Application of Airborne LiDAR Data and Geographic Information Systems (GIS) to Develop a Distributed Generation System for the Town of Normal, IL

Jin H. Jo; Zachary Rose; Jamie Cross; Evan Daebel; Andrew Verderber; John C. Kostelnick; Jin H. Jo; Zachary Rose; Jamie Cross; Evan Daebel; Andrew Verderber; John C. Kostelnick

doi:10.3934/energy.2015.2.173

AIMS Energy

2015, Volume 3, Issue 2: 173-183. doi: 10.3934/energy.2015.2.173

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Research article Special Issues

Application of Airborne LiDAR Data and Geographic Information Systems (GIS) to Develop a Distributed Generation System for the Town of Normal, IL

1.
Department of Technology, Illinois State University, Campus Box 5100, Normal, IL 61790-5100 USA;
2.
Department of Geography-Geology, Illinois State University, Normal, IL, USA

Received: 26 November 2014 Accepted: 23 March 2015 Published: 31 March 2015

Distributed generation allows a variety of small, modular power-generating technologies to be combined with load management and energy storage systems to improve the quality and reliability of our electricity supply. As part of the US Environmental Protection Agency's effort to reduce CO₂ emissions from existing power plants by 30% by 2030, distributed generation through solar photovoltaic systems provides a viable option for mitigating the negative impacts of centralized fossil fuel plants. This study conducted a detailed analysis to identify the rooftops in a town in Central Illinois that are suitable for distributed generation solar photovoltaic systems with airborn LiDAR data and to quantify their energy generation potential with an energy performance model. By utilizing the available roof space of the 9,718 buildings in the case study area, a total of 39.27 MW solar photovoltaic systems can provide electrical generation of 53,061 MWh annually. The unique methodology utilized for this assessment of a town's solar potential provides an effective way to invest in a more sustainable energy future and ensure economic stability.
- photovoltaics,
- distributed generation,
- renewable energy,
- energy modeling,
- sustainability
Citation: Jin H. Jo, Zachary Rose, Jamie Cross, Evan Daebel, Andrew Verderber, John C. Kostelnick. Application of Airborne LiDAR Data and Geographic Information Systems (GIS) to Develop a Distributed Generation System for the Town of Normal, IL[J]. AIMS Energy, 2015, 3(2): 173-183. doi: 10.3934/energy.2015.2.173

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Abstract

Distributed generation allows a variety of small, modular power-generating technologies to be combined with load management and energy storage systems to improve the quality and reliability of our electricity supply. As part of the US Environmental Protection Agency's effort to reduce CO₂ emissions from existing power plants by 30% by 2030, distributed generation through solar photovoltaic systems provides a viable option for mitigating the negative impacts of centralized fossil fuel plants. This study conducted a detailed analysis to identify the rooftops in a town in Central Illinois that are suitable for distributed generation solar photovoltaic systems with airborn LiDAR data and to quantify their energy generation potential with an energy performance model. By utilizing the available roof space of the 9,718 buildings in the case study area, a total of 39.27 MW solar photovoltaic systems can provide electrical generation of 53,061 MWh annually. The unique methodology utilized for this assessment of a town's solar potential provides an effective way to invest in a more sustainable energy future and ensure economic stability.

References

[1]	US EPA (2014) Fact sheet: Clean Power Plan Overview. US EPA Carbon Pollution Standards. Available from: http://www2.epa.gov/carbon-pollution-standards/fact-sheet-clean-power-plan-overview.
[2]	EIA (2013) Distributed Generation System Characteristics and Costs in the Buildings Sector. U.S. Energy Information Administration. Available from: http://www.eia.gov/analysis/studies/distribgen/system/pdf/full.pdf.
[3]	Walla T, Widén J, Johansson J, et al. (2013) Determining and Increasing the Hosting Capacity for Photovoltaics in Swedish Distribution Grids, 27th European Photovoltaic Solar Energy Conference and Exhibition, 9.
[4]	Jo JH, Otanicar T (2011) A hierarchical methodology for the mesoscale assessment of building integrated roof top solar energy systems. Renew Energ 36: 2992-3000. doi: 10.1016/j.renene.2011.03.038
[5]	Leitelt, L (2010) Developing a solar energy potential map for Chapel Hill, NC. Master's Project Report, University of North Carolina Chapel Hill. Available from: https://cdr.lib.unc.edu/indexablecontent?id=uuid:6e5c0eac-e631-4741-b038-d7e9c3e4da41&ds=DATA_FILE.
[6]	Sauter R, Watson J (2007) Strategies for the deployment of micro-generation: Implications for social acceptance. Energ Policy 35: 2770-2779.
[7]	NREL (2012) System Advisor Model Software Description. National Renewable Energy Laboratory. Available from: https://www.nrel.gov/analysis/sam/.
[8]	NREL (2009) Solar Photovoltaic Cell/Module Manufacturing Activities 2008. National Renewable Energy Laboratory. Available from: http://www.eia.doe.gov/cneaf/solar.renewables/page/solarreport/table3_8.html.

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