About the project
- SO1: Derivation of prosumers load curves (in the form of two quadrant, 2Q load models), using machine learning models.
- SO2: Embedding 2Q load models in an optimization framework for real time control in low inertia grids for scenarios including local and distributed storage.
- scientifically, following the 4M paradigm, an easier transition to the future sampled-values-waveform measurements and information retrieval will be enabled.
- economically, by an adapted control to the fast changes of systems with low inertial response: the expected output of WP4 is a methodology able to use highly time-granulated load demand and/or generation profiling (below 15 minute) of prosumers and their optimal temporal and spatial mapping with possible services to be offered in local electricity markets.
- environmental and societal, by pursuing the Green Deal objectives of “supplying clean, affordable and secure energy” through the development of smart infrastructure building blocks for future energy systems as a direct result of WP4, i.e. achieving an increased self-consumption of locally produced energy at community level and providing opportunities to participate, through aggregators, in multi-service provision across integrated electricity markets, not only for Day-Ahead.
The project will develop around the core issue in power system control, i.e. definition of the measurand for most used parameters in electric power system control: frequency; rate of change of frequency voltage and current phasors, voltage and current symmetrical components (in various coordinates- symmetrical components, alfa-beta, d-q), active power. The best choice of parameters to be used as descriptor for the (quasi-) steady state versus dynamic state, the required measurement setup and quality to issue the “steady state signal” will be analyzed. Most of the work will be done to formalize and then validate the 4M paradigm, reflecting the deviation of the assumed model for the measurement (for example, periodical, unmodulated measurand during the considered measurement window) from the reality (as “seen” by the measurement set-up after filtering and signal sampling). Further work (beyond the objectives of EMERGE) might consider synchronized measurements when the resulting information will be denominated as 5M (time stamp added).