Detect the undetected with Clir’s new feature

Detect the undetected with Clir’s new feature

Using peer-to-peer trending, Clir users can now detect changes in data that lead to false analysis.

Clir Renewables has just announced P2P, a new feature for their Data Exploration Environment. Clir’s Data Exploration Environment, Clir Explore, is a unique tool in the renewables space. Using informative data visualizations and pre-populated data variables Clir Explore allows users to view and manipulate streamlined data sets which narrow in on specific performance issues. Clir Explore makes complex analysis simple by providing the specific variables to use when identifying different kinds of anomalous turbine behavior and is comprised of 12 different features each manipulating data differently to identify underperformance. This new feature, P2P, adds to the products suite of capabilities by enabling peer-to-peer trending analysis for turbines. 

Comparing concurrent turbine data is a vital part of a complete wind farm analysis. Clir’s peer-to-peer trending tool makes it easy to detect anomalous behavior and trending over time. For example, it allows our clients to spot anemometer drift and other sensors needing to be recalibrated, as well as subtle differences in power or pitch curve behavior. The P2P tool uses concurrent data, and it’s possible to filter out any non-full performance data. P2P gives analysts a tool to analyze turbine operating data between two selected turbines and was developed to solve the problem of detecting degrading turbine components, to clean up data, and enable better analysis.

The P2P tool allows the user to compare any two turbines in their wind farm and select the variable they want to compare. Among the variables available are power, wind direction, wind speed, blade pitch angle, and generator speed. The results can be colored on time period, nacelle position, or wind directions, which means the user can easily identify if patterns are time depended or direction dependent. The scatter plot and overlaying linear regression, makes it easy to spot outliers. 

Detecting anomalous turbine behavior is easier and faster than before with the P2P tool. “Before our clients started using Clir they didn’t have the data model or tools to get their hands around numerous wind farms. Not only do you need to know what kind of underperformance you are looking for, but you also need to know which variables to use to complete the analysis. With our workbooks, users can use Clir’s catalogue of visualisations and create their own visualizations utilising the Clir data model.” says Gareth Brown, CEO of Clir Renewables.

Want to know more about how P2P could work for your portfolio?

Treating I&D as a core area of the business

Treating I&D as a core area of the business

By: Rebecka Klintström, inclusion and diversity lead at Clir Renewables

A quick internet search on inclusion and diversity will provide thousands of ideas on how to solve the tech industry’s issues with representation. It’s easy to find research, news articles, and lots of concrete tips on how to improve the diversity of teams or create a more inclusive work environment. However, none of that will have an impact in your company unless there’s buy-in from the entire organization, from executive level to the newest, most junior hires. It’s not enough to have goals for diversity or a vision for inclusion if it doesn’t lead to concrete actions and measurable improvements. But how do you make sure that inclusion and diversity move from being something mentioned in long-buried policy documents or the topic of a soon forgotten workshop?

Inclusion and diversity are complex, sensitive topics. To make progress, we need to be fearless, while at the same time, staying mindful of how intensely personal and complicated the discussion topics are. Conversations around gender or race, salaries, work environment, or biases in the hiring and promotion process often forces us to face uncomfortable truths, both about ourselves and about others. Done right, it’s an integral part of creating a healthy organization. Done wrong, at best it’s a lot of time spent without any impact. At Clir, we’ve found that the best way to work with this is to treat our inclusion and diversity initiative like any other crucial part of our organization and create processes for it accordingly. We wouldn’t expect there to be a pre-packaged solution for any other complex business issue we’re trying to solve, and we shouldn’t expect that for creating an inclusive and diverse company either. We’ve worked on creating an environment to have healthy, focused conversations around inclusion and diversity, and it’s nowadays an integral part of our company’s day-to-day.

