Let’s TAC™ About It: Digital Watermarking

For the fourth installment of our blog series, we will cover TAC™’s digital watermarking functionality. So, are you ready to TAC™ about it?

For centuries, watermarks have been used to verify currencies and important documents and to discourage counterfeiting. Today, watermarks are used for the same purpose to protect music, photos, videos, software, and other digital data.

The main goal of our TAC™ platform is to keep data private by not transferring data. Having said that, there are times when it is necessary (e.g., for audit or regulatory purposes) to transfer some data between trusted parties. 

At VIA, we use watermarking to enable data auditability when data owners choose to transfer data. For example, two organizations can receive identical datasets. If it is later found that data has been leaked, the data owner can review the leaked data and trace it back to the original analyst that requested it.

TAC™ provides the option to digitally watermark a dataset.

TAC™ automates the process of maintaining the provenance of data. As long as the data was transferred using TAC™, no additional steps are required by the data owner and there is no noticeable difference to analysts.

Watermarking is a simple and automatic method to provide auditability to data.

Introducing SWEET: AI for Data Wrangling

For the third installment of our blog series, Let’s TAC™ About It, we’d like to introduce you to SWEET, a built-in function on VIA’s TAC™ platform. So, are you ready to TAC™ about it?

SWEET stands for Smart Wrangling Engine for Extraction and Transformation. Check out the video (or the transcription that follows) to learn how we use AI to wrangle data!

Below is a transcription of the “Introduction to SWEET: AI for Data Wrangling” video.

Analysts need to transfer data from a spreadsheet to a database, often known as data wrangling. The analyst usually identifies a rule or multiple rules (such as: column x is data, row 5 is a header and can be discarded, and so on). The analyst then writes code to execute that rule. This works well when rules are easily identifiable. In most cases, however, this is incredibly time consuming.

Data scientists spend more time wrangling and cleaning data than on analysis and AI. The problem with that is analytics insights are of the highest value, but get the least amount of resources. The big leap in AI is being able to process information without humans writing all the rules.

As an example, computer vision is used to identify a dog. Think of all the varieties of dogs and all the possible variations in context that those dogs could be in. There isn’t an army of people large enough to write rules to identify a random dog in a random photo.

And yet, AI can.

VIA’s approach to data wrangling is to use some of the exact same AI algorithms used in image recognition. This works across a much wider variety of contexts and spreadsheet or file formats. Let’s take a look at how SWEET works.

Here’s a spreadsheet. What SWEET is going to do is use a number of different machine learning algorithms to automate the process of getting the information into a database format.

The first model uses machine vision to map out the spreadsheet. Purple represents blank space, green is headings, yellow is actual data. Once that model has run, there’s a second algorithm that takes a look at the content.

The second algorithm skips over the purple. It looks at the green (which is the headers) to know which column to write where in the database. Finally, it would take a look at the yellow area to write the data to the database.

A third machine learning algorithm determines which column is derived from other parts of the sheet. For example, a total column is just the sum of the other columns and may not be necessary to write to the database. The third model separates these derived columns from the raw data.

In this example, the ACCOUNT column turns out to be the total of the other columns added up. It could be difficult for a human to understand immediately, but one of our models does this instantly.

SWEET’s approach works irrespective of the format. The model doesn’t have to be re-trained when it comes across spreadsheets that are new or in different formats.

So, what’s new and different here? AI algorithms have been evolving quickly. Many of the models that we implemented didn’t exist just a few years ago.

The other insight is that we broke the “convert this spreadsheet into a db” problem into multiple steps and have a different AI algorithm for each step.

Combined, SWEET, a built-in function in VIA’s TAC™ ingestion engine, helps make processes that used to take analysts days to do manually and makes them instantaneous.

Update: July 31, 2020

The image below shows the steps SWEET takes to transform raw files into a standard format.

Meet the Team: Ashley DaSilva, Team Leader, Product Development

Through a Q&A-style interview, you will hear from VIA team members about things like a typical day at the office and favorite foods.

What does a typical day at VIA look like for you?

Typically I start my morning with coffee and code review. At VIA, we have a strong culture of peer review to help us learn from each other and improve our work. Reviewing my colleagues’ code is a good way to see all the amazing work my colleagues are doing, and setting aside this time makes sure I provide them timely feedback.

