For the tenth installment of our “Transformer Tuesday” series we’re taking our dedicated readers along on a journey with Annie the Asset Manager from ABC Power as she discovers how to provide the stronger supporting evidence required to approve rate case changes.
We’re back with a fan favorite: VIA’s Meet the Team blog series! Through a Q&A-style interview, you will hear from our very own VIAneers about everything from a typical day at VIA to their favorite books, emojis, and activities outside the office. Now, let’s meet ‘em!
There is no typical day for me at VIA! My days are a mix of business development, go-to-market planning, and sales strategy related activities. These activities can range from partner management to constructing government proposals to figuring out how to optimize our sales tools in order to drive efficiency and organization across the commercial team.
I really enjoy VIA’s flexible work arrangement. I’m usually in the office a few days per week. I enjoy the collaborative nature of in-person meetings with my colleagues. My role is one that requires constant collaboration with my teammates, and although we function well working remotely, some things are just easier in-person!
Plus, I’m known for being a connoisseur of the office snack drawer…but don’t tell anyone! If anyone asks, it was Will Chapman 🙂
A lot of the work I do for VIA is covered under customer confidentiality. So, although I can’t comment on the specifics, I’m proud of the government proposals we have submitted as well as the partner management strategies that I have developed collaboratively with my colleagues. Additionally, I am proud of the workflow processes that our team has created through our tech stack to optimize the relationships with our partners. We consistently set a high bar for ourselves, and as many know, the first step in reaching such standards is having an organized process. Now, we’re on to the next steps!
This is a tough one – probably a mix of the late nights working on proposals, a prank that my teammates pulled on me, and company related trips!
The VXP and company values are real! It is very impactful to hear and watch leadership stick to these values on a daily basis.
Generally speaking, I find it very exciting to watch how VIA’s technology can be uniquely tailored to fit customer needs through a combination of the dynamism and flexibility of our technology and the agile software development approach. I have enjoyed watching the transition of the work that we compose in proposals to the technical implementation of that work by our fantastic and incredibly skilled technical team. One example that comes to mind is VIA’s current work with USAF’s AMC (Air Mobility Command).
I think there is a lot of potential here – it is very exciting to be part of a software company that is at the cutting edge of web development, and doing so while holding true to our mission and values. My time at VIA has opened my eyes to the distributed data reality that many companies across industries face, and it is exciting to be part of a team that provides a unique solution to these challenges.
I’m a big fan of historical fiction and non-fiction – A Gentleman in Moscow by Amor Towles is one of my favorites. Currently, I’m reading a non-fiction book by Jimmy Soni titled “The Founders: Elon Musk, Peter Thiel and the Company that Made the Modern Internet “. Always looking for new suggestions though!
In terms of podcasts, I’ve started to listen to the WSJ What’s News podcast recently.
😂 – 🐐 – 🐿
Are you interested in joining a team like Sam describes? Read more about our cutting-edge technology and values here.
With all the buzz around Web3 and our soon-to-be officially launched Skylight application, it’s no wonder customers and partners have asked some incredibly thoughtful questions. So, we’re sharing our answers in a multi-part series with the best readership out there: YOU!
Let’s get right to it!
Question: You do a lot of work with the U.S. Department of Defense (DoD). That seems at odds with Web3’s decentralized and individual value. What’s the connection between the DoD and Web3?
That’s a fair question. It turns out that a lot of what is happening in the Web3 world is directly related to defense and vice versa.
In short, both consumers and the DoD have increasing data privacy and anonymity concerns. The DoD accepting our technology is great validation for consumers. If you can make the technology work for consumers, you can make it easy to use and scalable for the DoD.
People forget that the “crypto” in “cryptocurrency” is short for cryptography. So instead of thinking of a peer-to-peer financial transaction (e.g., you and me trading bitcoin directly) think of data as the asset using many of the same technologies.
A blockchain can store the record of the transaction. Smart contracts control under what conditions data is exchanged or analyzed. Zero-knowledge proofs verify anonymously that the data is what people say it is.
