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UCL PhD Studentship in Blockchain enabled peer-to-peer energy flexibility trading

1 June 2018

blockchain

The UCL Energy Institute, in partnership with GreenRunning, are seeking applications for a fully funded studentship on the topic: “Evidencing and authenticating energy demand side response using high frequency electricity disaggregation and distributed ledger technologies”

Funded by the Engineering and Physical Sciences Research Council (EPSRC) through the EPSRC Centre for Doctoral Training in Energy Demand (LoLo CDT) and co-funded by GreenRunning, this highly innovative project is look to bring together two of the most interesting recent developments in the energy field: high frequency electricity disaggregation for individual appliance identification and distributed ledger (‘blockchain’) technologies for authentication of demand response and as a transaction platform for DSR trading.

About the project

Supervisors: Professor David Shipworth, UCL and Dr Peter Davies, GreenRunning Ltd. (Additional supervisory expertise will be identified once a candidate is selected and the project develops.)

Studentship: The studentship will cover home fees and an enhanced tax free stipend of  approx. £18,000 per year for eligible applicants for four years (start date September 2018), along with a substantial budget for research, travel, and centre activities. Applicants should meet the EPSRC eligibility criteria EPSRC eligibility criteria .

Overview

Rapid penetration of distributed generation technologies such as photovoltaics wind and hydro, combined with electricity network constraints, is leading many to explore radically different configurations of the energy system. One of the hallmarks of this reconfiguration is the need to balance supply and demand at both the local and national levels in order to accommodate increasing penetration of intermittent renewable power into the grid. Such intermittent renewable power frequently lies that the extremities of the grid, creating problems for grid connection and load balancing, and requiring significant infrastructure upgrade costs unless alternative solutions are found.

To help demand follow supply there are two broad classes of solutions: demand-side response (shifting the timing of demand to meet available power supplies); and local energy storage (at the local grid or building level). In order to support uptake of DSR and local storage four key conditions must be met. Firstly, consumers must see value in it, this value can be financial, social (e.g. community participation) or phychological (e.g. risk aversion). Secondly, there must be some way of verifying that a specific customer has provided the DSR service – either through exporting electricity from local generation, storage, or by demand reduction at peak times. Thridly, there must be a way to record and authenticate that DSR service, to ensure trust in the system from all parties. Forthly, there must be a way to transact that service, so all units of energy generation, storage or reduction are uniquely accounted for both physically and financially. This is a very challenging problem, but one in which recent advances in electricity load disaggregation, and the development of distributed ledgers (‘blockchains’) offers significant new potential to address.

This project will work with one of the leading technology start-ups in this field to work on this fundamental problem of evidencing and authenticating demand-side response using electricity disaggregation and distributed ledger technologies. GreenRunning is a global leader in the field of high frequency electricity disaggregation (also called Non-Intrusive Load Monitoring ‘NILM’), applying data analytics and artificial intelligence methods to identify appliance use from very high frequency temporal sampling of the building’s voltage and current signals. This technology has a wide range of applications from providing better feedback to consumers on the appliances using most energy in their home, to disaggregated billing (costs per appliance), to appliance fault detection and supporting service contracts. UCL Energy Institute and Computer Science has expertise in the application of blockchain technologies and their applications in the energy sector, and has a growing portfolio of projects and industrial relationships in this area.

The research will address the following research questions:

  1. What blockchain architectures can be used to authenticate demand-side response within timeframes that would allow participation in the different elements of the energy market – from the half-hourly wholesale market to the fast frequency response energy market?
  2. What forms of evidence, and what level of confidence, will regulators and market actors accept as evidence of a demand-side response in order to allow participation in energy trading of that response?
  3. How do these acceptable forms of evidence vary depending on the timeframe of the energy market mechanisms?
  4. What are the social, policy, regulatory, data protection, communications technology, and hardware enablers and constraints to end user participation in energy trading?

Personal specficiation of applicant (specific skills required)

We are ideally seeking applicants with good degrees (min 2:1) in computer science or data science, or strongly quantitative degrees with a substantial component of data analysis and programming. Previous experience in, or knowledge of, the energy system is preferable but not required.

The successful candidate is expected to possess the following qualities:

  • Demonstrable skills in scientific or data-scientific programming (such as Python, R, Go, C++, Solidity, etc);
  • A strong interest in blockchain technologies and their appications outside of the cryptocurrency field;
  • A strong interest in entrepreneurship and working with start-up companies in the energy sector;
  • A strong interest in the energy transition and new energy business models;
  • Ability to use own initiative and prioritise workload;
  • Good interpersonal and communication skills (oral and written);
  • A high level of attention to detail in working methods.

Recruitment is now closed for this project.