Once I’ve finished my coffee, I like to take a morning walk (before we moved to remote work due to COVID-19, this was the time I spent commuting to the office.) The rest of the day varies depending on the project I’m working on: it could be writing a software design proposal for a new feature, wrangling data, or automating deployments.

I spend a lot of my day working with my colleagues to solve technical challenges. Often this is pair programming, but sometimes it’s designing the solution together on a (virtual) whiteboard. I really like having the opportunity to work on such a variety of tasks.

What’s something you have worked on at VIA that you are most proud of?

I was the technical lead on VIA’s 30-Minute Pilot and am really proud of how much of a difference it has made for our partners. They were able to get valuable data analysis in less than 30 minutes, while learning about VIA’s privacy-protecting software.

What’s your favorite VIA memory?

At our last company-wide All Hands event, we did a scavenger hunt in the underground city of Montreal. It really fit VIA’s culture: we were split into teams, and each team had to collaborate to solve the puzzles and at the same time, we were competing to solve more puzzles than the other teams! I got to know a little more about Montreal, and got to collaborate with colleagues that I don’t work with day-to-day.

If you were given an extra hour in your day, what would you spend it doing?

That’s a tough one. I would probably practice painting. I love creating things, and that passion is not limited to software. I love the bright colors and rich textures of oil paints, and the challenge of exercising my creativity in a totally different way than I do at work.

What’s your go-to food?

Tacos! Since moving to Montreal, I have learned how to make corn tortillas from scratch, which is actually much easier than I thought it would be.

What’s something everyone may not, but should know about working at VIA?

VIA’s twice yearly All Hands events are held in an “unconference” style: all team members submit and vote on topics just a couple days ahead of time. Because everyone has input into the topics, and the fact that there’s not much time for session leaders to prepare a lot of talking points, the sessions focus on discussion, collaboration, and brainstorming.

Let’s TAC™ About It: Models for Private Data Service

For the second installment of our blog series, we will cover VIA’s Models for Private Data (MPD) service. So, are you ready to TAC™ about it?

Companies are awash with data. To make sense of the growing data volume, AI models continue to proliferate in number and improve in performance. Even better, many of the best models are open sourced. Leading companies like Amazon, Google, Microsoft, and others have made freely available AI models for everything from facial recognition to text analysis. 

So, why aren’t more companies taking advantage of these models for analysis of their corporate data?

One of the top challenges is data privacy. Many companies are fearful of sending their data to the cloud or to an external AI provider. Data and AI regulations from Europe (GDPR) to California (CCPA) are complex to navigate. Even without government oversight, companies worry about the reputational cost of a real or perceived privacy violation. 

VIA’s TAC™ platform solves this with its Models for Private Data (MPD) service. 

TAC™’s MPD service makes machine learning models available for download and easy incorporation into data science workflows. This has the dual benefit of eliminating the need to send data outside the organization or to the cloud and also the need to have internal AI experts to run state of the art machine learning models. The result is that data is kept private and secure.

As an example, imagine a company capturing images about their equipment to identify corrosion. Through TAC™’s MPD service, a data scientist can choose a corrosion analysis model (e.g., a pre-trained TensorFlow algorithm) and easily incorporate that model into their workflow. The MPD service accomplishes this by using containers to make the models easily accessible through their Python scripts. The models use input from their local databases and return a list of predictions locally. Data remains on premise in their local VPC at all times. This is one way that we keep data private across our Global Data Asset Collaborative™ (GDAC™) with multiple energy utilities.

Stay tuned for a video demo of this service in the coming weeks!

Need a laugh?

We’re back at it – this time giving you some laughs from our remote team. See our video below for the funniest moments since working remotely.



Meet the Team: Annvie Nguyen, UX Designer

Through a Q&A-style interview, you will hear from VIA team members about things like a typical day at the office and favorite foods.

What does a typical day at VIA look like for you?

The only typical part about my days at VIA is that it changes every day! As the go-to media person, I’m lucky to have the opportunity to collaborate with different teams and work on a variety of projects. Some days, I’ll be working on filming and editing videos for VIA (check out the careers video produced by yours truly). Others, I’ll get to flex my design eye and work with our developers to create user interfaces for our products. Today, I’m updating our website and writing a fabulous blog.

