Document Type
Closed Project
Publication Date
Fall 2016
Instructor
Jisun Kim
Course Title
Technology Forecasting
Course Number
ETM 532/632
Subjects
Energy storage, Electric batteries, Lithium ion batteries -- Applications to demand-response systems, Technological forecasting
Abstract
This paper examines the multi-perspective criteria affecting the adoption of energy storage technologies, specifically lead-acid and lithium-ion battery technologies, in Demand Response systems. These criteria are incorporated into a multi-perspective analysis using a Hierarchical Decision Model (HDM) to identify the key criterion influencing the adoption lead-acid vs. lithium-ion technology for the Demand-Response usage scenario. With cost-efficiency being identified by the HDM as the key criterion, the cost efficiency of lithium-ion battery technology is modeled, showing that lithium-ion technology may potentially achieve price-parity with lead-acid technology by 2025. Predicated on this improved price efficiency over the next 10 years, a Bass Diffusion Model is generated, which predicts significant adoption of lithium-ion battery technology for both Demand Response (DR) and Uninterruptible Power Supply (UPS) usage scenarios. The model forecasts cumulative sales of $100 million USD over the next 10 years, and achieving peak single-year sales of $75 million USD in 2031. We conclude with the implications of this shift in technologies, and recommendations for further research.
Rights
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Persistent Identifier
http://archives.pdx.edu/ds/psu/21345
Citation Details
Velez, Edwin Vilanova; Kim, Sejoong; Fabini, Scott; and Bowen, James, "Battery Technologies for Demand Response Systems" (2016). Engineering and Technology Management Student Projects. 39.
http://archives.pdx.edu/ds/psu/21345
Comments
This project is only available to students, staff, and faculty of Portland State University