Electricity is an increasingly complex industry in the midst of transition to renewables and decarbonization. Using my 25 years’ experience as an engineer, policy analyst, and academic, I help my consulting clients think through their toughest technical challenges and formulate their best business strategies.
Renewables are often touted as being cheaper than fossil generation. Certainly true when we have wind or sun. But when it is not sunny and not windy, we must, by definition, use a more expensive resource. So how do we make sure that the total cost of producing electricity is the lowest possible, considering both the capital (investment) cost and the operating cost, where the latter might include the “cost” of inconvenience to us as consumers of re-scheduling our consumption.
The biggest challenge, then, is to match supply and demand. We all know that renewable production depends on the ambient conditions, varies over time, and does not closely match typical patterns of consumption. This is famously reflected in the California duck curve. In a previous post, I suggested that residential pre-cooling in regions with significant air-conditioning load could match the daily variability of solar production to electricity consumption.
But the fluctuations are not just daily. Variability also presents problems at timescales from the very short-term (minute by minute) to the very long-term (seasonal and longer). Much of the variability has a random character, because of issues such as the weather’s effect on renewable production and electrical consumption. How, then, should we think about matching renewable supply and electrical demand, bearing in mind that we must balance production and consumption in the electricity system at all times?
A first observation is that a portfolio of diverse renewable resources will have lower variability than a single resource. Its mix of resources can also be chosen to best match consumption on average. But that would still leave a discrepancy between renewable supply and electrical demand.
There are many possible solutions for coping with the discrepancy between renewable supply and electrical demand. Generally, I have advocated for demand-side responses to match demand to supply. And now that the cost of chemical battery storage is getting cheaper, batteries also play an important role in aligning renewable production to consumer demand. Where available, hydroelectric resources are useful. (Bill Gross’s Idealab has developed another promising storage technology that lifts heavy weights to store energy.) And I can also see how thermal resources, used sparingly, would help in matching supply to demand, particularly to cope with solar and wind “droughts,” where there might be little wind and solar for several days.
What is the most cost-effective solution? What’s key, I think, is to understand the underlying cost structure of each proposed solution, at least in broad brush. And when considering cost structure, we need to take into account the distinction between the capital cost per kW of power capacity or per kWh of energy capacity, or both, and the operating cost per kWh.
At one extreme, we might consider a solution that is capital intensive, like batteries and some thermal generation, with a high cost per kW of power capacity or per kWh of energy capacity. Such assets are most economical when used very often. Battery storage used on a daily basis to provide ancillary services has been relatively profitable, meaning that the value it delivers can easily justify the expense of the battery. On the other hand, using a battery or a thermal generator only for a once-a-decade condition, such as the extreme weather in ERCOT in February 2021), is likely to be expensive, because the cost is expended for only one occurrence of benefit per decade. In other words, to be cost effective, we need to stack the benefits of batteries. So, if we can use batteries for multiple applications, utilization is overall high enough to justify the cost.
At the other extreme, we might consider solutions that are operational cost intensive, with relatively lower capital cost. They include peaking generation, consumer backup generators, and various forms of demand response that involve interrupting customer service. These solutions are only viable if used very occasionally and for short periods of time.
Some good news on the consumer backup generation front: the upcoming “vehicle-to-home” (V2H) technology, where an electric vehicle battery is harnessed in a microgrid with rooftop solar. Nissan Leaf already has V2H available and next year the Ford F150 Lightning will be available with V2H. V2H is best suited to only occasional use because, obviously, unlike a dedicated generator, you need your car to drive. However, in a winter storm such as Texas experienced in February 2021, I needed power at my house during the blackout and could not even drive on the snow-covered roads, an ideal application for V2H! Such solutions match the rare, but sometimes severe, occurrences of distribution failures and rolling blackouts, stacking this occasional back-up role on top of the daily benefits of having a car. In a highly renewable world, V2H is also a potential solution for renewable droughts.
In between those two extremes, we can also imagine other solutions. Battery technology is improving, pushing its applicability toward uses with lower utilization. For example, some level of battery storage may be appropriate for daily charge and discharge cycles even though it would be insufficient for an extended blackout or renewable drought. Some demand-side adaptations such as residential pre-cooling and industrial demand-response may also be viable on a regular, daily basis. They will not, however, provide for a multi-day event such as the 2021 storm.