What’s something you have worked on at VIA that you are most proud of?

There are so many cool things I want to talk about, it’s difficult to choose!

For one, I really enjoyed working on the interface for the GDAC™ Transformers  30-Minute Pilot. In that project, I designed the user experience for a data analysis demo. It presented an interesting challenge: how can we make complex analysis simple for others to understand, operate by themselves, and see the value? I was able to participate from the conceptualization stage all the way to the user interface and experience. It was so rewarding to see the pilot go from its baby stages to a full-fledged site.

What’s your favorite VIA memory?

My favorite VIA memory might have to be this past holiday party. We made gingerbread houses, ate some delicious desserts (essential to the VIA brand), and played a ridiculous reindeer ring toss game that had us crying with laughter. Hats off to Jackie for being our star party planner!



If you were given an extra hour in your day, what would you spend it doing?

I can’t deny that I’d be playing Animal Crossing on Nintendo.

What’s your go-to food?

Nothing can outrank my comfort food of choice: a nice, warm bowl of pho. It’s Vietnam’s most famous noodle soup, light but also flavorful. But to me, it’s like getting a hug from Grandma.

What’s something everyone may not, but should know about working at VIA?

You should know that at VIA we’re always working on improving ourselves. With retrospectives at the end of each sprint, open ears during one-on-one’s, and offsites each year, being open to feedback is an essential part of VIA culture.

Working Remotely? Us too!

Along with people all over the world, the VIA team has adjusted to a new normal over these last few months. 

Given our distance apart, we asked some of our team members what they look forward to each day of working remotely.

Check out our video below to see what our team has to say (spoiler: this will give you all the feels!)



Meet the Team: Emma Fechney, Senior Lead, People and Operations

Through a Q&A-style interview, you will hear from VIA team members about things like a typical day at the office and favorite foods.

What does a typical day at VIA look like for you?

One of the things that I love about my job is that for me, there is no such thing as a “typical day.” Because my role encompasses the entire candidate and employee experience, there are often lots of different projects going on at any moment. Examples include planning recruitment events, working with the team on our professional development program, or even ordering a whole lot of pizza for our regular lunch and learn sessions.

I always try to start my day by consulting my to do’s and then from there, it can be a mixture of meetings, catch-ups with team members, interviews, or planning the next team event.

What motivates you to come to the office each day?

People! I am motivated by the idea of enhancing people’s work experience, whether it’s exploring ways to support professional development or strengthening the connection between our team and our vision. Plus, finding ways to celebrate and have fun together never gets old!

What’s something you have worked on at VIA that you are most proud of?

Introducing Lattice, our performance management platform, was a big win for me. Lattice is a tool that helps us plan and track goals, organise 1:1’s, and is an excellent vehicle for supporting a feedback-rich culture. We love the integration with our #shoutouts channel on Slack for constant praise and appreciation! (Not a paid plug, I promise).

What’s your favorite VIA memory?

My first official day is something that sticks out. Not only were lots of pastries involved, but the whole office pushed pause in whatever they were doing to welcome me over breakfast and to get to know more about me and my background. This really set the tone of inclusivity and respect that has not faded since!

If you were given an extra hour in your day, what would you spend it doing?

The angel on my shoulder says learning french, but the devil on the other says catching up on some z’s.

What’s your go-to food?

I can’t go past a really good Kiwi meat pie!

What’s something everyone may not, but should know about working at VIA?

In addition to being a kick-ass energy tech company, our team could have a side career in the food industry. Everyone is either an excellent home cook and/or just genuinely enjoys the ritual of eating great food.

Meet the Team: John Muddle, Team Lead, Data Science

Through a Q&A-style interview, you will hear from VIA team members about things like a typical day at the office and favorite foods.

What does a typical day at VIA look like for you?

My typical workday starts with a coffee, from either one of the local third-wave coffee shops or the machine at work. Once I’m settled, I look at my calendar and plan my day, this can be anything from looking at notes from a previous meeting to making sure I’ve booked a room. When that’s complete, I look for something I can quickly finish before Scrum of Scrums or continue with the task from the day before.