So, any time you want to keep data private and compartmentalized but also verify that it’s real, Web3 technologies have a huge advantage here.
An example is: you have 30 countries in NATO all of whom, now more than ever, need to share information about a conflict right on their doorstep … but … they don’t have integrated systems and, frankly, don’t even want to share all information with each other.
If you can securely share insights across 30 million users anonymously with Web3 technologies, then 30 intelligence agencies is not an issue at all.
In summary, we’re leveraging Web3 technologies to help consumers and validating the security and privacy elements with our DoD customers.
Appreciate the summary, but need to know more? Check out our Skylight page or better yet, send us a note: info@solvewithvia.com.
As we outlined in our most recent blog post, there’s massive pressure across the board to reduce energy costs and prevent power blackouts. For governments, utilities, industry, and many consumers, improving how we consume and manage energy has become a number one priority to maintain grid reliability.
One area that’s about to do its part to relieve this pressure is blockchain. Colloquially called “The Merge,” a long awaited change in the validation (or “consensus”) mechanism on Ethereum will be finalized in September.
By most calculations, the new upgrade will use roughly 2000x less energy than the current consensus mechanism. Like most innovations these days (e.g., speech recognition, file compression, self-driving cars), math is at the heart of this improvement.
The key change is in the “proofs.” In a completely decentralized and anonymous network, how can you verify that a transaction between two parties actually happened, when there’s no intermediary? For example, if you and I are trading bitcoin and one of us disagrees on the amount that got transferred, who do we go to as an arbiter? Different mathematical proofs are used to verify which transactions are real. In short, the current proof (proof-of-work) is greedy for energy and the new proof (proof-of-stake) has the same level of validity but is much more energy efficient.
This is good news for everyone. Not only will one of the most popular blockchain mechanisms significantly reduce its carbon footprint, transactions (e.g., minting NFTs, smart contracts) will be significantly cheaper as well. The timing couldn’t be better. As we’ve written about, the use of smart contracts and Zero-Knowledge Proofs have huge potential to support the transition to clean energy.
You’ll have seen a lot of blogs and posts from VIA recently about our work in Zero-Knowledge Proofs. We also use an energy efficient proof-of-stake approach, although our work is focused on creating proofs for energy data. Connections to Ethereum through oracles were in our original 2018 white paper and part of our roadmap. Until The Merge, however, VIA has had a private blockchain dedicated to a few users (e.g., U.S. DOD) for secure, digital asset custodial tracking. With the changes to a cheaper, more energy efficient Ethereum, we plan on leveraging EVMs post-Merge, for our newest applications.
To keep your lights on, the electric grid runs on one simple principle: power generation must be greater than power consumption.
While simple in principle, this is a challenge in practice. Consider the following headlines from the past 30 days:
Power is experiencing a perfect storm that’s impacting consumers the most (high prices and blackouts1). The challenges are global, although with regional variations.
In Europe, sanctions against Russia are limiting fuel supply that has led to fuel shortages, price spikes, and, worst of all, outages2. Compounding the supply issues is an aging generation and grid infrastructure. For example, France, normally self-sufficient or a net exporter of power, has 31 of its 57 nuclear power plants shut down due to unexpected maintenance3. This hits at a time when Europe and the U.S. are facing record heat waves4. As air conditioning is not as widespread in Europe, the bigger concern is that in a severe winter, when energy consumption generally doubles, outages will be even more widespread56.
In the U.S., sanctions against Russia have increased fuel prices but have not impacted supply directly. What’s more problematic is that while solar and wind generation is on the rise, connecting the power to the grid is slow, sometimes taking over a year, due to regulatory reviews and backlogs or the lack of energy capacity7. An aging infrastructure is also struggling to keep up with electrification. This is already having an impact in both New York and Texas as heat waves in the U.S. have been record breaking in temperature and duration.
To solve for this, many utilities are engaging their customers directly. The idea is that when consumers lower their electricity usage, they keep demand lower than supply. While many traditional businesses have done everything in their power to build a direct relationship with their customers, most consumers only know their utility through their monthly bill and when the lights go out.
