alexa Parametric Study of Community Load Aggregation on Thermal Storage Efficiency
ISSN: 2168-9717

Journal of Architectural Engineering Technology
Open Access

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Research Article

Parametric Study of Community Load Aggregation on Thermal Storage Efficiency

Kevin Carbonnier* and Stephen Treado

Department of Architectural Engineering, The Pennsylvania State University 104 Engineering Unit A, University Park, PA, 16802, USA

*Corresponding Author:
Kevin Carbonnier
Department of Architectural Engineering
The Pennsylvania State University
104 Engineering Unit A
University Park, PA, 16802, USA
E-mail: [email protected]

Received Date: March 31, 2013; Accepted Date: July 21, 2013; Published Date: July 25, 2013

Citation: Carbonnier K, Treado S (2013) Parametric Study of Community Load Aggregation on Thermal Storage Efficiency. J Archit Eng Tech 2:110 doi: 10.4172/2168-9717.1000110

Copyright: © 2013 Carbonnier K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Renewable energy technologies, most notably wind, solar hot water, and solar photovoltaic are not always available to the residential sector due to financial and feasibility challenges. In this paper we investigate the potential benefit of aggregating residential loads to more closely match the renewable energy generation profiles and to have a smoother energy demand curve which can be more efficiently supplied by an energy storage system. Four individual residential load profiles are matched against an optimized combination of wind, solar hot water, and solar photovoltaic generation. A simulation is then run to assess the percentage of the demand which must be supplied via auxiliary energy sources (i.e. the grid) with and without a thermal energy storage system. Finally, these four load profiles are randomly combined to create a 50 user community load profile. This aggregated profile is also matched against the renewable energy generation and the results are compared to individual load profile performance metrics for January, April, and July data. In the April and July cases, the community load profile reduced the demand supplied by auxiliary energy by as much as 5% on average in a simple system without storage (An improvement over the average of the individual loads of about 11%). With storage, a community system reduces demand supplied by auxiliary energy by about 0.8%, which is an improvement over the average individual loads of also about 11%. It is concluded that community shared renewable energy systems can be beneficial not only in terms of economics and feasibility, but also in terms of thermodynamics, which is often overlooked.


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