If we design a portfolio of solutions with heterogeneous cost characteristics, some with high capital cost and low operating cost, others with low capital cost and high operating cost, and others in between, then adaptation to renewable fluctuations can be accomplished across multiple timescales. If we know the cost characteristics of each proposed item in the portfolio, a “screening curve” provides a good guide to the lowest-cost portfolio. (Tong Zhang has developed a simplified implementation of a screening curve analysis. This version does not consider storage, but it could be used to evaluate the least cost portfolio of generation resources to complement renewables.)
Yes, the least-cost portfolio will involve batteries, but batteries are not the full solution. And neither are demand-side adaptations. It takes a portfolio of resources to match supply and demand. This has always been the case for electricity, but the addition of renewables to supply requires that we need to change how we design the mix of resources.
As has been exhaustively reported, the severe weather event in Texas and surrounding states in mid-February resulted in blackouts across the Electric Reliability Council of Texas (ERCOT) region, including blackouts for all but 90 minutes of a 59-hour stretch at my own home in Austin. Despite some initial claims motivated by animus against renewables, failures occurred across all generation technologies, as well as in gas and water infrastructure, and we can expect that there will be inquiries into the specific ways in which cold caused the Texas blackout.
Much public outcry has been sparked by the federal 2011 report about a less severe Texas winter storm that year. The report recommended weatherization for gas, water, and electricity infrastructure, but they were not made mandatory. Did we fail to learn from the lessons of 2011?
It’s more complicated than that. Before deciding on a solution, we need to be clear about the problem. We must first investigate the facts of the recent storm. Among the things we don’t yet know about weatherization:
- As far as I am aware, we do not know what fraction of electric generation and gas supply in ERCOT actually implemented the recommendations from the 2011 report.
- Electric generators have a large number of sensors, pipes, and other equipment, and we do not know whether the specific equipment that failed in 2011 was the same equipment that failed this time.
- In the gas-fired generation fleet, failures in both the generators themselves and in the gas infrastructure contributed to the outages. Was it gas or electric that was the more significant problem?
Should we have expected private asset owners to weatherize of their own accord? Each such asset owner, as any business owner, runs their operations on a cost-benefit basis. If weatherization improves their expected profit, they will do so. But when the public good is at stake, we can’t always leave risk management decisions to individual actors. In the context of a large “common mode” cause that affects many assets simultaneously as in mid-February, such private actions may be inadequate to appropriately address the risks from the community’s perspective.
When we face risks due to rare events, like winter storms in Texas, whose probabilities may increase with climate change, we cannot depend upon individual asset owners to make risk-averse decisions for the sake of community health and safety. We will likely need to impose regulations and standards to improve extreme weather resilience.
These improvements are likely to focus on weatherization, and they may also include, for example, smart grid technologies to more equitably “spread the pain” of any future blackouts. There may also be market design changes.
But before “firing” on any such actions, we need to “ready” and “aim” by first understanding: 1) what exactly caused the system failure, and 2) what are the costs to avoid these failures or respond to them more effectively. If we truly want to protect our communities, the right actions require thoughtful fact-finding.
Here are several links to selected panel discussions I have participated in and interviews I have given about the Texas blackout. (I will share a comprehensive list next week):
Institute for Operations Research and the Management Sciences (INFORMS) panel with Professor William Hogan (Harvard), Professor Shmuel Oren (Berkeley), Dr. Richard O’Neill (ARPA-E), and Professor Benjamin Hobbs (Johns Hopkins). Click here to view.
Salem Centre for Policy, UT Austin McCombs School of Business panel with Professor Sheridan Titman (UT McCombs), Ms. Bernadette Johnson (Enverus), Ms. Becky Klein (Klein Energy LLC), Professor David Spence (UT Law and McCombs), and Professor John Butler (UT McCombs). Click here to view.
“The Electrical Power Crash Is Just Like a Stock Market Crash,” by Peter Coy. Bloomberg Businessweek. Click here to read.