For the original energy investigation go to:
With the recent release of the McKinsey and Company report, “Unlocking Energy Efficiency in the U.S. Economy” regarding the total efficiency potential for energy savings and emission reduction in the United States, it would prove useful to apply information obtained from this report to the previously analyzed issue of electricity shortfalls when meeting the current emission standards set forth by the ACES.
The McKinsey report hypothesizes a maximum savings of 9.1 Quadrillion BTUs (2.667 billion MW-h) of total energy if all of the efficiency projects proposed are successfully undertaken and completed.1 These efficiency savings are estimated to reduce annual CO2 emissions by up to 1.1 to billion tons (gigatons).1 From that total approximately 40.87% of those savings are from the electricity sector. Most of the remaining savings are somewhat inconsequential from an electricity standpoint due to the fact that they are derived from sectors that are capped under the ACES, therefore, those reduction would occur anyways. The only real advantage in these sectors, but it is a big one, is increased efficiency will involve significantly lower costs than other reduction mechanisms. One could argue that efficiency also has an advantage in speed of reduction (overall emissions are reduced faster through efficiency measures instead of other avenues), but the overall significance of this speed would only account for at a small elimination of future atmospheric CO2 concentration.
The total savings from electricity can be divided into two different sectors, those that influence the down-slope of demand and those that influence the up-slope of demand. The down-slope of demand refers to total reduction in electricity use by existing infrastructure. The reason the term ‘down-slope’ is utilized is because the electricity curve itself is flipped with the application of efficiency, instead of going up it begins to go down. The up-slope of demand refers to the total reduction in electricity use required by future infrastructure. The reason the term ‘up-slope’ is utilized is because electricity required by future buildings at best can only be reduced to 0 MW-h (if all of the electricity is provided by a self-generated non-emitting source), but it is improbable to conclude that all future infrastructure will meet this condition. Therefore, no matter how great the efficiency improvement to the new buildings, there will be an increase in electricity demand; efficiency cannot change the direction of the demand slope for new infrastructure, it can only reduce the slope of the increase.
So assuming that all of the efficiency alterations are deployed by 2020 as suggested by the McKinsey report, it would result in a total savings of 1,020,000,000 MW-h on the down-slope of demand and 70,000,000 MW-h on the up-slope of demand. Note that assuming all efficiency alternations it is a very improbable assumption as pointed out by the McKinsey report, the breadth of the improvements cover over 100 million buildings of private, local, state and federal level and billions of appliances and electronic devices. Thus, this upper limit proposed by the McKinsey report must be regarded as the best possible, albeit remarkably unlikely scenario. However, even if this is the best-case scenario the probability of its occurrence at this point in time is so unlikely that it cannot be seriously projected. Instead it can be viewed as a target point for savings from all existing infrastructure to be attained at some point in the distant future. 50% of this best-case scenario was assigned as the 2020 efficiency and was applied to the current model. The point of this update is to identify how this 50% best-case scenario would influence the required electricity growth in trace/zero emission and natural gas providers instead of based efficiency savings on projected electricity estimates.
The only major change is the incorporation of the proposed electricity reduction due to efficiency upgrades. The 2007 to 2020 electricity demand curve remained the same as in the previous study with the addition of the predicted up-slope demand from McKinsey subtracted from each scenario. The 2020 to 2030 electricity demand curve was divided into the low, medium and high scenarios estimated by the EIA, similar to the previous study, with an additional 12% reduction, pertaining to the percentage of total electricity reduction in the total energy reduction. Basically because only 50% of the maximum efficiency reduction was assumed for existing infrastructure leading to 2020, the 12% is representative of further efficiency deployment in the existing infrastructure. All other assumptions and details not directly pertaining to efficiency remain the same as described in the advanced energy gap model posted here:
The results from the 2007 to 2020 analysis are shown below.
Obviously there are significant reductions in both natural gas growth rates and rates of coal loss due to the reduction in electricity demand brought on by efficiency increases vs. most of the results from the percentage efficiency investigation. In fact the reduction in electricity demand is so great when considering a low expectation demand increase and when utilizing 06-07 renewable growth rates that no natural gas increase is required to bridge the gap created by the loss of coal. Instead the coal loss comes straight from the reduction in electricity demand instead of the direct need to adhere to the emission cap. This result may initially be surprising as even if the entire reduction portfolio described in the McKinsey report is executed, the 2020 emission cap is not obtained, so how can only execution of ½ of that portfolio meet the cap? Recall that emission reduction is not solely attributed to the realm of electricity, but reductions will come from other capped industrial sectors and the transportation sector. Also the coal values are slightly smaller than can be attributed to the reduction in electricity demand because there is a natural transfer from coal to less emission intensive electricity providers that exists outside of electricity demands.