The way we work with inclusion and diversity is essentially the same as we treat other business areas: we have annual goals, broken down to quarterly goals, and we have a scorecard with metrics communicated to the executive team every month. Once a month, we have an in-person meeting with the inclusion and diversity focus team, where we plan the coming month’s work and discuss our top priority issues. We have a weekly check-in to make sure we stay on track with whatever our focus area is for the current month. Data from our monthly surveys, our hiring candidate pool, and the diversity numbers for the company form the metrics for our scorecard. The monthly newsletter shares these metrics with the whole company, and our diversity numbers are presented on our website to keep us accountable. We’ve found that to be able to have the important conversations and steer a change, we need to create a space where these conversations can lead to concrete actions. We must devise a predictable work and information flow to become aware of inclusion and diversity issues within our organization, and the communication routes need to be understood by everyone. Having processes for the inclusion and diversity work means we can make sure we’re focusing on the most important issues and identify if we’re making progress beyond just discussing them.

We’re a data-driven company, and we want that to influence all the work we’re doing, including inclusion and diversity. Our monthly work satisfaction survey includes questions around meeting culture, support from managers and coworkers, and general satisfaction with work tasks and work environment, broken down by team or gender. We can look at the results and let it drive where we focus our limited resources. Our bi-yearly general inclusion survey serves as a measurement of whether the work we’re doing actually has an impact on our work culture and environment. We’ve been hiring a lot the past year, growing from a small team of eleven to over forty employees in Vancouver, Eastern Canada, and the UK. We’re tracking the diversity of our candidate pool to stay focused on developing a less biased hiring process. For some roles where we get many applicants, we do a deeper dive to understand if we’re unconsciously filtering out groups at specific steps in our recruiting and hiring process. Our processes for the inclusion and diversity initiative helped us identify and solve this issue, while if we hadn’t implemented these procedures we likely wouldn’t have noticed the problem. Our data collection helped us understand that we were losing candidates identifying as visible minority in the first screening interviews. Without collecting and visualizing the data, we wouldn’t have identified the issue, and without having a process and fixed format for the discussions, even starting the conversation would have been difficult. Collecting data and having processes keeps us on track and creates the environment we need for the conversations to happen.

We would never say it’s “good enough” about another area of the company or that we don’t need to keep improving. Having the same workflow and level of accountability for working with our core values makes it easy to have the same mindset and sense of urgency for questions related to inclusion and diversity as for any other critical part of our company.

 

About Rebecka Klintström

Rebecka has been at Clir from the start and leads Clir’s Inclusion and Diversity initiative. She has over six years’ experience working in the wind industry, both as a consultant and for a utility. She has worked in all phases of a wind project, from pre-construction flow modelling, met mast installations and noise modelling to operational analysis, icing loss modelling and optimizations, as well as managed research projects and project portfolios.

 

Image: Freeimages.com

Successful close to investment round for Clir Renewables

Successful close to investment round for Clir Renewables

Clir Renewables secured a C$1.9m investment following discussions with multiple investors.

Canadian renewable energy company, Clir Renewables, has successfully closed an investment round, securing C$1.9m. The SaaS company has developed a renewable energy AI platform that helps wind farm owners and operators to maximize production and provides clarity on performance risk for all interested stakeholders.

Gareth Brown, Clir Renewables CEO, says, “It’s exciting times here at Clir. We secured this bridge financing to put us in a sound financial position to continue to grow the company globally and develop our domain-specific AI. It’ll allow us to continue to lower the cost of renewable energy and give us time to find the right Series A investor later this year. It’s fantastic to see so many of the previous investors reinvesting in the company and bringing in impact and renewable industry expertise investors from North America and Europe will align a lot of expertise with the company to facilitate a massive global impact. With a bit of luck, we’ll have over 10% of the world’s wind farm owners paying to use our platform by the end of June. We need to remain humble and focus on execution to drive our industry forward to lower cost of energy”.

Clir Renewables was previously awarded funding through Sustainable Development Technology Canada (SDTC), a Canadian government support for entrepreneurs accelerating the development and deployment of globally competitive clean technology solutions. The company also secured C$2.1m in a seed-stage financing round in 2018. This latest investment enables continued product development, strengthening existing features, and releasing new feature from the product roadmap.

Mike Winterfield, Founder and Managing Partner of Active Impact Investments, commented, “We have been watching the success of the Clir Renewables team for over two years and are thrilled to get an opportunity to support them in accelerating their global expansion. Climate change requires an urgent shift from burning fossil fuels, and the insights provided by Clir’s software will continue to drive the costs of renewable energy down so it becomes the obvious choice in all markets.”

