Meet SMAP Energy, working on a solution for estimating energy consumption across scenarios where meter data is missing. They are currently in the Evolve phase of EDI.

Can you tell us how you came to your Startup idea? We would also love to know more about your team, what makes your dynamic so promising and impactful?

We’ve been working with smart-meter data since 2014 when our team came together at the University of Cambridge. Operating as the privately sponsored Cambridge Energy Data Lab, we worked with academics, data scientists, and utility clients across the world to build and develop the next generation of data analytics tools and services that would capitalise on the growth of smart meter installations.

In 2016, we saw an opportunity to combine our expertise into a single platform and SMAP Energy was born. We envisioned a single cloud-based system capable of analysing hundreds of millions of smart meters and continuously evolving to deploy new applications. Our role in the future energy system was to be the foundational element for accelerating all components of the digital transition.

We’ve grown rapidly since then and have clients from all over the world subscribed to the platform. In the process, we’ve created not only a product capable of increasing operational efficiency, profitability, and end-customer satisfaction, but also an international community of like-minded innovators who want to push the boundaries of energy data analytics. As we move to the future, we want to accelerate the adoption of advanced “Energy AI” applications through our product offerings.


What makes your solution unique? What is the impact you are trying to achieve?

The algorithms and practices applied in the project are well evidenced in previous studies – which is important in the energy distribution sector as reliability is critical – but the strength we bring is in understanding and correctly applying them. We’ve been working in the field of energy data analytics even before the widescale rollout of smart meters and have gained expertise in developing and implementing solutions at all development stages.

Additionally, because we utilise a platform approach this means that we can increasingly add and tailor our applications to fit the needs of our clients. Ultimately, we want to accelerate data utilization and innovation in the energy sector through the use of our platform.

What challenge have you selected for the EDI incubation programme and why did you choose it?  

We applied for the challenge “Determining Load Profiles for Customers in the Indicated DSO Area based on Smart Meters”. The challenge presents an interesting problem – namely the estimation of energy consumption across a multitude of scenarios where meter data is missing – that matched well with previous applications we have built into our platform. This problem is compelling as many utilities struggle with gaps in their data and having a viable methodology to address this can provide a compelling solution.

For a few months you have worked hard in the EDI Experiment stage, developing your Big Data solution even further. Can you please elaborate on your progress and how have you evolved during the acceleration process? How was your experience working with your Data Provider? 

At this stage, we are on track to successfully completing our KPIs and have had the opportunity to iterate further based on our findings. One piece of the problem presented is that the meter data will be unavailable, but this occurs in several defined configurations. For example, there are meters where the data is only unavailable sporadically, but in other cases there are daily or monthly stretches of unavailable data. Our data provider – Energa Operator – was very helpful in explaining the likely circumstances behind each and was quick to answer any questions we had.

To address this, we broke down each case separately and applied a methodology more specifically suited to each. We are still compiling the results of this, but we are eager to share them at the final evaluation.

“The EDI programme provides several great benefits, including access to data for MVP development, a dedicated data provider giving guidance, a coach tracking your progress, and equity free funding”

After joining and benefiting from the tools EDI provided you, what is your next step? 

We have identified several areas where we could continue our investigations, but our ideal outcome would be to move to a trial project. One limitation of our work thus far is that we have limited the scope to a static dataset, but a commercial implementation would require daily updates and computations. As we have built and deployed similar applications on our platform, we are confident in our ability to do this successfully as the next stage.

Finally, what would you say to a startup considering applying to EDI? 

The EDI programme provides several great benefits, including access to data for MVP development, a dedicated data provider giving guidance, a coach tracking your progress, and equity free funding. These are all essential to startups building data products and services, and we highly recommend the experience as a way to build and test solutions.

Liked what you read?

EDI 3rd Open Call is coming on the 17th of March! Learn more about the programme and see if you have what it takes to apply!


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