The results from the 2030 analysis are shown below.
One may suggest that the wind growth rate in a given situation can be reduced by increasing the natural gas growth rate because of the reduced electricity demand. However, this is not plausible because recall that in the model coal derived electricity production falls to 0 by 2030, thus there is no coal to neutralize the increase in emissions generated by natural gas. Overall by 2030 when not using excessive amounts of offsets, the emission cap becomes the limiting factor determining electricity production, not electricity demand.
Using the previously predicted renewable growth rates and transportation emission reductions in conjunction with the efficiency deployment of this investigation, the results for the 2020 and 2030 analysis are:
Unfortunately the sad state of affairs is that even though only ½ of the total prospective savings projected by the McKinsey Institute was applied for this study, that result is still relatively improbable. The question comes down to why does it appear so difficult to do something society knows how to do and it would be rational to do?
Aside from obvious informational issues (how to go about increasing efficiency in the first place), there are two main obstacles to increasing energy efficiency in the existing residential sector. First, the payback rate is rather slow, especially for those that do not use a lot of energy. The payback rate is dependent on the total amount of energy used, but the costs associated with applying the new efficiency measures are relatively fixed. Therefore, increasing energy efficiency is not very attractive to those that do not use a lot of energy because a 500-5,000 dollar investment may take over a decade before breaking even and may not make more than 5,000-10,000 dollars over the lifetime of the house. Also the investment depends on remaining within the improved residence for a significant period of time to recoup on the investment. The lifespan of the house vs. the payback rate is a significant problem. Although it is good for the planet, as a means to make money the slow rate of return reduces incentive.
The above obstacle can be best illustrated in the following example. Suppose Person A offered Person B either 1000 dollars right now (the investment for increasing energy efficiency Person B’s home) or 150 dollars per year over 10 years (the savings from the increased energy efficiency of Person B’s home), which offer has the higher percentage of acceptance by Person B? If psychological behavior from lottery winnings, (a very similar situation), reveal anything, Person B would select the first option an overwhelming amount of the time. The problem is although the second offer yields more money, the time required for its allocation makes it seem smaller. Also the 1000 dollars is concentrated which allows an individual more versatility in how it is spent, whereas the 150 dollars per year has limited options.
Second, the overall ability or incentive to make efficiency changes is an obstacle. This obstacle can be divided into two parts. First, for the wealthy the prospect of saving money through efficiency changes typically does not seem worth the investment or the aggravation involved in the installation of the new infrastructure. Rather it is easier to pay the extra 300-1500 dollars per year in energy costs than to go through the hassle of buying new appliances, installing new insulation and other home improvements. Second, for the less wealthy the prospect of saving money through efficiency changes may not be viable because of inability to afford the fixed price of making the change. Unfortunately the slow rate of return also hurts lower income households when it comes to efficiency changes because it limits the ability to make piecemeal changes using the money saved from one improvement to fund a second efficiency improvement and so on. Another concern for lower income households is the aforementioned total profitability in that it is reasonable to conclude that most lower income households do not use a lot of energy because they cannot afford to do so, both due to limited allocation of energy funds and the lack of funds to create three television, two computer and cappuccino maker homes, which would demand more energy. Thus, with lower energy use not only is the total rate of return slowed, but so is the total amount of money that efficiency investments will yield.
Although this low energy use may not so cut-and-dry because it is plausible to suggest that some lower income household unwittingly use more energy than some higher income households due to inefficiencies in heavily outdated appliances and other electrical items due to cost constraints. Overall in the long-term energy efficiency is definitely viable, but there must be considerable personal motivation to pull the trigger, basically one must care about the environment over any financial incentives. Unfortunately it is likely that those that have such a mindset and have the proper information regarding how to apply these efficiency measures have already done so, limiting the total viability for future changes. Therefore, unless the government steps in and directly or indirectly funds efficiency programs at a greater level of both capital and awareness, it is highly unlikely that a significant amount of efficiency savings will come from the existing residential sector. It is currently unlikely that any other methodology to drive efficiency incentive will work despite efficiency improvements actually being cost negative.