Each day at 10:30, I attend Scrum of Scrums. As a technical lead, I need to know how my epic is progressing, so typically, I will check in with my colleagues before the meeting for any updates and check that the JIRA board reflects our current progress. Typically, there are a few meetings to take a deeper dive on topics raised at Scrum of Scrums. These are a great way to make sure that we are aligned across our epics and to share knowledge. 

Having conditioned myself over many years that 12 o’clock means lunchtime, I take a break at 12 to either buy lunch or heat up some leftovers. Lunch is a great opportunity to socialize with my colleagues on different epics and to give my brain some time to process in the background. Conversations range from the latest computer game, movies, and hockey, but mostly food. 

After lunch, my afternoons consist of meetings, customer calls, and development time. My time tends to be split into hour-long chunks which I’ve planned out in the morning. A lot of my work revolves around supporting my colleagues by answering questions, problem-solving, and pair-programming. One of the favourite ways to tackle a problem is to jump into a spare room and rubber duck the problem. Basically, by describing a problem to a rubber duck, you verbalise the issues you are facing and through this process, you tend to have a better understanding of your problem. Luckily, VIA has hired people rather than rubber ducks, so in fact, you can also get feedback, questions, and suggestions from your colleagues. 

At the end of the day, which is typically signaled by the sending of GIFs on Slack that it’s home time, I make sure to leave my work in a state that allows me to continue the next day.

What’s something you have worked on at VIA that you are most proud of?

At VIA, I have had the opportunity to work on many different projects. I’m proud of every single one of them, but if I have to choose one, then I am most proud of the GDAC™ Transformers project. The reason I have chosen this project is because it is the first application built on top of TAC™. I’m proud to have helped develop TAC™, but it’s even better to use it for the benefit of our partners. The partnership aspect is another element that makes me proud to have worked on GDAC™ Transformers. I have worked closely with our partners for almost a year and to see how far we’ve come together is fantastic. Having had the opportunity to meet our partners in person, I was able to see how the work we have done together will benefit them going forward.

What’s your favorite VIA memory?

VIA is a great place to work, I have so many memories from my time here. One that stands out to me, in particular, was “Game Night”. Each offsite (a company-wide in-person event where we talk about wins, solve project challenges, and plan for the next big thing) typically has an activity where we have a chance to socialize such as bowling, mini-golf, and a scavenger hunt. But, nothing quite beats seeing your own office converted, in-secret, to the ultimate “Game Night” experience to the point where it is almost unrecognizable and something I will never forget.

If you were given an extra hour in your day, what would you spend it doing?

One thing I say to myself quite often is “If only I had more time”, but what would I do with that extra time. If I had an extra hour in my day, I would like to improve my French. Montreal is a fantastic bilingual city and very little French is actually necessary, but to really appreciate its culture and to get the full Quebecois experience a good handle on French is essential.

What’s your go-to food?

My go-to food has to be a sandwich, you can’t beat the convenience, variety, and taste of a good sandwich. In particular, I’m a big fan of a bacon butty, which, for those of you who are unfamiliar, is a very basic sandwich with bacon and butter filling. Bacon buttys tend to be eaten in the morning at home or out and about. They are an excellent way to start the day if camping, at a sports event, or just a day of gardening.

What’s something everyone may not, but should know about working at VIA?

If you have the pleasure of working at VIA then you should know that using GIFs in presentations and on Slack is encouraged. Communicating context and meaning using just text can be difficult at times, but GIFs can add so much more. A strong GIF game is essential to signal it’s time to go home, go to the pub, play badminton, get bread, or celebrate the latest prize that VIA has won.



The End of Pilot Purgatory

We’re excited to have Andrew Bright, former ABB executive and VIA’s newest advisor, contribute to our blog. Read on to hear his commentary on one of VIA’s latest products, GDAC™ Transformers: 30-Minute Pilot.

Many industrial digitalization projects suffer from “Pilot Purgatory.” The pilots seemingly take forever and never end because no one can decide if they are a success or a failure. Since the term Pilot Purgatory was first coined a few years ago, much has been written about how to avoid it. However, the vast majority of this advice seems to involve throwing more resources, money and scale at the pilot, until well it no longer looks like a pilot but a full-scale roll-out. The logic is clear if the monthly cost of a pilot project is high enough – no one can afford to let the pilot continue indefinitely. How refreshing then, that VIA has come up with a radically different and frankly opposing approach for avoiding Pilot Purgatory. 

