Electricity Pricing—Fair Trade vs. Free Trade—Which is High/Lower

When I got married in 2004, my wife introduced me to the term “Fair Trade” as in fair trade coffee, where coffee growers are paid a price that allows a “living wage” to be paid to the workers on the coffee plantation where the coffee beans were grown.  I quickly realized that Fair Trade could be used to describe the standard regulated electricity market, including a fair rate of return to the investors.  In contrast, the term Free Trade could be used to describe a competitive market, such as the ones then being developed by Independent System Operators (ISOs).  Free Trade could also be used to describe the bulk power markets between large vertically integrated electric utilities, such as when my former employer American Electric Power (AEP) sold electricity to other utilities, whether Commonwealth Edison to its northwest or TVA to its south.  However, both these Free Trade examples have some aspects of Fair Trade, as has been shown by regulators intervening in the Free Trade markets when prices have appeared to be excessive, such as the imposition of caps on the ISO markets.

 

In 1978, the Federal government implemented a mixed form of Fair Trade/Free Trade for Qualifying Facilities, requiring many utilities to buy electricity at Avoided Cost under the Public Utilities Regulatory Policy Act (PURPA).  In 1984, Ernst & Whinney, my employer at the time, won a contract with the Texas Study Group on Cogeneration to investigate the way Houston Lighting & Power (HL&P) was paying (or not paying) cogenerators for the electricity that was being produced.  I invented the Committed Unit Basis[1] (CUB) for evaluating long term contracts under which utilities bought power from cogenerators.  CUB was adopted by name by the Texas Public Utilities Commission in its regulations and was used to determine the reasonableness of three large cogeneration contracts that HL&P signed over the next year.

 

CUB develops an inflation adjusted annual revenue requirement for the next generating unit that the utility would build were it not for the presence of the cogeneration plant.  The inflation adjustment results in economic depreciation rates, which could be negative in the first few years of the model.  Thus, not only did CUB reduce the first year payment to a levelized rate below the standard utility model for the revenue requirement, but the first year payment was below even that levelized rate.  The payment escalated with inflation over the life of the contract.

 

I saw HL&P sign three major contracts in 1984/5 based on CUB.  My analysis suggested that the second and third contracts were for rates that were successively lower than the first contract.  Some suggested that the lower rates reflected the loosening of the market for electricity.  The first contract reflected the full value identified by CUB, while the subsequent markets reflected competition, effectively going from a Fair Trade price to a Free Trade price.  When I subsequently addressed the concept of a competitive market for unscheduled flows of electricity, I concluded that sometimes the Free Trade price needed to be above the Fair Trade price, not always below the Fair Trade price.  This concern was included in the name of my model for a competitive market for electricity, WOLF, or Wide Open Load Following.

 

The Free Trade/Fair Trade issue comes up most starkly in the discussion of dispatchability, an issue that dramatically affects wind and solar generation.  They are not dispatchable and many argue that they should be paid a price that is lower than the price paid to dispatchable generators, such as gas turbines.  This lower price would be paid to any “as available” wind and solar (as well as many other forms of QF power, such as surplus cogeneration).  But sometimes, the “as available” power happens to occur when it is needed.  Should “as available, as needed” power always be paid a lower price than dispatchable power?  Should there be a way for “as available, as needed” power be made whole relative to the lower prices that they are paid during many of the hours when dispatchability is important?  How can that be done?

 

WOLF provides a price adjustment to reflect the concurrent need for power.  When load outstrips supply, the price follows the load upward above the standard price for scheduled power.  Conversely, when load is much below supply, the price follows the load downward below the standard price for scheduled power.  For electricity, the standard measure for whether load and supply are in balance on a utility is Area Control Error.  When the utility is synonymous with the entire grid, the standard measure for whether the load and supply are in balancer is frequency error.  Since both ACE and frequency error can be positive or negative, the price adjustment can serve to raise or to lower the settlement price relative to the standard price.

 

There are times when dispatchable generators fail to meet their obligations and the utility is able to meet its load because of the availability of non-dispatchable generators.  During such times, the value of the non-dispatchable generation is equal to the value of the dispatchable generators, perhaps even more valuable.  WOLF provides a way to set a price based on the value of “as available, as needed” generation.  When there is a shortage, the Free Trade price for “as available, as needed” generation should even exceed the Fair Trade price for dispatchable generation.



[1] Recently I googled “Committed Unit Basis” and had ten hits, including a paper written in Portuguese by Brazilian authors, but I had include the quotation marks to reduce the hits down to ten.

2012 Washington, DC, Area Storm Electricity Outage Duration

The Washington, DC, area was hit by two storms in 2012, each of which cause widespread electrical outages.  A derecho hit the evening of June 29.  Hurricane Sandy hit four months later on the evening of October 29.  I sent surveys to people on the mailing list of the National Capital Area Chapter of the U.S. Association for Energy Economics (NCAC-USAEE) for both storms asking for a reply about the number of hours they were without power.  (I experienced nine hours for the derecho and two hours for Hurrican Sandy.)  My “Derecho Outage Survey” was included in USAEE Dialogue, Volume 20, Number 3 – 2012.  Here I report on the outages related to Hurricane Sandy and compare the results to the outages related to the Derecho.

