The first installment of our thought leadership series features Chris Kalima, Intertrust’s Vice President of Product Management, as we discuss the intersection of distributed energy, data interoperability, and device security.
—What are some of the challenges the energy industry is facing, especially related to energy resources and managing a distributed grid?
There is an enormous amount of coordination that’s required in order to manage a distributed grid. Energy is shifting away from fossil fuels and renewables are on the rise. But the problem is renewables are not always predictable or they are only available during certain times.
For example, solar is great during the day, but as soon as the sun goes away in the evening, how do you meet increasing demand as heaters turn on, lights turn on, people want to charge their electric vehicles because they’re returning home from work?
So there is a huge demand spike and a simultaneous loss in energy production as the sun sets or maybe the wind dies down. So then you switch to battery storage, or you even share your battery storage with the distributed grid.
How do you determine when and how to discharge the battery resources? How do you communicate across the network to coordinate the available resources that are out there but are not directly under your ownership or control?
— So what is the approach for connecting the smart, connected home to the grid so it can sync its demand with the available grid capacity?
You need to not only see the data and data sources and understand the demand, but also to control how the energy at the device level is being consumed and load balanced. For example, when to turn on or off charging, or when to draw from what external resource.
But this isn’t just a matter of control, it also comes down to a question of data privacy and consent. Device and device data must interoperate with the larger distributed energy ecosystem, but they can do so only where consent is granted. Data security and trust is paramount for privacy and compliance in a model where consumers agree to give some level of control to a third-party, for the purpose of automating energy distribution against available capacity.
Of course this isn’t a need isolated to the residential home. Industrial settings or smart cities will also rely heavily on data-driven models where there are vast, interconnected networks of devices and data formats that must interoperate and react based on shifting requirements. Devices from different vendors will need to consent to work together ans for a mutual benefit. This is all going to be driven by data and data sharing.
For example, Intertrust technology partner DigiKoo offers an intelligent grid application in Germany, known as InGA. During a grid capacity shortage, a given substation will issue a power cap, or upper energy limit. InGA passes on the cap to charging system operators across the city in an unbiased manner. Through the automated governance of InGA, CSOs are treated equally and their customers are not impacted unfairly during the period of the shortage.
— Are there security implications, given how device endpoints are often the target of attacks? And, if so, how do you overcome them?
Yes, you’re going to have to confirm, on an ongoing basis, that these devices are what they claim to be. You need to know that you’re communicating with the right devices and that the data coming off of them is authentic, and has not been tampered with in transit or at any end point.
Without that, the machine learning models can be poisoned through the injection of bad data elements or inaccurate data to make the system think that something is happening when in fact that is not the case.
As devices become more ubiquitous and autonomous, they end up relying on signals received from the AI that operates them. Devices that are data-driven and operated without human intervention require greater levels of protection, especially where they have critical capabilities and functions. There’s a difference between hacking a smart bulb to rapidly cycle and fail, and bricking all the thermostats in Kiev right before a winter storm when people need heat to stay alive. There are many serious attack vectors that can be exploited out there.
Devices and data must be protected so the energy ecosystems can operate in a trusted way. Especially where commands are being sent back to devices, you must confirm this data is authentic to prevent accidents or worse, if malicious intent is what you are defending against.
— What about on the operations side, what are the considerations for how meaningful data is being processed, blended, and distributed?
On the cloud side, you of course need to process the device data in a secure manner. As the data is exchanged, it needs to move around and get shared with different entities. You provision the data to exactly the people who need to use it. You provide business analysts, data scientists, applications, and third-party stakeholders with granular access to only the data they need.
So not only the device side, but once that data propagates to other companies or different divisions or different functional units within a single organization, you must make sure it is interoperable and can be distributed in a trusted way. This allows the data to be consumed and used to make the right business decisions.
We can now intelligently operate the grid and optimize it through the connection of authenticated devices and data.The end goal is better management of the energy grid, better use of natural resources, and less reliance on fossil fuels–as we close in on a zero carbon future.