Similar to how the first generation internet helped improve customer engagement (e.g., email, online billing, order tracking), we see Web3 as a way to bring grid operators closer to their customers through direct engagement on the transparency and tracking of their electricity usage. Technologies like Zero-Knowledge Proofs, smart contracts, and tokens can help grid operators incentivize, coordinate, and track individual consumer usage while maintaining complete data privacy.
You’ll have seen some of VIA’s tech stack already demonstrate some of this functionality through our blogs. In the coming weeks, we’ll be talking more about how VIA can provide a turn-key solution to power providers and grid operators.
This is the ninth installment of our blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.
Grid reliability requires thoughtful preventative maintenance and replacements of critical assets like substation transformers. With soaring retirement rates and a tough hiring market, many utilities are faced with making hard asset health decisions with limited time and historical knowledge.
Taking a step back
Take a minute to put yourself in the shoes of an asset manager.
You are responsible for creating multi-year asset plans to address grid infrastructure vulnerabilities and replacement strategies.
There are dozens of different pieces of equipment at each substation and knowing the performance and health of each asset is both an essential and ongoing challenge.
Utility Asset Manager
You, like many others on your team, rely on the expertise of long-standing experts in your company who have acquired years of insight into an asset. They can provide colorful context and guidance on what happened historically or how to interpret certain results.
Your most knowledgeable expert is set to retire at the end of the year. How will you transfer all the knowledge you don’t know? You don’t even know what you need to ask about certain assets!
To make the best use of your most valuable assets with years of knowledge, experience, and pattern recognition, you need a way to transfer that critical insight to the new workforce.
Navigating the realities of the times
With 50% of the utility workforce set to retire within the next 10 years, the electricity sector having difficulties hiring replacement personnel, and the vast amounts of experience and knowledge needed to have a deep understanding of asset performance and health, there is a potential looming threat to reliability efforts.
Thoughtful data analysis can help to address reliability challenges caused by limited organizational knowledge of transformer health.
Pooling the shared knowledge and analysis of a single utility’s transformer fleet with the analysis of other utilities’ transformer fleets allows you to predict the future health condition multiple years in advance.
How thoughtful analysis helps to ensure reliability
VIA’s Global Data Asset Collaborative™ (GDAC™) has all of the above ingredients to make thoughtful and accessible analysis to ensure reliability!
The web-based GDAC™ portal conveniently flags high risk transformers so that utility employees don’t have to manually aggregate and analyze data across multiple databases and reports.
The “Highest Risk Transformers” report flags transformers most at risk of failure.
With this insight, asset experts and strategic planners can filter and customize their searches on factors they are most interested in. Identifying early indicators of condition decline or trends in recent failures can be done in several clicks – giving utilities valuable time back when creating their asset management planning.
A transformer flagged for Dissolved Gas Analysis (DGA) concerns.
GDAC™ provides downloadable, visual reports so utilities can provide any supporting evidence to replacement recommendations, including private multi-utility benchmark comparisons. With this unique capability, utilities can see how the health of their individual transformers stack up against transformers owned by other utilities, like what you see below.
Want to expand your organization’s transformer knowledge base?
Reach out to me on LinkedIn or email sales@solvewithvia.com to set up some time to chat about how GDAC™ can help you plan for the future.
For the fourth installment of our “Open Source Monday” blog series, we provide a demonstration of a mathematical proof called zk-SNARK (an emerging Web3 standard) for energy data.
Today’s Open Source Monday blog is the culmination of a number of previous Web3 open source releases and blog posts.
First, frequent blog readers will know that we’re long-time believers in the potential of Web3 and its ability to accelerate the adoption of clean energy. Our blogs below make that clear:
These blog posts are in line with VIA’s mission to make communities cleaner, safer, and more equitable.
Second, we’ve been committed to creating the best tech stack that (1) supports the transition to clean energy and, at the same time, (2) maintains data privacy:
Finally, it’s clear that the “time is now” for the clean energy transition.
