My Opinion: Sustainability Depends on Understanding System Interrelationships

Ed Brown

I strongly believe that when designing a project, you should start with a broad view of how it affects, and is affected by, other systems. Then when you start your design, you can take those impacts into account. This is especially important when your work relates to energy efficiency. For example, how does electrifying a whole spectrum of systems from vehicles to homes to commercial buildings affect power generation and transmission systems?

So, it caught my attention when I read a National Renewable Energy Laboratory (NREL) article titled “The Nature Lover Who Sees Our Planet from a Bird’s-Eye View.” It describes the work of Jibonananda (Jibo) Sanyal who leads NREL’s Hybrid Energy Systems team, which studies how future systems — including the power grid, buildings, and cities — can seamlessly integrate to provide communities with the steady power they need. Jibo’s work is an excellent example of my opinion that engineers should consider environmental impacts in their designs.

He started our conversation by telling me that although his Ph.D. is in computer science, he was always more interested in applications than creating the “next greatest search algorithm.” The applications that currently most interest him are the interrelationships among energy systems.

“I'm quite heavily involved with the NREL Advanced Research on Integrated Energy Systems (ARIES) research platform. It is all about future energy infrastructure and future energy systems, which are going to be inherently integrated systems-of-systems. A lot of these technologies are super new while some of them are older and well understood. And we are studying how they're all going to work together so we have confidence in them,” said Jibo.

He understands that taking a broad system-level view also requires analysis of the details of individual applications. Not only is he focusing on energy but also on non-energy consequences as well — a uniquely integrated approach. He is developing analytical tools that will readily help decision-makers understand a range of considerations, from examining the impacts of particular manufacturing methods at a plant level, to how these will impact other systems such as the ecology of the water supply.

Non-Energy Industrial Benefits

As an interesting example of non-energy effects, consider that a boiler or chiller is nearing the end of its life and will need to be replaced. Say there are three different technologies to choose from. A major factor in the choice will certainly be energy efficiency, but some of these technologies could also lead to reduction in how much water gets used, or maybe that the water comes out at a lower temperature. This is an environmental benefit that is understood but not quantified — but what if it could be?

In addition to the environmental benefit, perhaps the lower-temperature water reduces the risk of workers being scalded, which leads to lower medical expenses and reduced risk of lawsuits. So, there is a significant financial component in addition to worker safety considerations.

Jibo and his team are building a tool that allows an energy auditor to think through and quantify these possible non-energy benefits. “Because if you can quantify, it helps with your ROI,” said Jibo. The tool is designed to be used by all levels of stakeholders from the plant managers to the C-suite executives who make the final financial decisions.

De-Risking Energy Systems

In another scenario that can benefit from Jibo’s analytics, suppose a start-up has developed a system that will assure that if your power goes out or fluctuates, it will automatically switch over, so you won’t lose power. Suppose they can only test it up to 100 kilowatts, but it has to work at one megawatt.

De-risking the technology could give you guidance on how to safely scale it up. The system will have to stay within certain voltage and frequency limits. It will also need an adequate transient response if there is a hard switch from a heavy load going on or off, and consideration of how it then impacts interdependent systems.

The de-risking allows the designers of a new system to quantify and predict its performance in advance. These analysis and validation capabilities can address the hesitancy in making longer-term investments in a new system by addressing the high-risk unknowns, ensuring the technology is stable enough, and whether it will ultimately pay off.

Urban Systems

These days there are an immense number of sensors in urban environments — almost everything is data-driven. Whether ordering food from a delivery service or sensing traffic flow, there is an interconnected system of systems. For example, there are sensors that count how many cars are passing through intersections, how many are making a left, how many are making a right, how that's changing day to day, and how that correlates with the seasons or weather conditions. And while the immediate data is used for optimizing traffic signal timing, the longer-term aggregate data, can be used for planning purposes like what kind of infrastructure investments are worthwhile.

“But so many of the urban systems affect each other, it’s not just traffic patterns. You might wake up in a building, you take some means of transport, go to your work, spend your day there, and then make your way back, pick up your kids along the way, or go to the gym, and get groceries. It's the human set of activities around which everything is built. And all of these services are being put on steroids, really, with all the data and sensing we have around us. Urban planners bank on a lot of this data to see where growth is happening, what new businesses are coming in, what kind of new infrastructure is needed, both from an energy and a mobility standpoint,” said Jibo.

Energy Optimization

From a scientific standpoint, it is important that we understand discrepancies in energy demand and delivery across economic demographics. There’s a very significant scientific and infrastructure risk that this addresses. Hypothetically, let's say there’s an entire neighborhood where everybody has an EV or some kind of energy storage. In the event of an outage, will the priority for energy restoration for this area go down because of the perception that they are going to be ‘okay’ for a while?

“From a financial standpoint, for example, the sizing and cost of transformers for supplying energy to a particular neighborhood might become dramatically different. There are significant scientific, social-technical, and economic aspects to our rapidly evolving energy demand and supply challenges.

“A lot of the urban sensing work we do is based on sensors — and where do you typically have the most sensors: where there is substantial existing infrastructure. We can use data-driven insights to improve the quality of life, but for areas that are already rich with data. We are looking into using AI to bridge the gap where data is not easily obtained so that the benefits will be universally available,” said Jibo.

The Business of Energy Innovation

There is a bottom line to all of this work. By taking a broad view of the interrelationships between systems, Jibo and his team are developing methods for optimizing energy resources, while providing tools that demonstrate viable business models that will foster innovation and propel economic advances. That’s what I call a win-win.

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