Federal Government Brags about Being Average

I recently ran across a post on the Energy Information Agency (EIA’s) web sit highlighting the fact that from 2003 to 2012 Federal buildings had achieved a greater decrease in energy use intensity than had been achieved by commercial buildings, on average. I find this spin to be offensive on various levels.

The relevant graph is shown below.

2016-09-16-government-building-eui

The first thing to note is that, even with this decrease in energy use Federal buildings still have higher EUI than do other commercial buildings (compare the red and blue 2012 bars).

Second, while I am pleased that the Federal government is learning how to operate its buildings almost as well as the rest of the commercial building sector, it is not a remarkable accomplishment.  It reminds me of a verbal exchange between then Governor Bill Clinton and businessman Ross Perot during a presidential debate.  Clinton was bragging that under his leadership the State of Arkansas had improved its rank among other states in education from almost last up to the middle of the pack.  Ross Perot pointed out that you don’t have to be innovative when you are ranked last — you will move up by just copying what others have done.  (I will confess, this is my memory of what happened, but it might be that I imagined this exchange — it is a good story, in any case.)

Third, why is the EIA engaging in such spin?  This agency is supposed to gather and disseminate energy facts.  Spin should be left to political parties.

 

The Illusions of EUI in Calculating Energy Savings

In the last month I have found the time to begin looking at the 2012 CBECS data released by the EIA last May.

Today I am writing about something I just learned concerning U.S. Worship Facilities.  Here I am looking at the subset of Worship Facilities that meet the criteria stated by the EPA for performing their multivariate regression for the Worship Facility ENERGY STAR model (about 80% of all U.S. Worship Facilities).

In comparing the 2012 and the 2003 CBECS data for Worship Facilities we see there was an estimated 2% increase in the number of these buildings.  As there is an 8-9% uncertainty in the estimated number of these facilities, this increase is  not statistically significant.  The EIA data show that the mean site energy use intensity (EUI) for these facilities actually went down by 15% from 48 to 41 kBtu/sf — and this reduction is statistically significant as it exceeds the 6-8% uncertainty in these figures.  No doubt some government agency will use this reduction to claim success in programs to promote energy efficiency.

But nature is not impressed because total energy used by these buildings actually went up.  The reason — the buildings are, on average, getting bigger!  From 2003 to 2012 the total gross square footage contained in this filtered subset of Worship Facilities increased from 3.2 to 3.8 billion sf, a whopping 23%.  Thus the total site energy used by Worship Facilities grew by 5%.  A similar conclusion can be made for source energy, even with the improved efficiency of the electric power sector over this last decade.

It should be noted that statistics show that the number of Americans who actually go to church declined by about 7% from 2007-2014.  So in a decade when religious worship is decreasing the amount of energy used by Worship Facilities has grown by about 5%.

Bottom line — don’t be fooled by decreases in building EUI.  It is total energy that matters.

New CBECS Data confirm EPA’s K-12 School ENERGY STAR score is nonsense

As I have written before — indeed, the subject of my recent book — my work shows that the EPA’s ENERGY STAR benchmarking scores for most building types are little more than placebos.  The signature feature of the ENERGY STAR benchmarking scores is the assumption that the EPA can adjust for external factors that impact building energy use.  This adjustment is based on linear regression performed on a relatively small dataset.  For most building types this regression dataset was extracted from the Energy Information Administration’s 2003 Commercial Building Energy Consumption Survey (CBECS).  The EPA has never demonstrated that these regressions accurately predict a component of the energy use of the larger building stock.  They simply perform their regression and assume it is accurate in predicting EUI for other similar buidings.

In the last three years I have challenged this assumption by testing whether the EPA regression accurately predicts energy use for buildings in a second, equivalent dataset taken from the earlier, 1999 CBECS.  In general I find these predictions to be invalid.    For one type of building — Supermarkets/Grocery Stores — I find the EPA’s predictions to be no better than those of randomly generated numbers!

In May of this year the EIA released public data for its 2012 Commercial Building Energy Consumption Survey.  These new data provide yet another opportunity to test the EPA’s predictions for nine different kinds of of buildings.  These new data will either validate the EPA’s regression models or confirm my earlier conclusion that they are invalid. Over the next year I will be extracting 2012 CBECS data to again test the nine ENERGY STAR benchmarking models based on CBECS data.