So, now that you’re caught up on the importance of Web3 at VIA, let’s get to the good stuff.
Today, we’re demonstrating a zk-SNARK version of our proof for meter data. For those zk-SNARK fans out there, we’ve got a short video for you that shows step-by-step the contracts and code we have created to verify consumer electricity meter data and maintain strict data privacy.
With the integration of this proof, VIA’s Skylight application enables energy consumers to profit from interest in their data, while keeping their identities completely anonymous. We’re excited that Skylight is ready to support consumers and power providers globally. Stay tuned for more exciting commercial announcements in the next month on this topic. In the meantime, you can find more details in our Skylight white paper.
Following the $1.2 trillion Infrastructure Investment and Jobs Act (or Bipartisan Infrastructure Law) last year, an additional $437 billion in Tuesday’s Inflation Reduction Act may seem like small change.
It’s not.
Unless you’re into the policy details like VIA is, one thing that may have gone under the radar is that there’s the potential to add billions of dollars to consumers’ wallets and purses each year. The reason isn’t the tax credits or incentives in the bill itself (although that’s certainly part of it).
There are two different pieces of legislation and regulation that are going to make this happen. The first is this week’s Inflation Reduction Act and second is FERC 2222. The rule came out a few years ago, but won’t go into full effect until 2023. This is a national (except Texas) rule that makes it possible for pretty much anyone to participate in the wholesale energy markets.
Wait, wholesale what?
In short, FERC 2222 says that consumers of a certain size (individually or aggregated together) can buy and sell energy at the same price that a multi-billion dollar company can. Up until now, most consumers were paid or saved whatever their going retail rate was (e.g., $0.15 to $0.30 per kWh) for reducing their consumption, shifting the time of their consumption, or selling their generation (e.g., solar) back to the grid. While not nothing, wholesale electricity rates can fluctuate dramatically. For example, during emergencies, wholesale prices can be MUCH higher (e.g., $20 per kWh). Those volatile, skyrocketing prices are becoming more frequent and lasting longer. We’ll actually be talking about the drivers of that volatility in an upcoming blog post.
The impact is that, by some estimates, a consumer could earn $500 to $1,000 (your mileage may vary) per year through various demand response programs. That’s with retail pricing. With wholesale rates, those cash payments will be significantly higher.
So that’s FERC 2222. What’s the connection to the Inflation Reduction Act?
Well, a lot of incentives are in place for consumers to upgrade to electric heat pumps, add solar, add EVs, and upgrade appliances. Anything new has the potential to be “smart.” That is, remote controlled so it can automate the process of turning on or off when needed. Like during an emergency.
The combination of new “smart equipment” purchased through the Inflation Reduction Act and FERC 2222 mean greater incentives and lower barriers to adoption (automated transactions instead of manual transactions).
If you follow the news, there’s been some backlash against the idea of having a company, like a utility, remote controlling the appliances in your home.
We agree. That’s why we believe so strongly in our new Web3 solution, Skylight.
Three key benefits of VIA’s Skylight value proposition are:
So, overall, we’re pretty excited about the combination of events playing out right now. For savvy consumers, there’s HUGE potential for additional income and you don’t even need your tax accountant to help you out.
Of course, we’re equally excited that the regulatory direction is in line with VIA’s overall mission to make communities cleaner, safer, and more equitable.
Stay tuned for more upcoming announcements from VIA on this topic.
This is the seventh installment of our blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.
Electric utilities have a hard job. They have to ensure reliability to their customers in the midst of:
With constrained budgets, rising transformer costs, and longer lead times, how can utilities ensure they accurately prioritize the right transformer replacements now and in the future?
GDAC™ provides utilities with the tools needed to precisely prioritize transformer replacement
There is a cost effective solution that provides utilities with insights into the current and projected health of transformers at a cost any utility can afford: VIA’s Global Data Asset Collaborative™ (GDAC™).
