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Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment

The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the pote...

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Detalles Bibliográficos
Autores principales: Shakouri, Mahmoud, Lee, Hyun Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749943/
https://www.ncbi.nlm.nih.gov/pubmed/26937458
http://dx.doi.org/10.1016/j.dib.2016.01.049
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author Shakouri, Mahmoud
Lee, Hyun Woo
author_facet Shakouri, Mahmoud
Lee, Hyun Woo
author_sort Shakouri, Mahmoud
collection PubMed
description The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in . The application of these files can be generalized to variety of communities interested in investing on PV systems.
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spelling pubmed-47499432016-03-02 Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment Shakouri, Mahmoud Lee, Hyun Woo Data Brief Data Article The amount of electricity generated by Photovoltaic (PV) systems is affected by factors such as shading, building orientation and roof slope. To increase electricity generation and reduce volatility in generation of PV systems, a portfolio of PV systems can be made which takes advantages of the potential synergy among neighboring buildings. This paper contains data supporting the research article entitled: PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment [1]. We present a set of data relating to physical properties of 24 houses in Oregon, USA, along with simulated hourly electricity data for the installed PV systems. The developed Matlab code to construct optimized portfolios is also provided in . The application of these files can be generalized to variety of communities interested in investing on PV systems. Elsevier 2016-02-01 /pmc/articles/PMC4749943/ /pubmed/26937458 http://dx.doi.org/10.1016/j.dib.2016.01.049 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Shakouri, Mahmoud
Lee, Hyun Woo
Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title_full Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title_fullStr Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title_full_unstemmed Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title_short Mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
title_sort mean-variance portfolio analysis data for optimizing community-based photovoltaic investment
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749943/
https://www.ncbi.nlm.nih.gov/pubmed/26937458
http://dx.doi.org/10.1016/j.dib.2016.01.049
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