Their new GDAC™ Transformers: 30-Minute Pilot takes just 30 minutes, and most of this time is allocated to data gathering. If this were a recipe, you would be allowed up to 27 minutes to source the ingredients and just 3 minutes to do the cooking. Resources, time and money are all minimized. After 30 minutes VIA hopes to have delivered a valuable summary of the health of one of your transformers. If this has proved insightful, the pilot has been a success, if not then GDAC™ may not be for you. Either way, the pilot will have been concluded.

With their 30-Minute Pilot, VIA aims to demonstrate three specific concepts:

  1. show valuable insights about the health of one transformer and that the math really works;
  2. show that valuable analysis can be conducted whilst keeping data private and confidential; and
  3. provide an educational component about how VIA does what it does. VIA does more than provide recommendations, it also explains why & how a particular recommendation was made.

All three of these components are embedded in the 30-Minute Pilot. If you are interested in performing a full fleet analysis going back say 20 years, that’s more of a project and not the goal of this pilot. VIA’s 30-Minute Pilot is true to the spirit and literal about the term “proof-of-concept.” This seems to be an industry first and given the simplicity and radical reduction in resources, I hope that it becomes an industry standard approach.

VIA note:

If you are interested in learning more about VIA’s GDAC™ Transformers: 30-Minute Pilot and perhaps want to give it a try, feel free to contact us.



Meet the Team: Antoine Dozois, Software Developer

We’re thrilled to launch a new blog series at VIA called “Meet the Team.” Through a Q&A-style interview, you will hear from VIA team members about things like a typical day at the office and favorite foods.

What does a typical day at VIA look like for you?

Like most startups, we are working on lots of exciting projects. Here are some of the challenges that I’m involved in on a daily basis.

  1. Infrastructure: This means having the right data storage and resources through AWS necessary for our workloads. This is in constant evolution because every new project or project phase has different needs. So, we always look for improvements ranging from storage capacity and ease of use to performance and access management.
  2. Data (management, cleaning, processing): To deliver the best AI solution, data needs to be widely available, in the proper format, with good workflow, and overall managed well. This part of the work is more around trying to structure the workflow and the processes involved in the team’s recurrent tasks. We also need to understand the data to manipulate it and find insights that are most relevant for our customers and internal teams.
  3. Building software to empower the team: Software can be built to access data, compute some metrics, build a machine learning model, or display some insight. We build libraries to help us automate and optimize our workflow. Overall, we are always trying to create efficiencies internally through streamlining and automating recurring tasks.
  4. Collaborating with the team: This relates to reviewing code, meeting to organize our work, and helping each other when needed.

What’s something you have worked on at VIA that you are most proud of?

It is hard to pick just one piece of work that I am the most proud of since we are tackling lots of exciting new projects and challenges. But, in the first months of being at VIA, I wrote code to help us better ingest and manage data. It was the first time that I was put in charge of developing some code to solve a problem and make tasks more efficient for the team. We still use part of the code today and are continuously improving it. I think it was a real issue and being able to solve that problem was really rewarding.

What’s your favorite VIA memory?

My first offsite was really special for me, it was the first time I saw the whole team in-person and was able to learn more about every member of the team. It was also really nice to learn about the next challenges we were going to take on as a company.

If you were given an extra hour in your day, what would you spend it doing?

I like to learn, so anything from reading, learning a new skill, watching a documentary, or building something new would be mostly what I would use that hour for.

What’s your go-to food?

As a proud Montrealer (born and raised) I must go with Poutine (from La Banquise for the best in Montreal). I wouldn’t eat it every day because it is not the healthiest food, but I never say no to Poutine when proposed to me.

What’s something everyone may not, but should know about working at VIA?

The different backgrounds and diversity of every person in the company makes it a unique and fun workplace.



Let’s TAC™ About It: The Bridge to AI Experts

This is the first installment of our new blog series, where we will cover the many capabilities and benefits of VIA’s Trusted Analytics Chain™ (TAC™). So, are you ready to TAC™ about it?