This week I performed the first of these tests for K-12 Schools.  539 records were extracted from the CBECS 2012 data for K-12 Schools representing 230,000 schools totalling 9.2 billion gsf.  After filtering these records based on EPA criteria, 431 records remain, representing a total of 137,000 schools with 8.0 billion gsf.

I performed the EPA’s weighted regression for K-12 Schools on this final dataset and obtained result totally inconsistent with those obtained by the EPA using CBEC 2003 data. Only 3 of the 11 variables identified by the EPA as “significant predictors” of building Source EUI for K-12 Schools demonstrated statistical significance with the 2012 data. Numerous other comparisons confirmed that the EPA’s regression demonstrated no validity with this new dataset.

The EPA will no doubt suggest that their model was valid for the 2003 building stock, but not for the 2012 stock — because the stock has changed so much in the intervening 9 years! While this seems plausible, this explanation does not hold water.  First, CBECS 2012 data do not suggest significant change in either the size or energy use of the K-12 School stock.  Moreover, this explanation cannot also explain why the EPA regression was not valid for the 1999 building stock — unless the EPA is to suggest that the stock changes so much in just 4 years to render the regression invalid.  And if that is the EPA position — then why would they even attempt to roll out new ENERGY STAR regression models for K-12 Schools based on 2012 CBECS data more than 4 years after these data were valid?  You can’t have it both ways.  Either the stock changes rather slowly and a 4 year delay is not important or this benchmarking methodology is doomed to be irrelevant from the start.

 

The more plausible explanation — supported by my study — is that the EPA’s regression is simply based on insufficient data and is not valid — even for the 2003 building stock.  I suggest a regression on a second, equivalent sample from the 2003 stock would yield results that differ from the EPA”s origina regression.  The EPA’s ENERGY STAR scores have not more validity than sugar pills.

 

NYC Energy Benchmarking Report Over-estimates Energy Savings

The Mayor’s Office in New York City has recently released their annual report looking at the 2013 energy data for commercial buildings.  This is the fourth such report.  Each annual report appears to take longer and longer to prepare suggesting it is easier to gather energy data than to analyze and understand it.

The lead line in this report is that those preparing the report conclude that over a four-year period (2010-2013) green house gases associated with NYC building energy has decreased by 8% and energy use by buildings has decreased by 6%.  They cannot resist suggesting that NYC’s energy benchmarking program can take credit for this reduction.

My analysis of these data show the savings is only half this amount. The other half of the claimed savings is an artifact of the EPA’s having lowered its national, site-to-source energy conversion factor for electricity in Summer 2013.  The same mistake was made by the Washington DC Department of the Environment a year ago.

NYC does not live in a vacuum.  Over the last 10 years expanded use of natural gas and retirement of coal plants has cleaned up the entire U.S. electric grid — of which NYC is a part.  In fact, the purchase of fracked natural gas from Pennsylvania (fracking is outlawed in NY State) is the primary driver of reduced green house gas emission in NYC.  It has little to do with NYC building policies!

The NYC analysis apparently comes from adding up the annual greenhouse gas emission and weatherized source energy use of some 3,000 properties that submitted benchmarking data for all four years.  Using 2010 figures as a baseline the relative annual reductions for these selected properties are graphed below.

report figure 1

Here I want to focus on the source energy curve.  As compared with 2010, energy use went up slightly in 2011, then dropped by nearly 4% in 2012 and another 2.5% in 2013.  The drop in 2012 is easy to understand — hurricane Sandy brought the City to a grinding halt affecting tourism and many operations.  This reduction in energy use should be viewed with great skepticism.  But the continued reduction into 2013 seems like a sign of increased energy efficiency.  Or does it?

Until 2013 the EPA used a site-to-source energy conversion factor for electric energy of 3.34.  In summer 2013 the EPA adjusted this number by 6% to 3.14.  When it generated the 2013 report for NYC it used this reduced site-to-source energy conversion factor.  In other words, the 2013 reduction in NYC’s weather normalized source energy has little to do with building operation and everything to do with the EPA adjusting source energy down for the entire nation!  And this reduction does not reflect the single year improvement in the electric grid.  The EPA made no adjustment to this factor for many years prior to 2013, then in 2013 made a one-time-adjustment to reflect a 5-year average.

