Trial location

Various Locations


Due to technological and societal changes there is growing pressure to develop new electricity market processes. The emergence of both smart meters and smart contract platforms provides opportunities for regulators such as Ofgem to redefine roles and responsibilities. In particular, systems can be created to implement incentive structures based on the accuracy of network demand and generation predictions. This project uses a smart contract oriented regulatory model for public electricity networks, developed by Cardiff University [1]. The model defines monopoly roles, such as network operators, and a framework for facilitating trading between metered participants. In the model, each meter (including meters between voltage levels in the distribution network) is compelled to predict future usage. Rewards and penalties are later derived from these predictions. To reduce the possibility of ‘gaming’ the system, meter reputation factors are used to reduce the accessible rewards of meters with inconsistent predictions. This project will be used to assess algorithms that assign the meter reputation factors.

What is the challenge?

Cardiff University has developed a set of algorithms that assign a reputation factor to individual electricity meters, based on the quality of the meter’s demand/generation prediction. At present it is not known which of these algorithms will best incentivise improved prediction performance.

What is the proposed solution and how is OpenLV enabling it?

Cardiff University is seeking to assess the performance of its algorithms to create a reputation factor for meters. Doing this will involve creating a framework with which to assess prediction-linked reputation algorithm performance, coding of the algorithms themselves, running them using data gained from the OpenLV project as input, and analysing the outcome. Time and resource permitting, it is hoped to trial the real-time operation of the reputation algorithms within the OpenLV platform. For this, the OpenLV platform’s existing prediction algorithms will be used.

[1] Lee Thomas, ‘A smart contract oriented whole system regulatory model for electricity networks’, Rev. IET Smart Grid, 2018.

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