Power struggle: how data can help the energy sector innovate
20 to 70 years. That’s the average time it takes to deploy new technologies in energy innovation. If you’re a fellow energy sector professional, you’re likely sighing in agreement. Our industry is often called a dinosaur or “the place where startups go to die”. Cruel, but true. We have truly embraced the “if it ain’t broke, don’t fix it” mentality for far too long.
The problem now is that we can no longer survive with that mantra. The US electric grid, considered one of the world’s largest machines, has been operating the same way for over 100 years. We generate the power, we transform the power, and we distribute the power. Now, with complex emerging technologies such as distributed energy resources (a fancy term for things such as the solar panels you leased on your roof) and electric vehicles, the grid itself went from a one way flow of consumption to an ever-changing network of increased instability. This shift has demanded that innovation not only take place, but take place at an incredibly rapid pace to make up for lost time.
This may sound a bit doom and gloom, but the vastness of the issues has brought the industry in sharp focus. Although still slow on uptake, electricity providers are now embracing new technologies such as advanced software systems (i.e. Distributed Energy Management Systems, or DERMS), IoT sensors for monitoring, and taking many of their longtime analog systems to the new digital realm. The most interesting learning is that although at first glance this appears like a technology shift, the shift is cultural at its core. Our industry has to completely rethink the way we manage the grid. We have to embrace new methodologies, new processes, and let go of the way it’s always been. And with a big smile on my face, it’s happening.
For the energy sector, the next phase of transformation requires embracing data science. The amount of data created and consumed to bring energy to the masses is astronomical… and we’re barely tapping into it. Sadly, organisations can’t just wake up one day and decide “let’s hire a data scientist, that will solve our data problems!”
It’s well documented that out of the USD 50 billion invested in artificial intelligence projects, 85% will fail. Why? Because we’re jumping to develop tools we think we need, instead of solving problems that actually exist. So where do you begin?
Charging into the Future
Start simple, define your data. You’re sitting on more than you think. Then identify and get rid of the silos that prevent the data from being shared within the organisation. Gather stakeholders to define a well thought out data strategy before taking on major technological shifts.
Let’s say, you’re an electric utility company and you’re having a rash of underground cable failures. A brilliant young engineer suggests installing faulted circuit indicators on every lateral to help catch the outages quickly and deploy your crews faster. A sound suggestion, but that is a lot of faulted circuit indicators. Those installations require qualified electrical workers, training on the installation method, work orders, dispatch coordination, and so on.
Before taking this head on, you can instead run an analysis on the data from the failures you’ve already seen and look for trends. This could bring together multiple data sources such as equipment failure reports, as-built drawings, crew work orders, and weather data. Turns out there is a specific crew that is linked to 90 percent of the failures, and after further investigation it’s a workmanship issue. Are the faulted circuit indicators still valuable for decreasing crew response times and lowering outage minutes? Of course. But with the data you already had, you’ve solved the root cause of the issue and can deploy preventative measures rather than reactive.
This is just one simple example (yes, based on a true story) of how the data at your fingertips can be used in meaningful ways. Applying strategies from simple data trending, to advanced Artificial Intelligence can deliver immediate results to your organization. If you have data, you’re sitting on answers, on untapped opportunities, and on a direct source to improving your business. This is why understanding where you’re at today is the only way to map where you’ll be tomorrow.
To bring energy innovation into the timeline our situation requires, we have to first understand the root of our problems. We have to leverage the data we already have. We have to think in ways we haven’t thought before. Have a great idea? I honestly want to hear it. Talking about how we bring forth a responsible energy future for future generations is so important, and together we can bring forth the innovation this world needs.
If you are an energy company grappling with data-driven innovation, book a consultation with Amanda here.