Real-time monitoring and control of distribution systems is very limited due to the lack of sensors and communication systems. Hence the distribution system can be described as under-determined with the number of measurements insufficient to make the system observable. Once the complete system state is available, then any quantity in the system can be calculated. The observability and controllability of a system are mathematical duals, which means an unobservable system cannot be fully controlled. Distributed energy resources introduce significant uncertainties and, at high penetrations, may lead to operational difficulties in a network. Therefore the provision of accurate system state information to the network operators is critical for them to operate the system in a safe, prompt, and cost-effective manner, and also to make best use of the assets.

Smart metering is widely recognised as the first step towards a Smart Grid future and the UK is committed to the full deployment of smart meters by 2019. Smart meters and the associated ICT (information and communication) infrastructure can greatly improve observability. Therefore there is a need to investigate the technical feasibility and key technologies of using smart metering to increase the observability of the distribution system through state estimation techniques.

The research programme is structured around three challenges:

Research Challenge 1: The load demand needs to be aggregated at the MV nodes using data from smart meters connected to the low voltage (LV) nodes. A big challenge is how a state estimator deals with both various kinds of measurement errors with non-normal distribution and the influence of the measurement configuration (type, location, accuracy of measurements) effectively and provides accurate estimation on the system state.

We will improve the distribution state estimation to make it robust to the influence of both the measurement error distribution and the measurement configuration of a distribution system.

Research Challenge 2: Smart metering may change the behaviour of energy consumers and thus lead to more dynamic demand (e.g. load that is sensitive to price). Therefore the second challenge is how to model extremely dynamic load and to provide pseudo measurements to the state estimator under conditions of large latency or failure of the ICT infrastructure or if there are un-monitored quantities.

We will provide a theoretical contribution to MV nodal load modelling through investigating a new machine learning method which is able to obtain knowledge from past experience (e.g. past smart meter data).

Research Challenge 3: What and where additional real-time measurements should be placed, in addition to the smart meters, to make the estimated system states accurate enough for particular Smart Grid functions and reduce the impact of the measurement configuration.

We will develop an optimal meter location method considering impact from both measurement errors and measurement configurations while minimising the extra metering cost.

The research will benefit from close collaboration with national and international industrial partners, and will gain insight and make contribution to the research challenges through both theoretical study of using smart meter information to increase the observability of distribution systems, and technical demonstration via small scale test facility, i.e. the Smart Metering test rig and the Smart Grid test rig developed at Cardiff; medium scale test facility in RSE, Italy; and practical case study using a BC Hydro network.

The impact on potentiol beneficiaries will be delivered through collaboration, communication, and commercialisation. We will also utilise EPSRC HubNet as a dissemination platform to facilitate a wider communication.

Potential Impact:
The beneficiaries will be:

(1) Manufacturers involved in the development and deployment of Smart Metering and Smart Grid systems (S&C Electric Europe Ltd, Toshiba TRL, and Siemens);
(2) Utility companies who will benefit from tools for estimation of system states, improved modelling of the dynamic demand, and optimisation of meter location, which can be used to inform the planning, design, control and management of low-carbon smart distribution networks (UK Power Networks, INEXUS, E.ON, and BC Hydro); and
(3) Academia and research institutes (HubNet Consortium, RSE, and Tecnalia) who will benefit from the theoretical contributions from this project regarding increasing the observability of distribution systems using smart meters and use it as a basis for further development of advanced Smart Grid analysis and control functions.
Ultimately, electricity consumers will benefit through more efficient smart distribution networks that are designed and operated to minimise risks, improve services, reduce cost, and to be adaptable to an uncertain future.

The project is supported by a Steering Group (SG) which represents the main potential beneficiaries and are in an exceptional position to support the research, maximise dissemination opportunities and enable impact. All the individuals in the SG have agreed to serve in the SG, and all SG members will take part in the collaboration and will be engaged in reviewing, advising and disseminating the IOSM research. The SG members have agreed to these roles in their letters of support and, where they are able to do so, have estimated the value of this in-kind contribution. Three SG meetings will be organised and teleconference facilities will be provided for the international SG members. The first SG meeting will be held soon after the start of the project to plan arrangements for stakeholder engagement, dissemination strategy and a knowledge transfer plan. The second SG meeting will be organised as a workshop with wider participation, which will be scheduled along with an EPSRC HubNet annual dissemination conference to gain maximum impact. The third SG meeting will be organised at the end of the project to disseminate the final research findings and discuss the possible commercialisation arrangements. The high-performance test facility in RSE, Italy will be used for the medium scale demonstration, which will contribute to the integrated European research capability. A practical case network provided by BC Hydro under their Smart Metering and Infrastructure Program will be used for the proposed meter location study.

S&C Electric Europe Ltd and Toshiba TRL as major manufacturers of Smart Grid systems, have both technical and financial resources to commercialise successful research. Both of them have offered strong financial support to this project and proposed to take the research findings forward for commercialisation. Therefore they will have priority to commercialise the research output.

We will establish the IOSM as a visible focal point for Smart Metering/Smart Grid research in the UK and internationally. We will learn from international experiences; publicise the existence, objectives, activities, and findings of IOSM via launching the project web site, presentations at relevant meetings, publications in professional journals/conferences, and dissemination through the SG and the EPSRC HubNet consortium (a workshop and SG meeting will be organised at the same time and place as a HubNet dissemination conference in order to facilitate the wider communication). We will also link the IOSM research with our other networks, including SUPERGEN HiDEF, UKERC, ITRC and EU project MERGE and SEESGEN-ICT.