In this Q&A style blog, Alanna O’Hare, our Customer Performance Analyst, outlines her role in supporting Distribution Network Operators (DNOs) to accelerate network performance and drive a more sustainable future through the use of data. Alanna also discusses her recent 6-week trip to Parma, Italy where she spent time working alongside our data science team.
1. Tell us about your background and what your job entails?
Before working at Kelvatek I studied physics with astronomy at the University of Liverpool. During my time there, I was involved in several data analysis projects. Working with data and discovering what insights it can offer turned out to be an aspect that I found fascinating and encouraged me to pursue a career in this area. During my third year I conducted research into the future of the UK energy network. I was intrigued by the findings from this research, and this led to me to applying for a role with Kelvatek. I was initially attracted by Kelvatek’s innovative technology and the role it plays in supporting DNOs on their journey to net-zero.
My role as the Customer Performance Analyst for Kelvatek is to help DNOs accelerate the performance of their networks. We achieve this by supporting DNOs in driving operational best practice, helping them gain increased visibility of their networks and ensure they are utilising their LV equipment fleet to its fullest capacity.
2. Data is becoming increasingly important throughout the UK energy industry; how do we work with customers to transform their data into actionable insights?
While the growing use of electrical energy is essential as we transition towards net zero, it is causing an increased amount of stress on LV infrastructure, impacting Network Operator’s ability to meet customer demand. Data is a critical tool in helping Network Operatives overcome this challenge as it provides an enhanced visibility of their networks, ensuring there is adequate capacity to meet customer demand, and that faults are being proactively addressed.
Kelvatek has a Centre of Excellence located in Parma, Italy with a dedicated team of data specialists who analyse the data collected from smart devices connected to the network and identify patterns and correlations in conjunction with historical data. The Customer Performance team work closely with our teams in Parma to process the analysed data to drive actionable insights and then present it in easy-to-use dashboards which help DNOs gain a better understanding of network performance and allocate resources accordingly.
3. You are currently working alongside our Centre of Excellence team in Parma, can you tell us about that experience?
The Customer Performance team work closely with our team of data specialists who are located in Parma, Italy. Due to the restrictions of covid-19, face-to-face interactions have been very limited before now. Over the past 4-weeks, I have spent my time living in Parma and working alongside our Italian colleagues.
Getting the opportunity to work with my colleagues in the Parma office has been a great experience. Aside from enjoying all that the Italian culture has to offer, I have gained a deeper understanding of how Kelvatek’s specialised teams are deploying Artificial Intelligence (AI) algorithms and Machine Learning (ML) capabilities to solve customers’ challenges. I also spent time learning how our team in Parma are addressing the challenge of processing increasingly large data sets compiled from smart devices which collect fault and load information on thousands of LV circuits around the UK & Ireland and transmitting this data back to our operations centre for analysis. This kind of collaboration is what enables the Customer Performance team at Kelvatek to assist in the design of more effective solutions to meet our customer’s challenges.
4. Can you tell us about the type of work our Centre of Excellence team carry out?
At Kelvatek’s Centre of Excellence, there is a key focus on using technologies such as edge computing, Artificial Intelligence (AI), and Machine Learning (ML) to design and develop new methods of extracting value from data gathered from monitoring devices on the network and delivering these insights to customers.
The UK energy industry is faced with the challenge of progressively large, intricate, and irregular data sets. When we receive customer data gathered from monitoring devices, we need to extract value from it through rigorous processing and analysing methods.
To extract value, our Parma team use Artificial Intelligence and Machine Learning as tools for data capture, analysis, and collection of information. The team then design algorithms to make classifications or predictions, uncovering crucial understandings within data extraction projects.
Something I accomplished during my time in Parma was aggregating and analysing a unique data source to collaborate with the data team in constructing a dashboard that outlines the ‘timeline’ of a feeder. The point of this exercise was to collate data together so we could track a feeder’s history to give the customer performance team visibility on the historical performance of each individual feeder. This can be from installing a device, history of fuse ruptures, history of go-locates, sniffs performed, PRESense installations and much more.
By conducting this project, the data team at Parma, can optimise how we feed information and data to one another internally, simply by placing the data in one location, so it is easier to navigate through on one dashboard, instead of looking at several. This, in turn, allows our Customer Performance team to deliver solutions faster than ever before to our customers.
5. How are we tying together the work of our data and algorithms teams to the work you do with customers?
There are many exciting data products on the horizon which will provide new and essential insights into customers' networks. While the data and algorithms teamwork to deliver data products, my role is to present these findings in a meaningful and relevant way that will allow the DNOs to proactively manage their networks, ensuring they can adequately meet growing customer demands.
In today’s developing network, DNOs are under increasing pressure with where to place their limited resources whilst trying to avoid faults. Our data and algorithms teams provide the tools I need such as AI and ML programmes which help to identify subtle patterns and trends in network behaviour and power flows, helping build a detailed picture of likely fault activity, asset, and network health.
I then assist DNOs with prioritising imminent faults on their network based on individual needs such as filtering the faults that have had the most recent fuse operations or which have had multiple Go-Locates (these are notifications that detail the location of a defect which risks a loss of supply to customers allowing the DNO to proactively repair faults) sent to its location. In short, I bring our DNOs attention to the ‘worst’ issues on the network which will allow them to make informed decisions on how to deal with this fault.
6. What sort of benefits have our customers gained from working collaboratively with you and the wider Kelvatek team?
When DNOs work with us directly they gain quantifiable improvement in equipment utilisation – resulting in the location of more faults, more recloses and ultimately more value from every piece of Kelvatek equipment utilised.
We can also identify areas in the customer’s fault management process which could be improved. Communication is essential in the end-to-end process of finding a fault – from installing the kit to pinpointing where the fault is. Having that direct communication ensures that equipment is installed on the correct feeder, the cable routes entered are correct and ultimately that the algorithm will provide an accurate fault location.
Working collaboratively with customers enables us to provide a bespoke and personable experience for each of our customers. By having a clear understanding of their needs, I’m able to create visualisations of the data that are meaningful and useful for the person using it. This allows me to present visibility of the DNOs network in a way that is useful for our customers to facilitate more practical methods to fault management and improve the quality of supply for the DNOs customers as they become more dependent on the network.
7. What has been the most surprising insight or development you have found in relation to the UK’s transition towards net zero?
When I first started working with Kelvatek, I found it remarkable how well DNOs work not only together, but with solutions providers such as Kelvatek, to increase the visibility of the UK electricity network by being open with their data. From my experience, DNOs have recognised that open data is crucial for an effective response to climate change and can help unlock step changes in operational efficiency.
Great strides have been made by DNOs across the UK’s energy industry to use insights from data to proactively manage the network and address issues before customers are impacted.
It’s reassuring to know that our customers are incredibly focused on using their data to not only keep customers on supply but to facilitate innovation and navigate an increasingly complex network. This gives me great confidence that what we’re doing for our networks today will lead to a more sustainable and smarter grid tomorrow.
We recognise the challenges facing Network Operators as they transition to net-zero and navigate this new world of data. We’re committed to helping our customers unlock even more value from their data – enabling them to optimise the performance and utilisation of network devices, manage fault activity and support engineers in the field. We have dedicated teams, with specialists such as Alanna, on hand to support and develop bespoke plans to support your business.
To find out more, or to discuss anything highlighted in this blog, please complete the form below and a member of our team will be in touch.
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