Electricity auctions: Why didn’t I think of that?

Congratulations to Stanford Professors Robert Wilson and Paul Milgrom, who have been awarded the The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2020 “for improvements to auction theory and inventions of new auction formats.” Their work has led to numerous innovations in the use of auctions, including allocation of radio spectrum and, for my purposes here, the organization of electricity markets. Without their research, we would not have offer-based wholesale electricity markets.


I am reminded how I struggled during my PhD during the late 1980s with the problem of eliciting information from market participants for use by an electricity system operator in dispatching the system. The classic book by Schweppe, Caramanis, Tabors, and Bohn (Spot Pricing of Electricity), which introduced the idea of spot markets for electricity, was coy about how this information would actually be gathered from market participants to dispatch the system. 

I did not know it at the time, but economists such as Wilson and Milgrom were already thinking about using an auction to elicit this market information by straightforwardly asking the market participants to provide offers to produce and bids to consume. These offers and bids could then be incorporated into the existing engineering concepts such as unit commitment and economic dispatch by re-interpreting the cost functions used in unit commitment and economic dispatch to be the offered costs from market participants (or the bid benefit of consumption from representatives of load). 

This online auction format of offer-based unit commitment and dispatch was a key part of enabling the system operator-based electricity markets we take for granted, marrying the economic insight of using an auction with the engineering realities such as transmission constraints, unit commitment, and economic dispatch. In retrospect, it might seem obvious to use an auction, but no one did, until Wilson and Milgrom. Applying auctions to electricity trading was the game-changing connection.

So, I wonder, why didn’t I think of that?

If I may make an observation: We engineers have dependable technical skills. We are great at working through the math. But we can be a little slow to see the creative possibilities. Economists, for their part, appear to reach for new applications more intuitively. (Sometimes, maybe, an overreach.) And the best of the best, like Milgrom and Wilson, powerfully harness both sides of the technical/creative equation.

How can the rest of us aspire to that ideal marriage of technical prowess and creative spark?

It’s obvious but important to stress: We engineers need to leave the silo if we are to have any hopes of developing integrated insights. Today, everything is inter-disciplinary. In the context of electricity markets, for example, I recommend books by economists (such as Steven Stoft’s Power System Economics) to engineers and books by engineers (such as Kirschen and Strbac’s Fundamentals of Power System Economics) to economists.

Join me in congratulating Professors Wilson and Milgrom for their Nobel Prize. Their work inspires us all to think beyond traditional borders.

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Is demand side the way to go??

Because wind and solar production depends on weather conditions, it is subject to the variability and intermittency of weather. The challenge of renewable integration is to cope with the resulting variability of the “net load,” or total load minus intermittent renewable production. (Click here to read my blog post on the duck curve.)

Chemical batteries are often proposed as a solution for variability, and they do seem to be roughly competitive at wholesale in the supply of ancillary services (services additional to energy that are required for reliable operation of the electricity system). Chemical batteries are cost-competitive for the ancillary service of frequency regulation and possibly for managing contingencies. Frequency regulation and contingency services maintain supply-demand balance in the very-short-term to the short-term (in the seconds-to-tens-of-minutes time scale). 

However, broadly speaking, chemical batteries are not currently cost-competitive for storage of renewable electricity to match supply and demand at longer time scales of hours to weeks, given current wholesale electricity prices in most systems worldwide. Although chemical battery storage may eventually be cost-effective for medium-term storage, current costs imply that stored electricity would be much more expensive (including the wholesale cost of the electricity and the cost of storage) than the wholesale cost of electricity alone. Until (and if) costs come down by considerable factors, cost-effective progress toward very high levels of renewables must face the medium-term variability of renewable production with only a relatively small amount of chemical battery storage.  

There is also a challenge at even longer time scales as well. In particular, seasonal imbalances between renewable supply and electrical demand over weeks, months, and years are unlikely to be solved by chemical storage or any demand-side adaptations—we need to think about other ways to compensate for seasonal mismatches. Countries and regions with pumped-storage hydro and reservoirs with multi-year capacity will clearly be better able to utilize seasonal excess energy from renewables than regions without large, long-term storage.

That said, I now want to focus on the medium-term and to emphasize demand-side options. There are multiple, partially overlapping ways to help match renewable production and demand in the medium-term by harnessing or increasing flexibility to respond to renewable variability. While some of these actions are on the supply side, I want to focus here on demand-side actions.

Previously I have discussed one such demand-side option: AC pre-cooling to help align electrical consumption to the general pattern of solar production by taking advantage of storing “cool” at the end-use. (Click here to read the blog post.) This helps to adapt consumption to what could be called the “temporal endowment” of renewables, which, for solar, is during the hours in the middle of the solar day. Also, I have explored water pumping aligned to solar production (click here to read the blog post) and electric vehicle charging aligned to wind production in Texas, which is mostly overnight (click here to read the blog post).