The NYC report is based on confidential data — no public benchmarking data were released for 2010.  Nevertheless, I can mimic the analysis by looking only at public NYC benchmarking data for 2011, 2012, and 2013.  In these data I find about 1200 buildings that reported energy data for each of these three years. About 1000 buildings remain after removing any that have questionable data for any of these three years (i.e., site EUI >1000 or <10 kBtu/sf).  The total weather normalized source energy for these buildings is graphed in blue below for each of the three years.  This graph mirrors the trend displayed in the NYC report.  The total site energy for these buildings is graphed in red.  The change in site energy matches the change in source energy for 2012 but not for 2013.  This confirms what I have explained above — that the EPA’s changing site-to-source energy conversion factor for 2013 is responsible for most of the change.  The graph below shows that 2013 site energy was actually higher than 2012 site energy.  It did not go down at all.

relative-energy-savings-scofield

The simple fact is that over the three year period shown below the site energy use of these 1000 buildings went down by only 3.5% — a figure which is highly uncertain given the sample size.  The 6% energy savings claimed by the Mayor’s Office is obtained through faulty analysis.

 

Energy harvesting — the siren’s allure

My wife, Deborah Mills-Scofield monitors dozens of media outlets and forwards articles to me that might be of interest.  One recently came my way about an effort in Portland, ME to harvest hydroelectric energy from its water pipes.  A company, LucidEnergy, has developed turbines that can be installed for this purpose.  The basic idea is to capture free energy in municipal water pipes that would otherwise be wasted.

While I applaud such innovation and creativity, I find the effort is misplaced.  I predict these turbines, like solar panels of the 1970’s and green roofs of this last decade — will soon be removed and abandoned.  This kind of energy harvesting is a fool’s errand.

About a decade ago I learned about another energy harvesting project in Israel — to install piezo-electric tranducers in highways to capture energy from passing trucks.  As heavy vehicles passed over these tranducers the truck weight would cause the transducers to compress and produce electricity.  The promoters of this energy argued that normal road compression represented lost energy — their technology would capture energy that would otherwise be lost.  The installed transducers did, in fact, produce electricity.  But I am confident that careful analysis would show that this energy comes from slight increase in fuel consumption of the vehicles that pass over the transducers.  Highway rolling resistance is mostly due to compression of the tires, not the road surface!

I am not aware of any evidence that water passing through municipal pipes arrives at end destinations with excessive kinetic energy.  Therefore any energy harvested along the way is likely to have to be re-injected by pumps.

And the maintenance issues must be significant.  I envision a few years of testing at the end of which it will be concluded that the cost of maintaining these units far exceeds the value of the energy they generate.  And what about the maintenance of pipes which get plugged due to low flow velocity?

Nature has handed us sunlight, wind, and hydo energy.  Harvesting these abundant resources is proving to be a challenge.  Harvesting efforts should focus on these well-understood and low-maintenance options.

Humans clearly waste a terrific amount of energy.  And there are many different ways that this wasted energy might be harvested.  The problem is cost-effectiveness.

 

 

San Francisco PUC Building not so green

SFPUC photoThe San Francisco Public Utilities Commission Administration building, constructed in 2012, has been billed as the greenest office building in North America.  Yesterday the San Francisco Examiner published an article which suggests the declaration was a bit premature.   According to its author, Joshua Sabatini, the $202 million dollar, LEED Platinum building has not performed up to expectations.  The building included integrated photovoltaic panels and wind turbines — enough to provide 7% of the building’s energy (not sure if that is total energy or just electric energy).  The energy produced by the wind turbines was never metered and the wind turbines have already been decommissioned; the company that installed them has filed for bankruptcy.  While the PV panels are reported to have satisfactory performance the inverter room was over-heating, requiring the installation of an auxiliary cooling system.  We will have to take the SFPUC’s word for this result as nowhere can I locate specific information about the expected PV electric generation.  It is so much easier to control the story when you don’t share the facts.

But Sabatini’s article does not discuss the energy performance of this building which is also rather disappointing.  According to 2014 energy benchmarking data published by San Francisco for municipal buildings the 277,511 sf SFPUC building had a measured site EUI of 54 kBtu/sf, just 10% lower than the mean for SF office buildings (60 kBtu/sf).  This is hardly the 32% energy savings claimed on the sfwater.org web site.  Moreover, the source EUI for this building is 153 kBtu/sf, which is 10% higher than the mean for the other 38 municipal office buildings whose 2014 energy data were disclosed.  This “greenest office building in North America” uses 10% more primary energy than used for other municipal office buildings — most of them constructed many years ago.