Data science roles have proliferated in the past decade. The growth numbers look flat, however, in comparison to other technology trends.

AI is embedded in our phones, our TVs, and our cars. With 67% of large companies projected to have AI initiatives in place by 2021, big data and machine learning are no longer relegated to long-term, R&D projects in mainstream businesses. These are now critical functions required for the long-term prosperity of business. 

Many organizations with vast amounts of data struggle to recruit, develop, and retain the data science talent they need to analyze their data and deliver actionable insights. A large ecosystem of big data companies, AI specialist companies, and tools have emerged to address this data glut and talent shortage. However, there are very real data security and privacy risks to consider for the firms that work with external AI companies. In addition, selecting and managing AI companies is costly and time consuming. These barriers can trap an organization’s data and limit its insights. 

TAC™ reduces the time, cost, and risks to data security and privacy of working with external analysts in multiple ways.

  • TAC™ leaves the data where it is. Instead of sending data to an analyst, TAC™ controls the code delivered to the data’s location (even in multiple locations) through federated learning.
  • TAC™ automates data anomaly checks, data cleaning and harmonization, and NLP PII checks.
  • TAC™ tracks and, when required, restricts what analysis can be performed at the data’s location, through smart contracts and other programmatic controls.
  • TAC™ provides data owners control over results returned to analysts through digital watermarking, k-anonymity, additive homomorphic encryption, and other mathematical safeguards.
  • TAC™ streamlines data access workflows so companies can even grant multiple AI experts access to the same dataset. This allows companies to leverage the wisdom of the crowd to select the best solution for their particular challenge. 

In short, TAC™ is a secure bridge between a company’s distributed data and expert analysts. VIA works with global electric utilities and government agencies to help them gain access to the AI specialists that can harness massive datasets, even across companies, to transition to a cleaner, safer, and greener energy industry.

Thank you, 2019. Now, let’s do this 2020!

As we kick off 2020, we can’t help but think of all the moments from 2019 that contributed to what we think will be the biggest year yet for VIA.

Near and Far, Our Team Represented VIA
In 2019, our team traveled the globe to help spread VIA’s message. Our CEO, Colin Gounden and Senior Vice President, Joe Babiec, gave presentations at European Utility Week in Paris, Swiss-US Energy Innovation Days in Austin, TX, various Plug and Play summits, EDP Starter Acceleration Program in Houston, TX, and EPRI Venture Day in Chicago, to name a few. Kate Ravanis, our Chief Operating Officer, also spoke at the Greentech Media Blockchain in Energy Forum in New York City.

In addition, we were proud to sponsor, speak, and participate in several events across Montreal including Women in Physics Canada, McGill Physics Hackathon, and Montreal AI Symposium. We opened our doors for Startup Open House Montreal and hosted our own VIA Open House Party (featured below).

Fresh Off the Press
We wrapped up 2019 with six press mentions, two “Top” lists, and two technical blogs written by our team members. To take a trip down memory lane, check out press mentions here: BitcoinExchangeGuide.comAxios (and follow-up article) GreenBizDisruptor Daily, and Utility Dive; “top” lists here: Top 5 Big Data & Machine Learning Startups in Energy and The 10 Coolest Blockchain Startups of 2019 (So Far); and finally, our technical blogs: The Importance of Unit Testing and Understanding How EV Charging Behavior Affects Distribution Networks.

Our VIA Community Continued to Grow
Internally, we hosted two In-Person All Hands events in Montreal (featured below) where our team brainstormed big ideas for 2020. We held our first annual VIA Spirit Week where each office celebrated what it means to be part of the VIA team. Lastly, we created two videos on what it’s like to join VIA: The VIA Team and Applicant Journey.

The VIA community includes more than just our internal team members. This year, we launched our GDAC™ program and welcomed founding members Hawaiian Electric and Vector to the VIA community. In addition, we were pleased to share that the Westly Group led an investment round in VIA.

Our hats are off to you, 2019. Let’s do this 2020!

