During the last two years, MIT and Harvard have co-hosted the MIT A+B symposium on rapidly decarbonizing our society. These conferences have a unique approach that I really appreciate. The organizers call for presentations on A) mature, cost-effective technologies that are ready to deploy at scale, and B) potentially breakthrough technologies that may enable achieving a near-zero carbon emission society.
Unique conference structure
Splitting the presentations into these two categories or timelines does two things. It supports the urgency of the situation by emphasizing and exploring details of the abundant cost-effective, existing technologies that can be deployed now to make immediate impacts. These are the technologies that businesses can rely upon in the near-term and build into their business plans. They are also the technologies that policymakers should be looking towards to craft achievable near-term climate targets and policy.
The “potentially breakthrough technologies” category engages the research community and pushes the question of what is possible. Many studies have shown that achieving 80% carbon emission reductions is relatively simple. The last 20% of emissions that takes us to carbon neutral is by far the most difficult piece to solve in the carbon neutral puzzle. We need to cast a wide net to explore many possible technologies that could be available in a few decades to meet our final climate targets.
Electricity generation in systems with substantial wind- and solar-power
I submitted an abstract to the 2020 MIT A+B symposium focused on category A, deploying existing, cost-effective technologies. The abstract asked two questions: 1) how much traditional electricity generation capacity is needed to reliably meet society’s electricity demands as wind- and solar-power rapidly scale up? And, 2) how does the required traditional electricity generation capacity change year-to-year? This is an interesting question because the answer varies based on local industry and electricity use patterns and climate. A more detailed discussion of my presentation will follow.
For now, suffice to say, the abstract was accepted. A prerecorded virtual presentations is available online. Lastly, a short paper extending and refining the material in the presentation is now available in the conference proceedings.
I was invited to submit an extended version of the conference paper to the Applied Energy journal. The deadline for submission is Feb 1, 2021. Time to get moving.
There are many quirks of being an ex-high energy particle physicist who completed their PhD with the CMS experiment. For one, waking up in the middle of the night for an upset child doesn’t seem too bad compared to the many nights when I was “on-call” and woken up at 3am to help debug data collection issues with our experiment. I would much rather be “on-call” for my son than for a 14,000 tonne inanimate object.
Another quirk is that I am a year into my Postdoc at Carnegie Science and only now am I publishing my first ever first author paper. It is hard, in fact nearly impossible, to get to the front of the 3,000 person author list for the papers published by the CMS experiment. Needless to say, I did not make it to the front while I was part of the CMS team.
Now, I have the pleasure of being the first of only four authors on a paper discussing data cleaning and preparation for use in our energy models. While not the most glorious of papers, we hope this paper and the data we cleaned can be used by the energy modeling community. After all, more realistic data leads to more realistic models.
Part II of an energy and research discussion for my parents (part I)
We all expect that when we flip the light switch at night, the lights will turn on. We won’t have to stumble around in the dark feeling around for a glass of water or to let the dog out. There are people and algorithms working around the clock to make sure when you and I request power, it is available.
This is exactly what our electric utilities do. They focus on delivering reliable and safe power to meet our “demand”. Because most utilities do such a good job of delivering electricity, we never think about the details.
The chart below gives a good idea of my family’s electricity demand last Thursday, October 24th. You can see there are many spikes as we made coffee and ran the dishwasher in the morning and other larger spikes later when we returned from work. Your energy use probably looks just as spiky though the details will certainly differ.
Our household daily usage is fairly similar day-to-day, even if the exact timing of making Henry and myself breakfast can differ quite a bit.
Sharp spikes to smooth curves
If every household has spiky electricity demand, how can our utilities anticipate the amount of power they need to produce at any one moment? Utilities rely on my demand, the demand of all my neighbors, and your demand being similar day after day. This helps them figure out a daily quantity which will likely be requested.
What about the precise timing of our morning coffee, how do they get that right? Utilities rely on having many customers and the law of large numbers. Not everyone makes coffee at 6:00am. Some make coffee earlier, some make it later, some not at all. When the actions of thousands of electricity customers are added together, their small differences smooth out the jagged spikes you see from my household when viewed in isolation. This leads to a very predictable energy demand throughout the day for a utility territory.
The below charts show electricity demand over three October days in 2017. The first is for a small utility with only 26,000 customers. This demand curve is already much smoother than my single household’s usage. And, the total demand across the contiguous United States is even smoother. In both of these cases, the demand has a cyclic peak-and-trough pattern with the lowest demand late at night.
Utilities can make accurate forecasts of their territory’s electricity usage 24 hours in advance. Most can predict 24 hours ahead within 3% of the real value. This makes the cyclic peak-and-trough structure of demand very approachable for utilities.