Air separation plants can potentially adjust their consumption to help compensate for renewable fluctuations. Credit: Image provided by courtesy of Linde GmbH, Germany, 2020.

Another promising approach to demand-side management comes from UT chemical engineering professor Michael Baldea and his graduate students, including Morgan Kelley, Joannah Otashu, and Richard Pattison, with whom I’ve collaborated. The team has demonstrated flexibility of electrical consumption in industrial chemical processes through storing end-use products. In this research [see, for example, Morgan T. Kelley, Ross Baldick, and Michael Baldea, “Demand response operation of electricity-intensive chemical processes for reduced greenhouse gas emissions: Application to an air separation unit,” ACS Sustainable Chemistry & Engineering, 7(2): 1909-1922, February 2019], a case study considers the cryogenic separation of air into its constituent gases (in this case, nitrogen, but also oxygen and argon can be taken into consideration). This process is electrically intensive, but these products can be stored conveniently in liquefied form. Conceptually, this allows us to increase the production rate of the separation process (often referred to as an “air separation unit” or ASU, and illustrated above) in time intervals when, for example, renewable production is high, wholesale electricity prices are low, or marginal emissions from electricity production are low.

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To implement this concept, however, how do we deal with the fact that price signals in wholesale markets are updated hourly or sub-hourly? And with the fact that renewable production and emissions can fluctuate at the sub-hourly level, while key variables of the chemical process have dynamics that can be longer than hourly? We need to consider the chemical process dynamics and the limits on the values of process variables, such as pressure and temperature and the chemical composition and purity of the products, when adjusting consumption to follow prices. What Professor Baldea and his students show us is how to represent the salient issues of the complex dynamics of the process variables into a demand-response model that can respond to fluctuating prices or renewable production while also maintaining process variables within allowed ranges. 

How would this flexibility be utilized in an electricity market such as ERCOT, which has both a day-ahead and a real-time market? To participate in the day-ahead market, the air separation facility could first roughly forecast when wholesale prices are expected to be lowest in the coming day. Currently in most electricity markets, this is typically overnight and on weekends, but as solar penetration increases, hours in the middle of the day will also likely have low prices, as is already happening in California. Given a daily target for air separation products and the required electrical energy over the day, the plant could bid to consume electricity during the lowest price hours in the coming day, bearing in mind limitations on how fast it can change production from hour to hour. This would lock in day-ahead prices for consumption targeted to the lowest priced hours: if the plant follows in real-time its position from the day-ahead market, then it will pay exactly the amount determined in the day-ahead market. Because the consumption is focused on low-priced hours, the total energy bill would be lower than, for example, producing the nitrogen, oxygen, and argon at a constant rate throughout the day.

In real-time, electricity prices can vary due to unexpected outages and other events, including renewable fluctuations, providing an opportunity to further benefit from swings in prices. In a market such as ERCOT, with a price cap of $9,000/MWh, the swings can be considerable. If a market participant deviates in real-time from its day-ahead position, then it effectively purchases or sells that deviation at the real-time price. Naturally, it would be advantageous to sell when real-time prices are unexpectedly higher (effectively requiring that the plant have some additional product stored to satisfy its customers for such an event when it is actually producing less than planned).  

Historically, few loads have participated in real-time markets in ERCOT, because the requirements for dispatchability by ERCOT and other market operators have not been attractive. Depending on the circumstances, an air separation plant might have the ability to satisfy these requirements and bid into the real-time market. However, even if it is not attractive to fully participate by bidding into the real-time market, the plant can still take advantage of wholesale price fluctuations by simply adjusting its consumption compared to the day-ahead position. Again, such deviations require some additional storage capacity for the end product. Effectively, the air separation plant can provide flexibility to the electricity market by having additional storage and additional stored product that enables it to cut its production when the price is right.

The air separation plant is a particularly good candidate for providing such flexibility, but many other industrial processes may also be able to adapt to varying conditions and thereby help with accommodating high levels of renewables. Historically, many industrial processes have agreed to be interrupted in emergencies in return for lower electricity rates. Today, the market allows them a much more direct way to profit from their flexibility.

In the future, we may also see new uses for electricity that are inherently more flexible than traditional consumption, or that lead to other ways to store the electricity in an end product or energy carrier. Such futuristic applications include the electrolytic production of hydrogen, the production of chlorine (for example, see: Joannah I. Otashu and Michael Baldea, “Demand response-oriented dynamic modeling and operational optimization of membrane-based chlor-alkali plants,” Computers & Chemical Engineering, 121: 396-408, February 2019), or the production of ammonia. These approaches add to the growing list of ways to use demand-side flexibility to accommodate high levels of renewables.

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