AbstractIn the modern world, many cities make use of state-of-the-art technologies for a diversity of applications. A field with very specific needs is the electric power system that deals with both large entities that govern themselves (grid operators) and the citizens. For both and all actors in between, there is an increased need for information. Steps to provide these data are always taken and several initiatives are ongoing across the world to equip residential users with last generation smart meters. However, a full deployment is still not possible. Considering this aspect, the authors propose KPIs for the specific situation when some information is available from the meters and other sources, but some is not. The study case is based on a residential area occupied mainly by university students and after an extensive measurement campaign the results have been studied and analysis methods proposed.

The focus of the work presented here is to raise awareness of how ancillary services within the NordPool area could be of value in supporting the future grid, and who could be the provider of these services. The ancillary services considered here are not limited to the current market, but also services for future market solutions as well as services for fulfilment of grid codes. The goal is to promote the development of existing and novel solutions to increase the utilisation and thus the value of equipment within the power system. The paper includes a techno-economical categorisation of ancillary services, from a provider’s perspective, presenting opportunities and competition. Furthermore, procurers of services could utilise this kind of categorisation to identify possible providers or partners. The analysis of the categorisation shows a broad range of possible providers for each service and a broad range of possible services from each provider.

The paper describes modelling, design and testing of the developed Energy Management Strategy (EMS) system simulation model. The project was carried out by NTNU and IPE contributing to CloudGrid, with the aim to develop a new real-time simulation model with price-based Demand Response (DR) program for future implementation as consumer flexibility tool. Real load data were used as the basis of the model that was tested in Real-time Simulator in Norwegian National Smart Grid Laboratory at NTNU, with an algorithm and measurements provided from IPE member side.