Providing Electricity the Traditional Way
Over the past century, utilities have traditionally built enough coal, gas, nuclear, and hydro plants to match the peak electricity demand for their territory.
When a utility forecasts demand will reach 5,000 Megawatts tomorrow at 5:00pm in their territory, they make sure 5,000 Megawatts of their power plants will be ready to produce at that time. Human errors and mechanical failures can happen, and when they do, they are addressed. But, overall, the traditional system is very predictable.
The large scale introduction of intermittent renewable energy is changing this and will be the topic of the next post. Let me know if you have any questions or would love more detail. Check out the current energy use in your region with this amazing map.
Part I of an energy and research discussion for my parents
Abundant energy has shaped the modern world. It has enabled wonderful innovations such as rapid and affordable travel, vaccines produced on an industrial scale, fertilizer for our crops, an elevated standard of living for billions of people, and the Information Age just to name a few. Fossil fuel makes up the majority of the abundant, easily accessible energy we have consumed to get here. While our standards of living have been elevated, the aggressive burning of fossil fuels has positioned us on a path for severe climate change .
Current technologies exist that can significantly reduce our global energy use while delivering what energy is still needed via clean, carbon free sources. And, yes, this can be done while bringing power to the one billion people currently living in energy poverty.
A Brief History of Energy Use
Energy use has skyrocketed over the past two centuries. Over this same period, the composition of fuels and power sources we use changed significantly. Prior to the 1850s, wood was the main fuel source. For the first half of the 1900s, coal dominated. But coal was quickly outpaced by petroleum with the rise of the automobile. The 1970s saw the introduction of natural gas and nuclear power on a large scale.
At the start of the 1970s, petroleum was set to continue its exponential climb. Instead, the global energy market was struck by the oil crisis of 1973. The U.S. Federal Government enacted sweeping programs to beat down energy use while keeping the economy humming along. This was the introduction of energy efficiency as a staple of the U.S. energy strategy .
It is difficult to disentangle the effects of a growing population, an expanding economy, and an economy transitioning away from heavy industry in a single chart. The above chart shows us that the “Energy Intensity” or energy used to create economic value has been decreasing in the U.S. for many years. However, in the 1970s, after enacting aggressive efficiency policies, Energy Intensity fell faster than before.
Another way of viewing energy use is considering the amount of energy used per capita. Historically, the the total energy use per person in the U.S. increased every year until the 1970s. Since then, use per person has been steady or slightly declining.
It is worth noting that the U.S. has outsourced a significant portion of its heavy industry as it transitions towards a service based economy. Regardless, energy use per capita and energy intensity are both helpful indicators of the efficacy of coordinated energy efficiency policy at the national level.
A re-invigoration of coordinated energy efficiency policies would help further decrease Energy Intensity and reduce the energy which we need to supply with carbon free sources.
Carbon Free Energy
Nuclear energy and large scale hydroelectric power have been staples of the U.S. electric system for many decades (see first figure). Solar and wind power are relatively new to the U.S. energy portfolio. These four technologies, plus biofuels, make up two different categories of carbon free energy.
Predictable power sources who’s power output can be increased or decreased as needed (nuclear, hydro, biofuels)
Intermittent sources who’s output is controlled by weather, not customer needs (solar and wind).
The above chart from the EIA shows carbon free energy production by source and is part of their annual energy review. Solar and wind energy have begun a rapid rise since the turn of the millennium.
The rapid increase in solar and wind energy is on a collision course with the way electric utilities traditionally operate their grid. Intermittent solar and wind challenge operators to deliver continuous, reliable power despite their fluctuations. Batteries and other storage technologies are being researched, developed, and continuously improved to help smooth out these difficulties.
Currently, in places with lots of installed solar power, electricity is stored in batteries when it is sunny and discharged back into the grid when large clouds pass over, reducing solar panel output, or during the night. Many new wind power installations also include batteries to help smooth out fluctuations.
To enable a large scale energy transition away from carbon intense sources towards carbon free sources, we need to figure out the right mix of intermittent renewable energy, other clean sources, and storage technologies to create a reliable grid. This is the central focus of my current research working with Ken Calderia at Carnegie Science.
 IPCC Working Group 3: Fifth Assessment Report “Summary for Policy Makers” https://science2017.globalchange.gov/downloads/CSSR_Ch1_Our_Globally_Changing_Climate.pdf
 U.S. Office of Energy Efficiency and Renewable Energy, “Energy Intensity Indicators”, Accessed 14 October 2019, https://www.energy.gov/eere/analysis/energy-intensity-indicators