North West England, England
£50000 - £55000 per annum
about 1 month ago
About the job
Evergreen Energy is looking for a full-time Modeller/Data Scientist based in Manchester to start immediately. The ideal candidate will have an interest in renewable technology to join us working on optimal scheduling of smart home devices such as electric vehicles, batteries and heating.
At Evergreen Energy we use smart technology to help our customers dramatically cut their carbon emissions and reduce their energy bills! We believe that making our homes more energy-efficient, and using renewable technology to heat and power them, will play a big part in achieving a sustainable future.
What you'll be doing
Our energy system is changing: we are decarbonising power generation by increasing renewable capacity (e.g. offshore wind), while at the same time increasing demand by electrifying our transport and heating. By using smart technology we can make sure we use the cheap, low-carbon energy when it is available. Energy suppliers have started to offer dynamic electricity tariffs e.g. Agile by Octopus Energy, where prices change to reflect the availability of renewable energy and demand on the energy system. This means that by using electricity during times of high renewable energy production or high renewable generation customers can save money on their energy bills.
You will join our Smart Home team, focused on the development of integrated hardware and software solutions for optimisation of domestic energy usage. For example, our Homely Hub smart thermostat enables automatic scheduling of heating to meet user-specified temperature setpoints in the most efficient manner. The Homely Hub is designed specifically to work with energy-efficient heat pumps, maximising their performance while taking advantage of dynamic electricity tariffs, cutting both cost and carbon footprint. We are also extending the functionality of the Homely Hub to control batteries, monitor and account for PV production and in the future integrate with EV chargers for a fully integrated smart home system.
The successful candidate will take the lead on enhancing our current optimisation algorithms, working alongside the Head of Smart Home. The work will include:
Improvement/Programming of algorithms for optimal scheduling and control of domestic energy usage
Improving and designing algorithms that would instruct domestic devices such as heat pumps when to operate, in turn achieving the most cost-efficient operation of the heat pump whilst accounting for solar power production, battery charge levels and other power consumption in the home.
Working closely with the engineering team to automate the identification of heating systems that are underperforming.
Heat transfer modelling in buildings and parameter estimation using real-world data.
A simple example where we start with a simple equation to represent the heat dynamics of the building
dI/dt=a(T-I) + bH where,
I - internal temperature of the building ℃
T - external temperature ℃
a - heat transfer between indoor and outdoor
b - heat transfer coefficient of the heating system.
H - heater output kW
- Check how well the observed temperature (real-world data) fits the simplified modelling.
- Identify variables that could be affecting the internal temperature of the building outside the model.
- Improve on the simplified model of the building by including these variables.
- Estimate the best parameters a and b that fit the observed real-world data.
Essential Skills/Experience and Qualities
PhD, MSc or equivalent experience in a modelling or scientific programming discipline, for example:
- Applied Mathematics
- Software Engineering
- Data Science
- Financial Mathematics
Required Skills/Experience and Qualities
- Demonstrable experience of scientific programming in Python (numpy, scipy, vectorisation)
- A can-do attitude to problem-solving
- Ability to work within a multi-disciplinary team to reach a common goal
- Excellent communication skills, particularly technical documentation
Desirable Skills/Experience and Qualities
- Numerical techniques for the solution of PDEs
- Model calibration using real-world data
- Optimal control/scheduling problems
- An interest in "green" technology, e.g. heat pumps
Why work with us:
- Working at the forefront of building smarter and greener future
- Competitive salary
- Minimum 25 days holiday, on top of public holidays
- Health care expenses scheme
- Flexible working
- Pension contributions matched by the company up to 4%
- Cycle to Work scheme