GDAC™ provides a secure way for utilities to pool data about their transformers (including data from measurement tests like dissolved gas analysis, oil, and furan) without compromising data privacy. By pooling data from multiple utilities, the key differentiator of GDAC™, robust quantities of data are made available for artificial intelligence (AI) to train accurate models to predict transformer health 1-10 years in advance.
GDAC™ leverages a completely transparent Condition Based Rating (CBR) system that is based on industry standards and was co-created and validated by our founding utility partners. This gives asset managers confidence in how the rating is created and helps make it easier to interpret what to do with the results.
All of these insights are made available to asset managers in one place, in the convenience of a web-based portal. Some example reports from the GDAC™ portal that our current members love:
Utilities can use the 10-Year Condition Forecast report for a bird’s eye view of their fleet’s health, compared to other GDAC™ partners.
For more actionable granularity, GDAC™’s Highest Risk Transformers page flags individual transformers that currently have issues and are forecasted to decline over the next 3 years.
Want to accurately assess your transformers current and future condition?
Send me a note on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.
This is the sixth installment of our blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.
For 50 years, substation transformers were built to run during the day and taper down at night to cool. Now, picture your neighborhood lined with electric vehicles (EVs). Once your neighbors end their workdays and don’t need to use their vehicles anymore, they plug their EVs in to “juice up”.
While this is convenient for EV drivers, this significantly increased demand for evening voltage places additional wear-and-tear on the electricity grid during times when transformers are used to cooling down. In this scenario, transformers stay running and can overheat or experience a malfunction (not unlike a car if you think about it).
According to a 2021 McKinsey report, U.S. EV sales increased by nearly 200% between the second quarter of 2020 and the second quarter 2021. This number is expected to rise as a result of $7.5 billion EV infrastructure funding from the Bipartisan Infrastructure Investment and Jobs Act.
Growing fleets of EVs will clearly require utilities to expand their power capacity, and therefore, optimize or add transformers to handle more intense power requirements throughout the day and evening. This leads to critical questions like:
Which transformers should a utility repair, replace, or buy to add to their grids first?
Which units and future plans can wait?
How much will all of this cost?
Utility asset managers need to understand which transformers in their fleet are most at risk as EV penetration increases. VIA’s Global Data Asset Collaborative™ (GDAC™) can help.
Engaging with EV Stressors
Despite higher rates of EV adoption and challenges related to where and when EVs are being charged, utilities need to maintain the highest standards for electricity reliability and resiliency for their customers. GDAC™ identifies cases where transformers have unexpected declines in health condition, at an early age or in an area where previous transformer condition was consistent. These situations are good indicators to intervene sooner or review the assets in place.
Utilities analyze historical and forecasted transformer condition changes (e.g., downgrades) in locations where EV adoption is high.
The GDAC™ portal conveniently flags high risk transformers for utilities so that they don’t have to parse through multiple databases, reports, and analyses, saving them invaluable time and effort. As a result, utilities can allocate resources to the transformers most in need, allowing them to work smarter.
As shown in the diagram to the left, utilities easily identify transformers in need of maintenance or replacement due to EV-related stressors. Utilities also glean insights from transformers located at the same substation experiencing similar EV stressors.
GDAC™ analyses like these help utility personnel with or without analysis experience to identify which transformers to repair, replace, or buy; which units and future plans can wait; and how much it will cost to address EV-related stressors.
Want to go for a ride with GDAC™?
Reach out to me via LinkedIn or email sales@solvewithvia.com to learn more about the ways GDAC™ can help you be prepared for EV-related stressors on your transformer fleet.
One of VIA’s core values is: learning never goes out of style. We believe that real learning (e.g., a new instrument, a new sport, a new programming language) requires feedback from others.
At VIA, we use a common process of pull requests to review code. That is, no individual, no matter what role or how senior, can submit their code to a repo without having it first reviewed by someone else.
But, how do you give feedback directly and also respectfully? This is an example of living two VIA values: Learning never goes out of style and Respect a challenge and challenge with respect. Balancing directness and respect is especially important in a remote working world, where an increasing portion of interactions may be virtual (e.g., on Slack), which doesn’t include any context or body language cues.
