Automated processing of energy measurements for the provisioning of analytics and recommendation services
Data analytics services and recommendations for promoting green energy and cost savings
Problem: Need for shifting from fossil to greener energy as well as cost savings is essential for consumers and DNOs.
Solution: Data analytics services and recommendations can provide in depth knowledge and predictions for optimized usage. It will help to better cope with energy consumption management for both DNOs and consumers.
Grid-friendly home smart devices
Problem: When the grid faces supply issues, a signal can be sent to a certain area so its homes could react to help solve these issues in real-time. In addition, thanks to consumption predictions, grid operators can avoid very costly demand peaks, asking homes to adapt their consumption behaviour.
Solution: The Demand-Response solution relies on making home devices, equipment and white goods interoperable to make them reactive to grid needs. Home energy management systems and smart meters’ data are harmonized (SAREF-ized) so one home can receive a request via the interoperability layer to adapt their consumption and actuate on the devices regardless of the provider. User preferences are considered, preconfigured in a mobile app, to select which devices should change consumption.
Interoperable EMS control ofdomestic appliances
Problem: The common household is built from an assortment of appliances from different manufacturers, exposing a multitude of requirement for concept representation, data access and appliance control. The scenario imposes limitations for an observation and control service as the EMS, requiring adoption and integration with distinct manufacturers.
Solution: Adoption of the Interconnect’s Semantic Interoperability Framework, introducing transparent domain-centric concepts such as flexibility and interfacing with appliances and services from several manufacturers.
This project has received funding from the European Union’s 2020 research and innovation programme under Grant agreement Nº 857237
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