As Clir Renewables gains more market traction, it is considering sourcing larger investors to assist in capitalizing on this traction and increased interest in the software.

Wind Engineer AI learns to detect turbine failures early

Wind Engineer AI learns to detect turbine failures early

Replacing components in a wind turbine is a costly procedure, especially if required urgently; however, it can be avoided or planned for by on-going monitoring of temperatures.

Canadian optimization software company, Clir Renewables, has released its latest AI feature. The Clir AI platform has evolved to learn how to identify anomalies in component temperatures to detect failure at an earlier stage.

Maintenance budgets for wind farms account for the majority of associated OPEX. These planned budgets can be shattered if unexpected repair is required due to a component failure. Increased expenditure is not the only cost involved with unexpected failures. When a failure occurs, the turbine can be out of operation anywhere from a few days to a few weeks, dependent on sourcing replacement parts or required machinery in a quick timeframe. This downtime can result in large quantities of lost energy generation.

The question is, can you predict and prevent component failure? The answer is yes. Clir AI can learn temperature behaviour in the context of the real world operational environment anomalies or trends that could be utilized to identify when a component is operating at higher than expected temperatures under certain conditions like increased loads. Once identified this information allows owners and operators to assess components for signs of degradation which if ignored could lead to catastrophic failure.

Clir AI can remove some of the unknowns around unexpected failures by creating actions for the owner or operator to investigate the turbine further. The challenge for wind farm owners is the amount of data and its context. Simple peer to peer trending or other limited algorithms have shown time and time in our industry to frequently lead to false positives that cost owners money and impact confidence and trust in data analytics platforms.

This type of detection is difficult; turbine components heat up and cool down in different ways. Inconsistent measurement instruments between components and temperature are often driven by the conditions leading to a moment in time rather than specific live conditions. Clir AI puts the data in context and takes into account a variety of factors including, but not limited to, service information, ambient temperature, rotor speed, ramping up and down, and seasonal variations. Based on all of this information, Clir AI learns a model of the behaviour pattern for the turbine. If the temperature varies outside the probabilistic range, the system creates events and actions on the system. It reports multiple grades of severity, based on how much the trend deviates from the expected behaviour and learned failure models in the turbine.

As an independent system, Clir seamlessly integrates this detector with its other features, providing a multitude of information and actionable insights in one place.

“We really wanted to focus on building detection that has limited false positives, so the tool isn’t wasting peoples’ time while maximizing the benefit of early fault detection,” says Clir CEO Gareth Brown. “The approach maximizes the use of the data to drive improved performance, and crucially it can be scaled across all turbine technologies and as components are upgraded or replaced. It’s exciting to see when we take deep domain expertise and apply the latest and greatest AI techniques what we achieve”.

 

Image: Clir Renewables

Customer Success Team Profile

Customer Success Team Profile

The key ingredient in the recipe for a successful business is a successful client. To achieve success you need a good product and excellent customer support. The latter is what Clir Renewables’ Customer Success Team provides. Our Customer Success Team consists of engineers dedicated to working with clients to get the best out of their portfolio using Cir AI.

The Customer Success Team first get involved when onboarding projects to the platform, working with clients to make the process as smooth as possible. From this point, they are in regular contact with clients providing training on how to navigate the system and get the best results from the tools and data available. Supporting clients utilize the Clir AI tools to optimize production from their portfolio and highlight when anomalies arise in the data that require further investigation by the client are key focuses for the Customer Success Team.

The relationship between clients and Customer Success Managers is two-way, our clients provide important feedback on system features and functionalities. This is an important element of the relationship enabling us to continue to improve our product offering.

Customer Success Team members hail from companies with a background in renewable energy engineering, including Innergex, SgurrEnergy, DNV-GL, Vattenfall, Natural Power, Blu-tility Wave Power Inc. and ESB (Electricity Supply Board Ireland).

 

Image: Unsplash

Meet Customer Success Manager Erin Quon at AWEA Windpower 2019.

Join our Customer Success Team in Vancouver or Glasgow.