Pricing Gasoline When the Pumps Are Running on Backup Electricity Supply

I attended the MIT Club of Washington Seminar Series dinner on Tuesday, 2014 February 11, which this year is on the topic of “Modernizing the U.S. Electric Grid,” listening to Michael Chertoff talk on “The Vulnerability of the U.S. Grid.”

Chertoff’s maguffin was a story about a hurricane hitting Miami in about 2005.  Electrical workers couldn’t get to work because they had no gasoline for their cars.  The gas stations had gasoline but no electricity to pump the gasoline.  Back-up electricity generators would have required an investment of $50,000 which was not justified on the razor thin margins on which most gas stations operate.

The gas station owners thought process was that the sales lost during the blackout would just be gasoline that would be sold after the power came back on.  Investment in a back-up generator would not change the station’s revenue and would just hurt its profitability.  My first comment during Q&A was that the same issues were raised after Hurricane Sandy[1] in the New York City area in 2012, and perhaps in many other areas that experience wide spread storm damage.

After the dinner I talked with Matthew, a friend from ExxonMobil who had learned about the Seminar Series from my advertizing it to people who attend events of the National Capital Area Chapter of the U.S. Association for Energy Economics.  Because of that linkage, he makes a point to search me out at each Seminar Series dinner.  Our after dinner discussion focused on how to make the $50,000 investment in a back-up generator profitable to the gas station owner.

Matthew said that many gas station permits including anti-gouging provisions, preventing the gas station owner from increasing the price during emergencies.  My thought was that the investment in back-up power supplies would mean that a temporary price increase could be justified to pay for such an investment.  After all, bulk electricity prices in Pennsylvania on the PJM grid during the cold snap associated with the 2014 January arctic vortex soared to $1,839.28/MWH ($1.84/KWH) from an average of only $33.06/MWH during 2012.  This was a temporary 55 fold (not 55%) change in the base price of electricity.[2]

I believe that prices are sticky.  Once set, prices tend to stay unchanged for significant periods of time.  The independent system operators (ISOs such as PJM) get around some of this stickiness by having elaborate models for setting prices every hour, with the basic mechanism setting a value every five minutes and then averaging those five minute values over an hour to get a price.  The basic mechanism includes (1) bids by suppliers as to the price they want if they are to provide specified amounts of electricity and (2) estimates of the demands that will occur each hour or that are occurring on a real time each five minutes.

Almost 25 years ago, long before the advent of ISOs, I published my first article[3] on using the measured real time imbalance between supply and demand to set the real time price for unscheduled flows of electricity.  Using the measured imbalance eliminated the need for bidding processes, bidding process that can lead to stickiness.  I proposed using the concurrent system frequency for setting the price, calling the concept Wide Open Load Following (WOLF).

For electricity, a surplus of demand will drag down system frequency, which I say warrants a higher price, at least higher than the nominal price.  A surplus of supply will push up system frequency, which I say warrants a lower price, at least lower than the nominal price.  Over longer intervals, imbalances will change the accuracy of wall clocks that use system frequency to determine the correct time.  Thus, WOLF includes the concept of time error in setting the nominal price for electricity imbalances.  The WOLF concept could similarly be used to set prices within each of the five minutes of an ISO dispatch period, or even on a sub-minute basis, modifying the ISO’s sticky five minute nominal dispatch value.

The State of California has variable pricing for its State Route 91 Express Lanes under the rubric of congestion management.

“On July 14, 2003, OCTA adopted a toll policy for the 91 Express Lanes based on the concept of congestion management pricing. The policy is designed to optimize 91 Express Lanes traffic flow at free-flow speeds. To accomplish this OCTA monitors hourly traffic volumes. Tolls are adjusted when traffic volumes consistently reach a trigger point where traffic flow can become unstable. These are known as “super peak” hours. Given the capacity constraints during these hours, pricing is used to manage demand. Once an hourly toll is adjusted, it is frozen for six months. This approach balances traffic engineering with good public policy. Other (non-super peak) toll prices are adjusted annually by inflation.