Table 1 replicates the form of Table 1 from my “Derecho Outage Survey.”  There were 93 survey responses, which I have summarized for five of the electric utilities in the Washington, DC, area.  I report the number of customers who reported an outage to me and the duration of those outages in hours.  I also include the number of customers who reported that their outage time was zero.  Many of these zeroes may have actually been an outage of a few seconds to a few minutes.  None of PEPCo’s customers in Washington, DC, reported an outage.   I note that 22 PEPCo’s customers in Washington, DC, did participate in the survey, though each reporting 0 hours of outage.

Figure 1 presents a cumulative distribution function for the outages, including separate plots for BG&E; PEPCo-Montgomery County; and VEPCo; as well as a plot for the combination of all of the outage data.  Each plot has a convex shape, showing a rapid increase in the number of customers who have been returned to service, with a gradual degradation of the response rate as time accumulates.

The phenomenon of a convex cumulative distribution function is often referred to as “low hanging fruit” or “the most bang for the buck,” reflecting the incentives and policies that utilities have to concentrate on returning the most customers to service as quickly as possible.  Thus, problems that can be resolved quickly for large numbers of customers are the first problems to be attacked.  The result is the rapid early increase in the number of customers who are returned to service.  Problems that affect individual customers are the last to be resolved, resulting in the plots turning horizontal as the outage duration time increases.

Figure 2 presents the cumulative distribution function for the outages of BG&E, comparing the outages for Hurricane Sandy with the outages for the derecho.  The plot for the four outages associated with the derecho does not have the convex shape described above.  But with only four outages reported, the distribution of reported outages has a greater chance of not being representative of the distribution of actual outages.

Figure 3 presents the cumulative distribution function for the outages of PEPCo in Montgomery County, comparing the outages for Hurricane Sandy with the outages for the derecho.  PEPCo took some 72 hours to restore half of the customers who had outages associated with the derecho compared to only 3 hours to achieve the same restoration level for outages associated with Hurricane Sandy.

Figure 4 presents the cumulative distribution function for the outages of VEPCo, comparing the outages for Hurricane Sandy with the outages for the derecho.  VEPCo took 40 hours to restore half of the customers who had outages associated with the derecho compared to only 12 hours to achieve the same restoration level for outages associated with Hurricane Sandy.

Figure 5 presents the cumulative distribution function for all the outages reported in the two surveys, comparing the outages for Hurricane Sandy with the outages for the derecho.  The utilities in the DC area took 55 hours to restore half of the customers who had outages associated with the derecho compared to only 9 hours to achieve the same restoration level for outages associated with Hurricane Sandy.

The DC area electric utilities were severely castigated by government officials for the length of time that restoration efforts took after the derecho.  Few comments were made about the restoration time in regard to outages in the DC area for Hurricane Sandy.  Some of the differential in the length of the outages associated with the derecho versus Hurricane Sandy relate to physical phenomenon.  Some relate to planning by the utilities.

The derecho occurred four months before Hurricane Sandy.  The derecho is likely to have toppled many of the trees that Hurricane Sandy would otherwise have toppled.  The utilities in the DC area also initiated a substantial tree trimming program after the derecho, further reducing the number of trees that would otherwise have been grist for Hurricane Sandy in causing outages. The derecho may also have had stronger winds.  Together, these items are reflected in the large increase between the two surveys in the number of responses that showed no outages.

At least one utility in the DC area, PEPCo, pre-positioned contractors before Hurricane Sandy, as I wrote while sending out the survey.

When my wife and I drove to church Sunday morning, I was impressed with the dozen or more bucket trucks sitting in the parking lot of the Gaithersburg Holiday Inn, thinking I should call the television stations as a potential story for them to film. I didn’t, but I was no longer impressed by yesterday’s sight when I saw Channel 4’s story today about noon from Gaithersburg, just across the street from the Holiday Inn. The Montgomery Country Fairgrounds seemed to have over a hundred bucket trucks, making the Holiday Inn parking lot scene look insignificant.

These pre-positioned contractors would likely have reduced the duration of the outages, just as the relative timing of the two storms, the tree trimming programs, and the relative strengths of the two storms likely contributed to the reduced fraction of customers who reported any outages and the increased fraction of customers who reported no outages at all.

Pre-positioning contractors comes with a cost.  The contractors I saw at the Holiday Inn were in the DC area two days before Hurricane Sandy hit.  Some of that time might have been non-productive.  Some of the time might have been used for additional tree trimming and other normal on-going work that utilities do on a routine basis.  Even the contractors shown on TV seem to have been pre-positioned a day ahead of time.  In contrast, the derecho was not anticipated and contractors generally travelled during the first day after the derecho hit instead of one or two days before Hurricane Sandy hit.