Consider the following comment: “Interesting. Why did you code this way?”
Is the commenter genuinely interested in knowing why? Is it a rhetorical question actually implying that it’s wrong? You can’t tell from the note. You also can’t guarantee how it will be interpreted by the reader.
You could provide more context, but that’s work and even then something can get misinterpreted.
So … At VIA, we use four words to help disambiguate these scenarios and save time.
| VIA VOCAB WORD | MEANING |
|---|---|
| Optional | “Nice! Here’s an alternative. No pressure. There are always multiple ways to solve a problem.” |
| Curiosity | “This rocks! How did you come up with this?” |
| Required | “Dude, this has to change.” |
| Future | “Not right now. Let’s come back to this later.” |
The result? Clear feedback, succinct communication, and no emotional damage.
This is critically important at a hugely diverse company like VIA. We have team members right out of academia, folks from industry with little academic training, folks from numerous nationalities, and 86% of our technical team speak at least one language other than English.
“These “VIA vocab” words are meant to move us beyond seeking diversity at work to getting diversity to work. With this approach, we have a better chance of achieving the intended impact of diversity like an increased pace of innovation.”
Consistent with VIA’s mission to enable cleaner, safer, and more equitable communities, we are “open sourcing” our VIA vocab in hopes of encouraging others to make diversity work for them.
You can find a summary and example on GitHub.
This is the fifth installment of our new blog series, “Transformer Tuesday,” brought to you today by VIA’s SVP, Strategic Initiatives, Joe Babiec. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.
Last week’s Transformer Tuesday post by my colleague, Will Chapman, highlighted the way GDAC™ member utilities can learn from each other’s experiences. In particular, joining GDAC™ can help a utility prepare for challenges that they haven’t yet had to solve for or frequently experienced in their own transformer fleet. This shared knowledge not only helps utilities learn from each other, but can also help save on costly transformer failures.
This week, we want to highlight the value a specific GDAC™ member, Hawaiian Electric, brings to the entire collaborative.
Hawaiian Electric is one of GDAC™’s founding member utilities. The company serves 95% of Hawaiʻi’s 1.4 million residents on the islands of Oʻahu, Hawaiʻi Island, Maui, Lānaʻi, and Molokaʻi.
Hawaiian Electric has been referred to in the industry as a “postcard from the future.” With very high levels of distributed solar penetration, they are rapidly transforming their grid to provide 100% renewable energy by 2045. Hawaiian Electric has already accumulated considerable experience dealing with a host of unprecedented challenges related to clean energy that many in the industry will not face for several years. Utility Dive recognized Hawaiian Electric’s trailblazing efforts and named the company “Utility of the Year.”
Hawaiian Electric has been contributing valuable insights on substation transformers to the collaborative since 2019. Having their experience included in GDAC™’s many benchmarks allows other utilities to better anticipate how their transformers might behave and how long they might last, as a result of accelerating clean energy technology adoption in their service areas.
In addition to enabling valuable benchmarking, Hawaiian Electric, like other GDAC™ members, is sharing their hard-won operational insights during VIA-hosted GDAC™ workshops. Topics often include fleet management practices, plans, and challenges, as well as the future GDAC™ enhancements that would provide the most value to all utilities.
Hawaiian Electric illustrated the value of the collaborative best themselves:
“Like most electric utilities, Hawaiian Electric does its best to maximize use of grid infrastructure, some of which are nearing the end of their practical use,” said Rick Pinkerton, Director, Asset Management at Hawaiian Electric. “As we modernize our grid, we’re always looking for ways to improve our decision making. We joined GDAC™ to learn from other members and from VIA’s expertise in AI and machine learning, to improve our capabilities to prudently manage the performance, risk, and cost of our fleet of substation transformers, and other T&D assets in general.”
If you would like to learn about how GDAC™ can help your utility to “future proof” by learning from the experience of trailblazing companies like Hawaiian Electric, reach out to me on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.
This is the third installment of our new blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.
