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Title: Solar soft cost ontology: a review of solar soft costs

Abstract

The continued deployment of renewable energy is critical to the energy transition necessary for climate change mitigation. Since cost is one of the primary drivers of solar adoption, we must continue to reduce the cost of solar to hasten the transition to clean energy. Currently, solar soft costs account for 52%–70% of the cost of an installed residential solar photovoltaic (PV) system in the U.S. These costs are persistent and an increasing share of the costs, since hardware costs continue to decline. The consensus on a definition of soft costs is 'non-hardware costs', but defining something by what it is not does not tell us what it is, which makes it difficult to study and understand. To this end, we developed the solar soft cost ontology (SSCO) to provide a comprehensive view of the complex and variable knowledge domain of solar soft costs. In this work, we identify the main categories of solar soft costs, how they relate to each other, how that knowledge is created, shared, and acquired, and the relevant actors in the solar soft cost knowledge ecosystem. Developed by coding a corpus of nearly 130 academic articles, the resulting ontology in web ontology language (OWL) includes 136more » classes and 87 properties. The SSCO can facilitate and enhance knowledge transfer of research findings and best practices within and between stakeholder communities, including researchers, practitioners, and policy makers, that seek to address solar soft costs. We conclude with a discussion of potential applications and use cases for the SSCO among this diverse stakeholder community.« less

Authors:
ORCiD logo [1];  [1]
  1. Univ. of Texas, Austin, TX (United States)
Publication Date:
Research Org.:
Univ. of Texas, Austin, TX (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
OSTI Identifier:
1595723
Grant/Contract Number:  
EE0007658
Resource Type:
Accepted Manuscript
Journal Name:
Progress in Energy
Additional Journal Information:
Journal Volume: 2; Journal Issue: 1; Journal ID: ISSN 2516-1083
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; soft cost; solar energy; ontology; learning process; review; knowledge domain; SSCO

Citation Formats

Beck, Ariane, and Rai, Varun. Solar soft cost ontology: a review of solar soft costs. United States: N. p., 2019. Web. doi:10.1088/2516-1083/ab59be.
Beck, Ariane, & Rai, Varun. Solar soft cost ontology: a review of solar soft costs. United States. https://doi.org/10.1088/2516-1083/ab59be
Beck, Ariane, and Rai, Varun. Fri . "Solar soft cost ontology: a review of solar soft costs". United States. https://doi.org/10.1088/2516-1083/ab59be. https://www.osti.gov/servlets/purl/1595723.
@article{osti_1595723,
title = {Solar soft cost ontology: a review of solar soft costs},
author = {Beck, Ariane and Rai, Varun},
abstractNote = {The continued deployment of renewable energy is critical to the energy transition necessary for climate change mitigation. Since cost is one of the primary drivers of solar adoption, we must continue to reduce the cost of solar to hasten the transition to clean energy. Currently, solar soft costs account for 52%–70% of the cost of an installed residential solar photovoltaic (PV) system in the U.S. These costs are persistent and an increasing share of the costs, since hardware costs continue to decline. The consensus on a definition of soft costs is 'non-hardware costs', but defining something by what it is not does not tell us what it is, which makes it difficult to study and understand. To this end, we developed the solar soft cost ontology (SSCO) to provide a comprehensive view of the complex and variable knowledge domain of solar soft costs. In this work, we identify the main categories of solar soft costs, how they relate to each other, how that knowledge is created, shared, and acquired, and the relevant actors in the solar soft cost knowledge ecosystem. Developed by coding a corpus of nearly 130 academic articles, the resulting ontology in web ontology language (OWL) includes 136 classes and 87 properties. The SSCO can facilitate and enhance knowledge transfer of research findings and best practices within and between stakeholder communities, including researchers, practitioners, and policy makers, that seek to address solar soft costs. We conclude with a discussion of potential applications and use cases for the SSCO among this diverse stakeholder community.},
doi = {10.1088/2516-1083/ab59be},
journal = {Progress in Energy},
number = 1,
volume = 2,
place = {United States},
year = {2019},
month = {12}
}

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