Generalized Operational FLEXibility for Integrating Renewables in the Distribution Grid (GOFLEX)

Objective

The GOFLEX project will innovate, integrate, further develop and demonstrate a group of electricity smart-grid technologies, enabling the cost-effective use of demand response in distribution grids, increasing the grids’ available adaptation capacity and safely supporting an increasing share of renewable electricity generation. The GOFLEX smart grid solution will deliver flexibility that is both general (across different loads and devices) and operational (solving specific local grid problems). GOFLEX enables active use of distributed sources of load flexibility to provide services for grid operators, balance electricity demand and supply, and optimize energy consumption and production at the local level of electricity trading and distribution systems. Building on top of existing, validated technologies for capturing and exploiting distributed energy consumption and production flexibility, GOFLEX enables flexibility in automatic trading of general, localized, device-specific energy as well as flexibility in trading aggregated prosumer energy. Generalized demand-response services are based on transparent aggregation of distributed, heterogeneous resources to offer virtual-power-plant and virtual-storage capabilities. The sources of load flexibility include thermal (heating/cooling) and electric storage (electric vehicles charging/discharging). A backbone data-services platform offers localised estimation and short-term predictions of market and energy demand/generation, and flexibility in order to support effective data-driven decisions for the various stakeholders. Smart-grid technologies, such as increased observability and congestion management, contribute to the platform. Over 36 months, GOFLEX will demonstrate the benefits of the integrated GOFLEX solution in three use-cases, covering a diverse range of structural and operational distribution grid conditions in three European countries.

Mission of Technische Universität Dresden

The Technische Universität Dresden has developed the benchmark framework ECAST for energy forecasts that allows transparent comparison of forecasting models for different application scenarios. Our task is the integration of ECAST as part of the GOFLEX cloud service and the integration of additional forecasting models, especially those coming from IBM’s energy forecasting solution. Furthermore, we will integrate maintenance functionality into ECAST, in order to keep predictive models up-to-date in an efficient way.

Acknowledgment

This research project receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731232.

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