findings with implications for EE and DR resource program design and cost-effectiveness.
Project Impact
EE and DR resources reduce and/or shift load, providing important electric system benefits, including reduced need for new generation, transmission, and distribution system investments, and reductions in utility fuel and purchased power costs. This project informs the load and economic implications of integrated EE and DR from a systems perspective and considers their co-benefits.
This project intends to do the following:
- Advance the understanding of ways in which EE and DR resources compete with and complement each other.
- Develop novel cost-effectiveness and valuation frameworks for EE and DR program design.
- Produce publicly available EE and DR load shape data sources.
Contacts
DOE Technology Manager: Monica Neukomm
Lead Performer: Mary Ann Piette, Lawrence Berkeley National Laboratory