Aging electric grid components threaten the reliable, safe delivery of electricity. With substation transformer costs ranging anywhere from a few hundred thousand dollars to more than $5 million, the decision to replace these assets requires careful long-term capital investment planning. Unexpected transformer failures can upset those plans and requesting regulators to revise a utility’s rate case is not quick or guaranteed.
Here is an example of a situation that can arise when a transformer fails suddenly. If, say, Transformer 1 fails, a utility can decide to redeploy funds originally planned for the replacement of Transformer 2 into emergency purchasing of a brand new, Transformer 3. The result of this decision is that the utility needs to find a way to extend the lifespan of Transformer 2 since funds allocated to replace this transformer have gone to purchasing a new one.
So, how do utilities typically solve dilemmas like these and others?
Performing consistent maintenance is a sensible approach because aging transformers can have their lifespan extended, and it helps to defer replacement spending. To guide their maintenance work, utilities turn to predictive analytics to detect which transformers are at the greatest risk of failure. There are some helpful analytics that exist in the marketplace, however, there is a catch to predictive analytics: to be effective, they need a sufficient amount of data about transformers during normal periods of operation and leading up to faults and failure events.
Events like substation transformer failures don’t happen frequently (thankfully). But, utilities with too few failure events may not have a sufficient amount of transformer data on their own to train accurate predictive models, like Utility A on the left of the diagram below.
In principle, Utility A could address this challenge of data scarcity by exchanging data with other utilities so each utility has enough data to train and apply their predictive models and benchmarks, as shown on the chart to the right above. However, in practice, sharing sensitive operational data with other organizations presents serious privacy and security risks. Even if those risks are managed, utilities often keep their data in different or even incompatible formats. Utilities can find themselves needing so much time accessing and preparing data for analysis that they lack timely insights or have to abandon predictive analysis altogether.
VIA’s Global Data Asset Collaborative™ (GDAC™) overcomes these problems.
The Bridge to Predictive Insights
GDAC™ solves for each of the obstacles mentioned above: data scarcity, data privacy and security risks, and different data formats. With GDAC™, each utility retains complete control of its data and is able to connect to utility-controlled data locations. The collaborative does this by establishing a secure, privacy-protecting bridge between each company’s data and GDAC™ predictive analytics.
Leveraging GDAC™, utilities can prevent unanticipated transformer failures by:
With GDAC™ (pictured above), utilities can forecast individual transformer health anywhere from 1 to 3 years in advance.
By using GDAC™, utilities share access to, not copies of, valuable transformer data and learn from the combined valuable experiences with faults and failures. This enables GDAC™ member utilities to reliably predict transformer failures and minimize unexpected replacement scenarios.
Want to expand your transformer knowledge base?
Reach out to me on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.
For the third installment of our “Open Source Monday” blog series, we provide a demonstration and example code of how Zero-Knowledge Proofs can be applied to clean energy applications.
Zero-Knowledge Proofs (ZKPs) will be very familiar to blockchain experts and cryptocurrency enthusiasts. As we described last week, there are also non-financial applications for ZKPs in the clean energy sector.
Imagine that you are an electric vehicle charging station company. You collect data from charging stations that have a huge amount of individual information. You collect and centralize that data for billing and maintenance. Some of the data could even be considered personally identifiable information. That is, time, location, vehicle type, etc. could be pieced together to identify an individual even without having a specific name of a person.
In summary, your data is valuable. Others ask for it. The local utility wants access to help plan grid upgrades. The local government wants to use it to plan public transportation. Community groups want access to learn the impact on the environment. Do you hand over your data to them? A better approach would be to enable them to ask questions of your data in an anonymized way without you physically transferring the data. Fewer copies means less risk.
As an energy planner (e.g., utility, government, community group) how do I know the data is real if I never see it? This is where ZKPs come in. ZKPs can prove that the data is as expected without having to reveal the actual data itself.
The video below shows an example of some of the steps to accomplish this.
