Sean Moser, GE Digital Grid Software
History shows that every cycle of human innovation and growth has been dependent on a network – the telephone, rail and shipping, the Internet, and, of course, electrification.
The electric grid is a very, very finely-tuned network that also happens to be the largest machine built by man.
It wasn’t that long ago that a grid operator’s job was to simply manage the connection points in the network. Switches, are they open? Are they closed? These operators monitored the power coming in from hydroelectric dams, nuclear reactors, and steam generation plants. Then they looked at the previous day’s consumption and weather conditions to predict what the demand will be and how to deal with it.
That was the full extent of managing energy on the grid. It was very complex, but we kept the balance — every electron comes on as another one goes off and grid operators managed frequency.
But with advancements in technology, our networks are becoming more complex. Take, for instance, the telephone network. It was once regional and proprietary. But it has now moved to a business based on digital signals running on the Internet with a fiber backbone. The electric grid is now experiencing a similar transformation.
In the Los Angeles basin, a new solar-equipped home comes onto the network about every five minutes. There will be tens of thousands of new electric vehicles this year. So now there is a neighborhood that is producing electrons and another neighborhood that’s consuming them. That one simple change creates a lot of challenges for grid operators. How do they keep the grid balanced?
The challenge of predicting the future
The challenge isn’t just to manage what exists today. It is to imagine the grid of the future. We know that it won’t operate the same, and we know that it won’t be commercialized the same way. But we do know that the scale and the speed will be beyond our ability to manage with people in control rooms today. And we also know that it won’t be designed the same way.
There are additions we’ll make to the physical network. We won’t create a new one, but we will transform the one we have. We will add to it, modernize it. We will make it smarter.
The challenges of transforming today’s grid into the intelligent energy network of the future and enabling the electronic economy to grow are many. Digitalization is the key to solving these challenges because, again, we aren’t replacing the physical network, we’re modernizing it.
That requires modeling and sophisticated forecasting and look ahead capabilities. It is AI and machine learning combined with real policy that will allow utilities to see the grid as it will exist in the future and to plan for how it needs to change.
The need for speed
The demand for electrification between now and 2025 will outstrip the increase in renewable energy capacity that decarbonization is calling for. For example, electric vehicles are replacing combustion engine vehicles. If we take all the wind turbines and solar panels and deploy them as fast as we can manufacture them, we will most likely not keep up with the increase in demand.
This change is happening so rapidly that as utilities seek to bring more distributed renewable energy on to the grid to not only meet demand, but to meet decarbonization goals, they need to manage those distributed energy resources (DER) today, right now. They can’t just forecast for the day ahead. They now have to forecast for the next hour. And now they need to forecase energy production from DER as well as energy demand.
Digital technologies look ahead in very rapid, near real-time increments, and then trigger demand signals into a market that is constantly monitoring the production of electrons that are available for consumption. Utilities, then, can buy those electrons in real time to match the demand that they’re going to have in the next five minutes. That couldn’t have happened five years ago.
Change has already begun
The grid is not one-way anymore. Operators have to deal with both generation and transmission with hundreds of DER connected at the distribution level and the intermittency nature of renewables. This leads to the challenge of having to quickly mitigate potential distribution outages. And as the industry commits to decarbonization through renewable sources like wind, solar, electric vehicles, and energy storage, utilities need digital solutions to enhance grid resiliency and reliability.
We are already deploying digital technologies to deal with challenges in the grid today. Advances in software enable electricity distribution utilities to optimize their operations with increased flexibility and operational awareness. This means that field crews and operators are better connected to provide an effective and efficient response to power distribution situations, including getting power restored more quickly in case of an outage.
The distribution network is a tree and node network, so paths go out and terminate. This means the grid can’t always be managed to heal a fault. And this problem gets exacerbated as we add more connection points to the distribution network, i.e. electric vehicles, batteries, and solar panels.
Today’s distribution management system (DMS) looks at the following:
- How do I sustain and maintain availability to the end consumer?
- How do I keep the lights on in the home?
- How do I keep the air conditioning running?
- How do I keep the car charged?
- How do I keep the factory running?
That’s what the distribution management system cares about. The distribution network is becoming progressively dynamic, complexity is increasing, and the volume of data that utilities need to understand and integrate continues to grow.
The advanced distribution management system, or ADMS, is the software that’s used to manage the entire low voltage distribution network. As energy comes off a high voltage network, it comes down to a substation and gets distributed. This is not a redundant system.
Many utilities consider ADMS to be a combination of SCADA, distribution management systems, and outage management systems to span and connect distribution optimization, outage response, and DER orchestration. This integrated architecture has grown in recent years to include energy management systems and distributed energy resources management system (DERMS) modules. This growth is a natural technological extension of ADMS. The boundary between networks is blurring, and future network operators require access to both transmission and distribution applications.
The ADMS, combined with the utility’s advanced energy management system (AEMS), manages traditional power generation combined with renewable power generation to make sure both are “consumed” at both the transmission and distribution levels. Tracking, managing, and controlling DER in real time connect “behind the meter assets” like solar and EVs, to enable optimization and balancing of power generation and consumption.
ADMS also helps utilities forecast intermittency in load and generation to get as much time as possible to manage renewables and automate fault recovery and voltage management.
One of the other ways that we deploy digital technologies is in helping to reduce the outage impact due to extreme weather events. These events are increasing in intensity and frequency. And while the cause of the increase may be debatable, the reality is not. There are more intense storms, more fires, more ice, and the predictability of these events is decreasing.
Another dramatic change that is happening now is the changes to how electrons are traded. In the United States, ISOs manage large, interconnected portions of the grid and look at cost and availability. It’s their responsibility to look at the market and what the value of an electron is in that market. There are literally thousands of transactions to move electrons from generation to consumption.
Where do we go from here?
Some of the questions that need to be answered include how we rethink the modeling challenge posed by assets behind the meter. It’ll extend into a much broader disaggregated view of generation that is unsensed.
As we look forward, we’ll also want to look at how to automate control systems, how to handle distributed management and virtualization of the network. Could we create virtual pathways or virtual pools that are a subset of the network that would allow an aggregator to only see their part of the network? How do we incorporate weather data? How do we predict the increasingly less predictable with more accuracy and get to the point of impact for recovery?
There’s also a unique business opportunity for utilities. As the number of electric vehicles increases, we will need a new network of energy consumption to maintain mobility. We’ll still rely on trucking to move goods, but the trucks will consume electrons. People will still drive on vacation, but they’ll consume electrons.
Who’s building that new network? How is it being commercialized? Where would we deploy it? Can the network support it? How are the rates managed?
We are not staring into the abyss. We’re at the precipice of an amazing transformation. It’s scary and there’s risk, but it’s something that we simply must do. It is the kind of challenge that we will rise to and it will make the grid smarter than ever.
About the Author
Sean Moser is the SVP of Product Management for GE Grid Software Solutions. Sean began his career working as a designer, creative director and information architect understanding customers use of technology across multiple industries and businesses. For the past 27 years, Sean has held several technical, product, strategic and leadership roles focused on bringing industrial-scale digital solutions to enterprises and governments all over the world. Having been involved from the internet boom through the dawn of IoT, he sees how customer and data driven digital solutions can transform an industry.
Sean joined GE three years ago and has taken on the role of Product Management Leader for Grid Solutions this year, having responsibility for portfolio vision and strategy.
Sean is also a California native, husband and father of two who pretends he can cook.