In other words this LEED Platinum building, the greenest office building in North America, uses 10% more primary energy than its counterparts in the San Francisco municipal building stock.  Sounds like a real winner.

Previously in 2009 I found that LEED-certified office buildings demonstrated modest (about 10%) site energy savings but, owing to their greater reliance on electric energy, demonstrated no significant source energy savings.  The result for the SFPUC building is even worse.

2012 CBECS show building energy use up from 2003

Last week the U.S. Energy Information Administration (EIA) released summary energy use data from its 2012 Commercial Building Energy Consumption Survey (CBECS).  The EIA reports that, as compared with 2003 results, the energy use intensity (EUI) for all U.S. commercial buildings has decreased by 12%.  They also report that for office buildings and educational buildings EUI have decreased by 16% and 17%, respectively.  These numbers, taken at face value, would appear to be encouraging.

But dig a little deeper and you find there is not much to celebrate.  The first thing to note is that mother nature does not care about energy use intensity.  This is a man-made metric for comparing energy use between buildings of different size. What really matters is total green house gas emission and total fossil fuel consumption.  To arrest global climate change, or at least to stabilize it, will require a global reduction in annual green house gas emission.

The 2012 CBECS data show that the total gross square footage (gsf) of the U.S. commercial building stock has expanded by 21% since 2003.  Its total (site) energy consumption has expanded by 7%.  That’s right — U.S. buildings are using more (not less) energy.  During this same time the U.S. population grew by 7.6%.  If world energy consumption and green house gas emission continues to grow with world population we are doomed!  Energy use in undeveloped countries will grow much faster than population as they increase their standard of living.  This growth is especially notable in India and China.  Developed countries like the US — which already use 5X-10X more energy per capita than non-developed countries — must decrease their energy consumption and green house gas emission.  Yet the U.S. is not even holding steady.

The above figures are based on site energy — not primary or source energy which is what really matters.  Building source energy — which includes the off-site energy use associated with energy generation and transportation — is a better indicator of primary energy consumed by buildings.

I have made crude source energy calculations based on the 2012 CBECS summary data and find that for all U.S. commercial buildings source EUI decreases by only 7% and source EUI for offices and educational buildings decreased by 12 and 13% respectively.

But again, what matters is total primary, or equivalently, source energy consumption.  When you combine these figures with the 21% growth in building gsf you find that the total source energy for all buildings increased by 13% — faster than the rate of population growth!  For offices and educational buildings the increases in source energy were 15 and 8%, respectively.  For offices that is double the rate of U.S. population growth and for educational buildings it is about the same as population growth.

2003 to 2012 is the decade of ENERGY STAR and LEED building certification.  These programs both provide cover for building owners to “feel good” about their ever-growing buildings that consume more energy and produce more green-house gas emission — yet are judged to be “green” and “energy-efficient.”  Proponents of these programs will claim that, while their accomplishments are disappointing, things would be far worse if these programs and their goals did not exist.  I doubt the truth of this assertion.  There is no evidence that ENERGY STAR and LEED-certified buildings are performing any better, on average, than other commercial buildings.  These programs are pretty much a distraction from the important societal goals to reduce green house gas emission.

The 2012 CBECS data also put the EPA’s claims that ENERGY STAR benchmarking is saving energy into perspective.  In 2012 the EPA published marketing literature which claimed that 35,000 buildings that used Portfolio Manager to benchmark for the consecutive years 2008, 2009,, 2010, and 2011 demonstrated a 7% reduction in source EUI over this same time period.  The analysis is sophomoric because they literally average the EUI for these 35,000 buildings rather than calculate their total gross source EUI (as does CBECS) which is the sum of all their source energy divided by the sum of their gsf.  It is entirely possible that the gross EUI for these buildings did not decrease at all while their average showed 7% reduction. The 35,000 buildings in the EPA study is dominated by office buildings — by far the largest set of buildings that use their benchmarking software.  Hence their claim of 7% reduction in source energy over the three year period must be seen in a context in which all U.S. office buildings saw a reduction in source EUI of 12% over a 9 year period.  There is simply little reason to believe that buildings that benchmark perform any better than those that don’t.

Once again real energy performance data cast doubt on energy savings claims for U.S. buildings.