“Recent customer surveys indicate that 91 Express Lanes users lead busy lives with many hours dedicated to commuting to and from their jobs. About 85 percent of customers are married, with more than half raising children. Many customers choose the toll road only on days they need it most, joining general freeway lane commuters on other days. Customers emphasize they value a fast, safe, reliable commute and the toll policy strategy is designed to support this value.

“The toll policy goals are to:

  • Provide customers a safe, reliable, predictable commute.
  • Optimize throughput at free-flow speeds.
  • Increase average vehicle occupancy.
  • Balance capacity and demand, thereby serving both full-pay customers and carpoolers with three or more people who are offered discounted tolls.
  • Generate sufficient revenue to sustain the financial viability of the 91 Express Lanes.

“The effect of the toll policy has been an increase in customer usage with sufficient revenue to pay all expenses and also provide seed funding for general freeway improvements. Revenues generated by the toll lanes stay on the SR-91 corridor, a significant departure from past practices. Under the previous owner’s agreement with Caltrans, a “non-compete” provision restricted adding more capacity to the SR-91 corridor until 2030. When OCTA purchased the lanes, it opened the door for new improvements on SR-91 by eliminating the non-compete provision.[4]

The free flowing capacity of the 91 Express Lanes is 3400 cars per hour.  When average hourly volume exceeds 3200 cars per hour (about 94.1% of the free flowing capacity), the price increases by $0.75 at the beginning of the next six months.  When average hourly volume exceeds 3300 cars per hour (about 97.1% of the free flowing capacity), the price increases by $1.00 at the beginning of the next six months.  When average hourly volume is less than 2720 cars per hour (80% of the free flowing capacity), the price decreases by $0.50 at the beginning of the next six months.  The flow analysis is done for each hour of the week, producing 168 distinct prices each way on the 91 Express Lanes, that is, for 24×7 distinct hours each way.  But as of 2013 July 1, about 1/3 of the hours are charged the minimum price, that is, they are not considered to be super peak hours.   The flow analysis also is separately done for holidays, nominally as minor as Mother’s Day.

The 91 Express Lanes toll mechanism shows that some jurisdictions, including the notoriously protectionist State of California, allow incentive pricing for congestion management during critical periods, such as a wide spread blackout.  The 91 Express Lanes toll mechanism also provides a mechanism for automatic adjustment of the  price.  The 91 Express Lanes toll mechanism uses explicit measurements of the balance between supply and demand, much like the WOLF mechanism for electricity imbalances.  The 91 Express Lanes measurement is the fraction of the capacity of the 91 Express Lanes, changing the price when the hourly utilization is outside the band of 80.0% to 94.1%.

Based on a review of the 91 Express Lanes toll mechanism, there is some hope that gas stations will be able to afford the major investment in backup electrical supplies.  For gas stations, the measure of the imbalance between supply and demand can be as simple as the length of the line of cars waiting for gas or as complex as including the gasoline inventory compared to the desired level and the estimated time before the inventory is extinguished.



[1] Presentation of Adam Sieminski, Administrator of the U.S. Energy Information Administration at the 2012 October 19 lunch of the National Capital Area Chapter of the U.S. Association for Energy Economics (NCAC-USAEE.org).  Pursuant to its charter as an information agency, EIA created for Hurricane Sandy a real time display of gas stations with internet connectivity, a nominal measure of whether the gas station had electricity.

[2] PJM differentiates prices geographically.  Thus, one local price increased to $2,321.24/MWH and another fell to a negative $391.14/MWH because of transmission constraints.

[3] “Tie Riding Freeloaders–The True Impediment to Transmission Access,” Public Utilities Fortnightly, 1989 December 21.

[4] https://www.91expresslanes.com/policies.asp

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.