U.S. federal energy regulators convene tomorrow to discuss modernization of the nation’s electric power grid.
Recent years have brought significant changes in technology and the ways we use energy. From distributed energy resources like solar panels to a variety of "smart grid" applications, society has new tools that may be able to improve the nation's energy sector. As a result, state and federal energy regulators are considering "grid modernization." Issues in play can include whether improvements to the nation’s
electric power grid are appropriate, and if so, how to fund them.
For several years, the Federal Energy Regulatory Commission has considered grid modernization issues. Now, the Commission has scheduled a grid modernization event for tomorrow.
At the Commission's April meeting, it will hear from representatives from the U.S. Department of Energy, including Patricia A. Hoffman,
assistant secretary for the Office of Electricity Delivery and Energy Reliability, and Roland Risser, acting deputy assistant secretary for Renewable Power. The Energy Department will also offer panelists from its National Renewable Energy
Laboratory, Pacific Northwest National Laboratory, Idaho National
Laboratory, Sandia National Laboratories, and Lawrence Berkeley National
Laboratory.
Following the FERC meeting, the panelists will be available for a post-meeting information session on the
work of the Grid Modernization Laboratory Consortium. Panelists are expected to discuss devices and integrated systems, sensing and measurement, system
operations, control and power flow, design and planning tools, security
and resilience, and institutional support.
Energy powers society; society's choices shape energy policy. A blog about our energy resources and the choices they present for society.
Showing posts with label National Lab. Show all posts
Showing posts with label National Lab. Show all posts
Report: solar panels add home appraisal value
Tuesday, November 17, 2015
"How will putting rooftop solar panels on my home affect its value?" is a common question among those considering residential-sited solar energy projects.
It will help, according to a report recently released by the Lawrence Berkeley National Laboratory, finding solar photovoltaic systems add value to homes in a variety of markets under traditional appraisal methodology as well as statistical analysis.
Intuition and previous studies have shown a "price premium" effect for solar photovoltaic systems in some markets. Where a price premium applies, a home with a solar PV system can command a higher price than a comparable home without one.
A 2013 study of California using statistical analysis found "clear support that a premium exists in the marketplace; thus, PV systems have value, and their contribution to home values must be assessed." That study found a strong correlation between premiums and PV system size, and a weak negative correlation with PV system age. Essentially, "larger systems garner larger premiums and older systems garner smaller premiums," with each 1-kilowatt increase in size estimated as commanding a $5,911 higher premium, while each year of system age yields a $2,411 lower premium.
A similar 2014 study of eight states found "PV consistently adds value across a variety of states, housing and PV markets, and home types." Notably, these studies relied heavily on hedonic or regression pricing models to account for characteristics specific to each property (home type, site, neighborhood, market). While such large-scale statistical analysis is commonly performed in economics, home buying more commonly relies on the appraisal process to support both price formation and financing. Few previous studies were written by experienced real estate appraisers using paired-sales techniques or other standard appraisal methods.
The Lawrence Berkeley National Laboratory has released a report designed to bridge this gap, featuring a comparison of statistically derived PV premiums and analysis performed by experienced home appraisers. That report, "Appraising into the Sun: Six-State Solar Home Paired-Sales Analysis", examined 43 pairs of comparable homes that sold with and without PV across seven areas in six state (California, Oregon, Florida, Maryland, North Carolina, and Pennsylvania). It compared traditional real estate appraisal analysis of these homes to contributory-value estimates based on gross cost, net cost, and income. Overall, it found that under either statistical or appraisal based analysis, PV systems added premiums of $2.68/W to $4.31/W across states, averaging $3.78/W or about $14,000 for an "average-size" system sold in 2011 (3.8 kW).
The study did identify some difficulty in conducting comparable-sales analysis on homes with solar panels. (It also includes a section titled "Warning to Users of this Study", noting the analysis was limited to specific times and places, only considered host-owned systems with crystalline-silicon panels, and does not address potential sales price implications related to the location of the PV systems.) However, it found that appraised premiums are in agreement with the hedonic modeling results as well. Practically speaking, this means cost- and income-based statistical estimates of PV premiums could be reliable when paired-sales analysis is impossible.
Further information about the Lawrence Berkeley National Laboratory report on appraisal value of residential solar PV systems can be found in a November 12, 2015 presentation hosted on its website.
It will help, according to a report recently released by the Lawrence Berkeley National Laboratory, finding solar photovoltaic systems add value to homes in a variety of markets under traditional appraisal methodology as well as statistical analysis.
 |
| A residential rooftop solar project in Massachusetts. |
Intuition and previous studies have shown a "price premium" effect for solar photovoltaic systems in some markets. Where a price premium applies, a home with a solar PV system can command a higher price than a comparable home without one.
A 2013 study of California using statistical analysis found "clear support that a premium exists in the marketplace; thus, PV systems have value, and their contribution to home values must be assessed." That study found a strong correlation between premiums and PV system size, and a weak negative correlation with PV system age. Essentially, "larger systems garner larger premiums and older systems garner smaller premiums," with each 1-kilowatt increase in size estimated as commanding a $5,911 higher premium, while each year of system age yields a $2,411 lower premium.
A similar 2014 study of eight states found "PV consistently adds value across a variety of states, housing and PV markets, and home types." Notably, these studies relied heavily on hedonic or regression pricing models to account for characteristics specific to each property (home type, site, neighborhood, market). While such large-scale statistical analysis is commonly performed in economics, home buying more commonly relies on the appraisal process to support both price formation and financing. Few previous studies were written by experienced real estate appraisers using paired-sales techniques or other standard appraisal methods.
The Lawrence Berkeley National Laboratory has released a report designed to bridge this gap, featuring a comparison of statistically derived PV premiums and analysis performed by experienced home appraisers. That report, "Appraising into the Sun: Six-State Solar Home Paired-Sales Analysis", examined 43 pairs of comparable homes that sold with and without PV across seven areas in six state (California, Oregon, Florida, Maryland, North Carolina, and Pennsylvania). It compared traditional real estate appraisal analysis of these homes to contributory-value estimates based on gross cost, net cost, and income. Overall, it found that under either statistical or appraisal based analysis, PV systems added premiums of $2.68/W to $4.31/W across states, averaging $3.78/W or about $14,000 for an "average-size" system sold in 2011 (3.8 kW).
The study did identify some difficulty in conducting comparable-sales analysis on homes with solar panels. (It also includes a section titled "Warning to Users of this Study", noting the analysis was limited to specific times and places, only considered host-owned systems with crystalline-silicon panels, and does not address potential sales price implications related to the location of the PV systems.) However, it found that appraised premiums are in agreement with the hedonic modeling results as well. Practically speaking, this means cost- and income-based statistical estimates of PV premiums could be reliable when paired-sales analysis is impossible.
Further information about the Lawrence Berkeley National Laboratory report on appraisal value of residential solar PV systems can be found in a November 12, 2015 presentation hosted on its website.
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