This interview is part of our new Blockchain In Energy series, where we interview the world's leading thought leaders on the front lines of the intersections between blockchain and energy.
In this interview we speak with Colin Gounden, CEO of VIA, to understand how his company is using blockchain to transform the energy business, and what the future of the industry holds.
1. What's the story behind VIA? Why and how did you begin?
CG: My colleagues, Kate Ravanis, Jeremy Taylor, Jackie Finn, and I founded VIA in 2016. Each one of us had some level of experience in the energy sector and realized there was a real need for AI solutions in the industry. Since 2016, we’ve had the privilege to work with some of the largest utilities in the world on important grid resiliency issues like predictive maintenance and contingency planning.
Time and time again, we found that though utilities had enormous interest in using AI, they seemed to struggle with their data. Some companies had too little data, some didn’t have clean data, some had a lot of data but not in any single location, and some were unable to share it due to security concerns. That’s when we had the idea to develop our blockchain application, Trusted Analytics Chain™ (TAC™). TAC™ is the only software solution for utility companies that provides data access for sophisticated, privacy-protected analytics while avoiding the time and expense of moving data from its normal location. By using TAC™, a group of utilities can create larger datasets for more rigorous analysis and insights while maintaining the privacy and security of each company’s data.
In recent months, we’ve taken our efforts with TAC™ a step further and built the foundation for the Global Data Asset Collaborative™ (GDAC™). GDAC™ is the first privacy preserving, multi-company database for machine learning-ready transformer data, which has been created on top of our TAC™ software. As an analogy, GDAC™: Transformers is like an app on our “TAC™ app store”.
2. Please describe one of your use cases and how VIA uses blockchain?
CG: One of our best use cases is VIA’s transformer risk prediction and failure prevention initiative, the Global Data Asset Collaborative™ (GDAC™): Transformers.
I’ll give a little context on why this initiative is so valuable for utilities. Transformers are very expensive pieces of equipment. If one transformer fails, the result is millions of dollars in equipment replacement costs, revenue losses, and regulator penalties. So, for utilities, an ongoing function is to assess their transformer fleets’ condition and take the appropriate action to prevent a failure in the first place. It's hard to predict transformer failure when for a single utility, it's a very rare occurrence. To be able to provide insight and valuable predictive analytics, we combine the data and expertise of multiple companies’ fleets.
GDAC™ is creating a new type of “virtual data asset” where TAC™ provides privacy-protected access and analysis of each utility member’s data without moving the data into a centralized database. Analyzing the combined operating experience of the participating utilities is allowing GDAC™ to advance the precision and scope of the partners’ comparative metrics, their rankings of different types of risk (e.g., maintenance, replacement, end-of-life), and the ROI of various proactive O&M interventions.
To make this work, we use blockchain’s smart contracting functionality to control data access across network operators while maintaining the privacy of individual companies. We also use blockchain’s immutable ledger to create a record of how and when data is being analyzed for greater preventative security and regulatory compliance.
3. Could you share a specific customer / user that benefits from what you offer? What has your service done for them?
CG: One of our founding GDAC™: Transformers members has already seen benefits from joining the collaborative. They wanted to see how often fellow members are doing a particular type of maintenance test on their transformers. As a result of seeing private benchmarks of other GDAC™ members, they took action and changed their maintenance procedure just two weeks after seeing the benchmark. This kind of benchmark was previously not possible or too expensive to gather given the data privacy issues.
In general, using a combination of GDAC™ (for data and expertise) and TAC™ (for security and privacy), members see major benefits including:
Advanced notice: members can compare similar transformers to foresee possible issues.
New indicators: relationships previously never evaluated like condition of transformers and weather.
Auditability: blockchain provides greater preventative security and regulatory compliance.
Privacy / security: smart contracts control data access for members while maintaining privacy for each company.
What other blockchain energy use cases are you excited about?
CG: We’re excited about blockchain’s ability to share consumer data securely and anonymously for things like individualized incentive programs (for renewables, as an example).
In general, there is a growing need for greater data privacy, security, and anonymity, as well as transparency from companies that collect consumer data. This need extends to the energy industry and smart meters are a great example of this. In theory, utilities could work with AI companies to leverage the massive volume of consumer data collected by these meters to improve things like reduce overall home energy consumption. However, while utilities gather and store the data, they don’t own it. Consumers own their own data. In addition, governments want utilities to safeguard such data in accordance with consumers’ wishes. So, using TAC™, utilities can balance consumers’ rights to data privacy, security, and anonymity, while leveraging this wealth of new information to improve service reliability, efficiency, and create incentives for their customers.
Where will VIA be in five years?
CG: We see VIA’s Trusted Analytics Chain™ as the go-to solution for both utilities / network operators and AI analysts alike. For utilities, they can become part of GDAC™ (which uses TAC™ as the underlying software) to have their data analyzed to get more accurate predictions about their equipment. For analysts, since it's hard to access robust data like that of utilities, TAC™ will be the go-to software to solve high value, super interesting problems like those related to grid resiliency. The reason we think TAC™ will be the standard solution is that network operators will be confident about being part of the collaborative because it’s private and secure. And for analysts, we’re the gold standard because we have the largest machine learning-ready data sources like EVs and solar, available for analysis.