Understanding How EV Charging Behavior Affects Distribution Networks

The International Energy Agency projects that 30% of all vehicles will be electric vehicles (EV) by 2030. This transition, at the intersection of electric power and mobility, combined with increased generation from renewable resources has the potential to significantly reduce greenhouse gas emissions in the years ahead. To make this happen, utilities who operate the distribution network need to understand how this new demand for electricity will affect smart grid assets. Our primary job at VIA is to help utilities navigate these shifts by understanding their data and fostering collaboration through our Global Data Asset Collaborative™ (GDAC™) program. As an example, VIA recently kicked off our first GDAC™ by focusing on transformers. Through this GDAC™, we are beginning to see that transformers are stressed by the switch to EVs and our focus will be on helping utilities find ways to keep these assets healthy over the coming years.

There are at least two things that make charging an EV different than, say, running a central AC unit. First, the power that needs to be delivered to an EV is around 20kW, which is four or five times the power required for a typical central AC unit, which ranges from 3-5kW. A “short-range” charge to power the EV so that its owner can commute could require around 40kWh, thus a “slow-charge” for a “short-range” car requires about two hours of charging. Powering large fleets of EVs will clearly require extending the capacity of current electricity distribution networks. 

The second issue that makes charging an EV different is timing. The timing of EV charging events changes the daily load profile of the home, workplace, and in urban centers equipped with networks of charging stations. Transformers are generally able to run past their rated capacity so long as they are given ample time to cool overnight. That is changing as commuters return home after work to charge their vehicles, never allowing transformers that time to cool down, which can cause them to malfunction and in extreme cases, explode. EV charging events, because they demand so much power so quickly from the grid, can lead to shifts in voltages along the distribution network. This leads to wear and tear on tap changers and other voltage regulation mechanisms. 

Utility asset managers need to understand which transformers in their fleet are most at risk as EV penetration increases. A recent study by researchers at Ohio State University illustrates what needs to be done to understand the effects EVs have on transformers and voltage regulators (“An Integrated Algorithm for Evaluating Plug-in Electric Vehicle’s Impact of the State of Power Grid Assets”). The authors have studied a representative sample of urban, suburban, and rural areas and tried to answer the question “What would happen to the distribution grid if each home had an EV?” To understand both the total load and the rapid charging behavior, the authors used actual distribution grid topology provided by American Electric Power (AEP) and simulated the behavior of the system as EV charging events are inserted into today’s “baseline” load demand. The authors find that suburban areas are expected to see the greatest stress, as it is assumed that, in urban areas, additional power will be provisioned by specific “fast-charging” stations while the suburban dwellers load will stress the transformers that serve their primary residences. In rural areas, the lower population density typically means that the transformers are not as heavily loaded as in a suburban area. Some authors predict long-term changes in mobility patterns that will increase the number of rideshare services (i.e., Uber). Rideshare cars are typically required to drive all day and would require longer charge times. This corresponds to the most aggressive scenario studied by the authors, in which case they expect insulator degradation to occur after just one year. The results illustrate the socio-technical complexities of planning the future smart grid and the need for detailed studies on how people are expected to use their vehicles.

Author’s Note

As a highly-trained problem solver with deep scientific and computing expertise, I’m always hungry for tough problems to solve. There’s no doubt that integrating EVs into the smart grid is a tough problem. More importantly, it is a high-impact socio-technical problem that we as a society need to solve to transition to a greener future. Working together with the world’s largest utilities, VIA is in a position to help solve these problems, a privilege I am grateful for every day I go to work. At VIA, we have a company value, “Love in=Love out” which means that if you love what you are doing, you will do great work. I expect we will do great work in this area, and help our customers navigate the challenges of the EV revolution.

The Importance of Unit Testing

In March, VIA’s Ashley DaSilva, Team Leader, Product Development, was invited to lead a workshop on unit testing for McGill’s Computer Science Graduate Society. The workshop was part of their seminar series: CS Tools and Tricks, which introduces graduate students to topics they may not otherwise explore in depth in their academic programs. Ashley discussed the critical importance of software testing, why developers should embrace unit testing, and when and how to use mocking. She shares her experience with unit testing and a recap of her workshop below.

