#3 Clean Power Plan Assessment

Posted by David on Jun 16, 2014 in Market Insights, Power, Renewables | 0 comments

Let me note a couple points of reflections from my last review of the Clean Power Plan before I proceed with the next portion of the plan.  The choices made by human civilization over time typically revolved around resources.  Certain groups became experts at their region and learned how to extract and use their resources (e.g. Coastline habitats typically became expert fisherman and trades people).  The US unlike many other nations is a large conglomerate of vast and different regions.   For the most part, the US respected the states’ rights, and each state grew to maximize their resources without much force to do it one cerain way.  Renewable generation is not a universal accessible.  There are regions that clearly will have better performance in certain renewable generation (e.g. Solar – Arizona, Wind – West Texas, etc…).  The EPA tried to balance that by using the state RPS programs.  However, the state RPS programs became a political tool rather rooted in economics and science.  To substantiate that point, many RPS programs offer an escape clause (e.g. Alternative Compliance Payment) so the politicians can take credit for promoting without having necessarily to commit. This made it much easier for some to pick catch phrase policy such as 20 by 20 (20% renewable by 2020). 

To have solar mandates greater than states such as Arizona, in the end, offers a huge subsidy to those states with high solar intensity.   Natural economic evolution would produce solar cost savings and technology improvements driven from states such as Arizona, which would then roll those gains into less sunny states.  Arizona 2012 average retail rate ranks 19 out of the 50 states at 9.71 cents/kWh.   The top state is Hawaii – another very sunny state who is limited in resources and whose rate averages 31.59 cents/kWh.  If solar was so easy and economical, these states would be far ahead of their current levels – Hawaii less than 0.5% and Arizona slightly under 2% as percentage of total energy in 2013.  Obviously, there are some economic advantages of being able to build and design effective solar technology to export to areas of need.   To extract this value, it does not necessarily require the host state to have policies exceeding other states.  A difference of 10% capacity factor (12% to 22%) can produce a swing of over 10 cents/kWh.  I mentioned all this to point out the concern that EPA used the state RPS program as their guide to the level of renewable.  However the economics and science to these RPS programs may not be reality, as politics can defy reality.

The final recommended Best System of Emission Reduction (BSER) from the EPA in the Clean Power Plan is “4. Reducing emissions from affected EGUs in the amount that results from the use of demand-side energy efficiency that reduces the amount of generation required.”  This is the 3rd  most impactful out of the 4 programs in terms of reducing CO2 rates.

I have worked and reviewed many demand-side energy efficiency programs.  I had the opportunity to work with the Northwest Power and Conservation Council (NWPCC) and review their data, which is impressive.   Demand-side energy efficiency programs should be evaluated as a resource.   I have helped many utilities in enabling their power models to do this.  Unlike the other 3 BSER, this one is very dependent on human behavior, and because of that, much more detail and thought needs to be examined.  EPA did not go into detail.  “We have not assumed any particular type of demand-side energy efficiency policy.”

The issue with demand-side energy efficiency program can be summed up with EPA’s own words “Regardless of how the energy savings of an energy efficiency measure are determined, all energy savings values are estimates of savings and not directly measured”  EPA spent much time talking about evaluation, measurement, and verification (EM&V) industry given the reliance on estimates.   The problem I have noticed here is we have an industry that has grown significantly from $1.6 billion in 2006 to $5.9 billion in 2011 and projected to be over $8 billion per the American Council for an Energy-Efficient Economy.  As with all industry that grows that quickly there will be growing pains.   The first one that comes to mind is that there are certain companies who are in all three spaces,  Evaluation, Measurement, and Verification.   You can see there are many companies who evaluate in one state and verify in another.   This should be unacceptable practice and the commissions need better oversight of these companies.  Too many incentives exist to support the ever growing DSM-EE industrial complex regardless of actual results when this happens.   It is important that there are checks and balances in the EMV space to minimize these practices.

The goals set forth by EPA are done so by assuming a best practice standard for each state and then targeting that rate.  “For the best practices scenario, we have therefore estimated that each state’s annual incremental savings rate increases from its 2012 annual saving rate to a rate of 1.5 percent over a period of years starting in 2017.”  I am sure this is conservative for many states, but at the same time I expect just as many, if not more states, to have a much harder time hitting target.  Based on their spreadsheet, by 2030, demand-side energy efficiency programs will total 380,569,493 MWh.  To put that number in perspective, this is more energy used by the state of Texas, state of California, or the United Kingdom.  Using the average retail rate of electricity of 9.9 cents/kWh – this would amount to over $38 billion dollars a year “wasted” by society.  It is an astronomical number to imagine that society would be that inefficient on a business as usual path. 

It is true, that as whole, there are energy savings that an individual consumer could not realize or value without a collective saving mechanism. The difference can typically be traced down to the value of capital and the fact that a personal decision is not always economically rationale as other factors such as feeling good, to peer pressure, are very hard to economically quantify.  In these cases, programs can be developed to add more value to savings to even nudging the consumer to act good for the whole.

The extrapolation from one state to another state needs to be carefully balanced given the human connection to these programs.  As I noted before, DSM is a detailed process since it focuses in on what your customer uses energy for.  If your customer uses heat pumps to stay warm as their primary energy usage, implementing a large light bulb program will only get you so far compare to places like California.   As weather becomes more temperate, it is easier to modify behavior since human life is not harmed.   However in extreme cold or heat, energy efficiency becomes limited.  The successful California experience in energy efficiency just cannot be extrapolated one for one to other states.

Programs do naturally have a natural end life.   As a simple example, consider the conversion of lighting.  It eventually ends.  In fact, the big gains end quite soon, as you think about where and how you use lighting.   Eventually the incremental lighting updates occur in less used areas such as garages to closets.  The initial lighting change will be in the most used area, but the incremental change much less so.   An extrapolation of those impacts needs to be carefully considered.  Many EMV companies understand this so it is worrisome to extrapolate savings for so many years.

Let me pause here before I go into a can of worms in dealing with cost and benefit.

If you need help in designing and modeling your DSM programs I can help you.  In addition if you need a third party to help discuss with regulators and commission your decision criteria for DSM, I can also assist in this.

Policy discussions can be beneficial when coming from a factual context without significant biases or agenda.  There is no doubt in my mind policy can be an effective tool in producing positive societal benefits – it is all in the design, implementation, and regulation.

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