It is highly probable that the greatest level of success in applying increased energy efficiency will come from the commercial sector. The two biggest reasons for this anticipated success is first a greater anticipated rate of return due to shear energy use and second less total unique units that have to be improved. The first reason is important because a faster rate of return not only provides a greater incentive to initiate the improvement, but also allows for a greater ability to work from a piecemeal methodology, thus reducing the initial capital expenditure required for an increase in efficiency. However, due to area constraints, it is highly probable that initial costs would also be higher for commercial infrastructure. For example instead of 1000 dollars now or 150 per year for 10 years, the proposal would be 1200 dollars now or 210 per year for 10 years. The second reason also relates to the higher energy use in that to save x MWh one may have to apply efficiency improvement to 26 homes vs. 1 commercial building [based on the total divergence of efficiency changes that are available].1
The future of the residential and commercial sectors is a different beast entirely largely because of the new federal guidelines that exist in the ACES. If passed as is, the ACES would set national standards for both future residential and future commercial buildings, which would eliminate the problem of incentiving, for the efficiency improvements would be incorporated before sale. The prescribed efficiency codes are documented in Section 201 of the ACES.
The ACES proposes initial baseline standards correlating to the efficiency requirements in the 2004 ASHRAE Standard 90.1 and 2006 International Energy Conservation Code (IECC) code for the commercial and residential sectors respectively. Although some seem to unrealistically believe that all the DOE has to do is snap its fingers and new policy will both be enforced and executed, this is hardly the truth. Clearly there will be some delay between both the date of discussion and agreement and the date of agreement and enforcement. For example a 30% reduction from the baseline is supposed to be the target set immediately after the passage of the ACES. However, enforcement will not begin immediately despite the target being law immediately. Instead it will take anywhere from 1 to 2 and a half years before one can expect 100% of new buildings to abide by the new target code. The reason for this delay is that under subsection c: State Adoption of Energy Efficiency Building Codes – states could drag their feet for up to a year before enforcing the standards put forth on a given target date under Section 201. Also there are questions regarding enforcement issues on a national level and how they transfer to this one-year state grace period (is it consecutive or concurrent?). Thus, it is easy to overestimate the amount of energy saved from new buildings under these guidelines. [Note that this issue does not pertain to the estimates made by the McKinsey Report referenced above because they do not appear to include policies put forth by the ACES in their analysis.]
The biggest problem stemming from improving the energy efficiency of new buildings is that these improvements typically increase the capital costs associated with constructing the buildings, thus forcing the builders to increase the selling price. Price gouging due to forced inclusion from legal standards could account for an additional unanticipated increase in price. For example suppose the new regulations demanded an additional 50 square feet of insulation be installed in all new homes from currently existing standards to meet the new energy reduction standards. It is too idealistic to believe that insulation manufactures and provides will not gleefully raise their price in response to the greater required demand. These prospective price increases will then make most affordable housing less affordable. Therefore, the issue of increasing new home and other commercial building prices due to improved energy efficiency infrastructure will have to be addressed.
Overall this new addendum to the previous energy study illustrates both the benefits of increasing efficiency deployment, the pertinent obstacles to deploy a significant efficiency program to achieve these benefits and the fact that despite the benefits of efficiency, trace/zero emission technologies will still require a significant amount of growth for future energy demands. The biggest issue in aiding efficiency savings involves the development of an incentive type program that does not involve the government directly footing the bill. The problem with the government footing the bill is that due to the economic downturn, the national debt is already set to spike and further handouts for things individuals should already be doing is unacceptable. Ideally a price signal involving the increase in electricity price would serve as the proper motivating factor; however, Congress appears determined to limit any significant change in price signal in the short-term. Therefore, the best option would most likely be specifically targeted very low interest governmental loans given for the purchase of improving efficiency. Hopefully individuals and corporations can push forward in the pursuit of higher efficiency goals reducing the already daunting future requirements for electricity and energy generation under a future emission cap.
1. "Unlocking Energy Efficiency in the U.S. Economy." McKinsey and Company. July 2009.