What you’ll see is:
For our implementation, we take advantage of some recent advances in ZKPs. In particular, many ZKPs rely on some interaction with a prover and a verifier. They ask each other a series of questions to validate the data. Here, we apply an approach inspired by zk-SNARKs. The “N” in SNARK is for Non-Interactive. The genius behind this approach is that all the proof can be provided in a single message to the verifier, eliminating the traditional back and forth. There is a LOT of math behind this which is out of scope for our example. You can learn more about the math and how it works thanks to Zcash. For simplicity in this example (see GitHub), we use a simple hash implementation rather than a full zk-SNARK.
One other addition that we made here is that since the proof is a simple message, we can codify it as an image. We can then mint the image as an NFT. The big advantage of this approach is that proofs are visible to everyone and searchable by anyone on a platform like OpenSea or Coinbase without revealing any individual data. This removes a transaction headache for the data owner. They don’t need a new system or special hosting, etc. to handle inquiries about their data.
And, the last addition, is that we have an example Polygon smart contract that enables an individual to validate their own dataset. What the validation code enables is that the EV charging company and / or energy planners who incentivize data owners to validate data get greater assurance that the data is real. This is a great use case of data privacy enabled through crypto.
The basic principles here can be applied to many sectors where there is centralized off-chain data, strict data privacy needs, and a need to prove the data is valid. Next week, you’ll see an expansion of this proof to leverage more of the zk-SNARK stack.
This is the second installment of our blog series, “Mastery Monday with VIA” where we share with you some of the inside details of our technology and math in 5 minutes or less. So, are you ready to become a master?
Math impacts everything we do. You never really see the math, but you experience it.
AI is the math that helps us control our TVs with our voice and drive our Teslas. We watch Netflix and listen to Spotify, courtesy of compression algorithms that send more and more data through increasingly crowded bandwidth.
One of the invisible math innovations that is changing the world is Zero-Knowledge Proofs or ZKPs.
If you’re not familiar with ZKPs, these videos from UCLA Professor Amit Sahai and Up and Atom do an excellent job of explaining the concept easily. We particularly like how Prof. Sahai gets a 5 year old and a 13 year old to repeat back his definition of a ZKP, after he explains it. It’s a testament to great teaching.
So, why should you care about ZKPs?
The short answer is that if you care about privacy and fairness, then you care about ZKPs. It’s the math for you.
For example, ZKPs are used every day by millions of people in bitcoin and other cryptocurrency trading. It’s how two parties who don’t know each other can verify that the right amount of funds were transferred from one to another without the need of an intermediary like a bank. There are other, non-financial uses of ZKPs, as well.
Given VIA’s mission to enable cleaner, safer, and more equitable communities, let’s use an example from the clean energy sector. VIA blog readers will know that our software platform enables energy data to be analyzed in such a way that an analyst will never see the source data (read more about that here).
This has obvious data privacy benefits to the data owner. Data owners don’t have to physically transfer their data to anyone or let an analyst see it in any way.
But, what about the analysts? How do they know that the data is legit?
Well, one way is that an analyst could just trust the data owner. That works well if you both know the data owner and believe that they are reputable. For example, if you know the data owner is your public utility, and trust them, then as an analyst, you may say, “the data must be OK.”
What if the data owner isn’t someone you trust? They don’t necessarily have to be “untrustworthy.” You just don’t know them. So, the new energy retailer in your neighborhood, or the EV charging station start-up, or the microgrid operator may be perfectly legitimate. But, how do you know? How can you make sure they are playing fair?
This is where ZKPs come in. You don’t have to know. You don’t have to trust them. With ZKPs, you can mathematically verify that the data stored by the utility corresponds to the data offered to the analyst. Also, ZKPs, given a verifier, enable us to validate that the values of the data provided by the utility are indeed what the verifier is expecting.
To take the example even further, think about consumer data. Energy is decentralizing rapidly to the individual level (e.g., rooftop solar and EVs). Your energy data is literally personally identifiable information so data privacy is paramount. At the same, you can’t possibly know and trust every other individual consumer as a data owner. ZKPs can address this.
So, is there a ZKP for energy data that energy analysts can use? Stay tuned for next week’s post …