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Brad Roberts

dblp:147/2336 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 77% Computational finance and economics · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy systems and smart grids
energy storage
0.212014
Business Models for Deploying and Operating Energy Storage and Risk Mitigation Aspects · Proc. IEEE 2014
Computational finance and economics
cost-benefit analysis
0.112014
Business Models for Deploying and Operating Energy Storage and Risk Mitigation Aspects · Proc. IEEE 2014
YearPublicationVenuePosition
2014 Business Models for Deploying and Operating Energy Storage and Risk Mitigation Aspects
abstract
Energy storage is a novel technology with perceived performance and lifecycle risks. In addition, there are many different business/regulatory paradigms for investors in storage resources based on existing business models for electric power assets today. At the heart of designing storage applications for best cost-benefit results and for evaluating storage economics of particular applications is the way different business models realize direct monetized benefits and indirect avoided costs from energy storage. This paper unpacks the complexities of deploying and operating energy storage and identifies any potential barriers to participation in storage. It lays out some of the existing and hypothetical business models for the investment in and operation of electric storage, and explores the complexities and possibilities of these business models when storage is bucketed” as a generation, transmission, distribution, or customer asset. It also identifies possible policy recommendations and areas for further analysis, including some alternative models that consider storage as a unique asset class that offers services offered by other assets today.
Ralph Masiello, Brad Roberts, Tom Sloan
Proc. IEEE2