Learning Never Goes Out of Style

I first learned the importance of software testing in the early days of my theoretical physics Phd program. Back then, most of my coding was limited to scripting. I wrote scripts to model physical systems, analyze data, and visualize results. Over time, I started writing modules to be reused by myself or my colleagues for different projects. The first time I attempted to refactor one of these modules, it broke in unexpected ways, and I spent days tracking down and resolving all the issues.

I’ve grown significantly as a developer since those days, and now lead a product development team at VIA, focused specifically on the Trusted Analytics Chain™ (TAC™). Every day, my team and I build, test, and deploy Docker containers with microservices. This includes Airflow and RabbitMQ for scheduling tasks, Redis as a cache storage, and BigchainDB to host a blockchain. Software testing is critical to each stage of product development, and something we constantly work to improve.

Unit testing is the foundation of VIA’s software testing process, and an essential skill for all of our developers. For example, TAC™ contains several components that all need to communicate with each other. We maintain a list of python scripts that are authorized to run on the system. Components of TAC™ must download this list to verify the checksum of the scripts. If we did not use mocking for the content of the list in the unit tests of these verification functions, then every time the list was updated, the tests would all have to be updated to account for the change. With mocking, we are free to update the list of scripts without affecting the status of the unit tests.

Ready, Set, Resilience!

Clean Architectures in Python by Leonardo Giordani is a great resource for learning more about unit testing and test-driven development. During my workshop at McGill, I presented examples of unit testing and mocking and shared a few exercises for the students to practice on their own. Some of these exercises came from the github repository associated with Giordani’s book. I’ve included some other examples below:

First, let’s look at a snippet of code. The code below shows a DataAnalyzer class. It has a method, get_data, which is a placeholder for however one would want to retrieve the data from an external resource (e.g., a database or an http request). It also has a method,
analyze_data which performs the sum of the items in a list:

class DataAnalyzer:
   def get_data(self):
      # Gets data from an external resource
      def analyze_data(self):
         data = self.get_data()
         result = sum(data)
         return result

The code below shows one example of a unit test that uses mocking of the get_data method:

from unittest import mock
from calc.analyzer import DataAnalyzer
def test_analyzer():
   analyzer = DataAnalyzer()
   with mock.patch("calc.analyzer.DataAnalyzer.get_data", return_value=[1.0, 2.1, 3.5]):
      result = analyzer.analyze_data()
   assert result == 6.6

In this example, the unittest.mock.patch will be applied to the method specified as its first argument and return the assigned return value every time that method is called from inside the scope of the patch. A sample list is assigned to the return value of the patch of the get_data method. This list should have the same format as the expected output of the get_data method, which in this case is a list of floating point numbers. Finally, the result of the analyze_data method is checked that it matches the expected value.

Mocking can also be used to check how you handle exceptions:

import pytest
from unittest import mock
from calc.analyzer import DataAnalyzer
def test_analyzer_connection_error():
   analyzer = DataAnalyzer()
   with mock.patch("calc.analyzer.DataAnalyzer.get_data", side_effect=ConnectionError("Could not connect.")):
      with pytest.raises(ConnectionError):

In this example, instead of specifying a return value, there is a side effect. When the specified method is called, the side effect will be executed. In this case, a ConnectionError is raised by the get_data method. Using a side effect is particularly applicable when you have logic in your code that catches and recovers from errors.

Stay Curious

I enjoyed leading a thoughtful discussion on unit testing, and fielded some great questions from the students. One that stood out to me was:

“How can developers make sure that their mocks don’t get out of date?”

This is a really important and sometimes tricky topic! At VIA, we know that unit testing is only the first step of software testing. We also use other types of tests, like integration tests or end-to-end tests help identify problems in mocking before our software reaches users. And isolating and resolving problems at that stage is key to setting ourselves up for a successful integration. 

Mocking allows the freedom to isolate one particular part of your code and focus your unit tests on that functionality. Ideally, the expected inputs and outputs of the component being mocked are not going to change. This is typically true for external modules that you will use, at least within a particular major release of the software. However, if you know a software update will cause a change to your internal code base, it is your responsibility to recognize and communicate how that will affect your teammates. That’s why VIA believes that, in addition to testing, strong team communication and values like Learning Never Goes out of Style, Ready, Set, Resilience!, and Stay Curious are what help us develop and deliver the best iterations of our software to our users.