Description
EMERGE at a glance
Type of action: Exploratory Research
Grant Number: PCE-2020-2876
Start Date: 04/01/2021
End date: 31/12/2023
Project Coordinator: UPB
Objectives
EMERGE aims to define and validate a new measurement framework for emerging power systems and its validation for selected measurands. In addition, we aim at defining prosumers load curves and embedded 2Q load models.
Topics
The project addresses how to accurately extract information in non-stationary power signals from measurements delivering a measurement result and the associated metrological quality (2M paradigm). The measurand (e.g. frequency of a voltage signal) is represented by a parameter in an a-priori accepted model (periodical, quasi-sinusoidal voltage waveform). Foreseen activities:
- Framing information in non-stationary power signals with an additional flagging concept (3S) and a procedure to derive a steady-state signal.
- An enhanced definition (4M paradigm) by including the steady state flag derived from frequency measurements and with various application-selected thresholds and window durations.
- Machine learning models to provide accurate predictions for high-level multi-scale optimization tasks in energy systems.
Objectives
Main objective of EMERGE is to define and validate a new measurement framework for emerging power systems and its validation for selected measurands: frequency, rate of change of frequency, voltage and current phasors, active power in at least two scenarios defined by the phenomena dynamics (and reflected in the selected reporting rate if the measurements and associated steady state flagging concept).
Secondary objectives are:
- 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.
Impact
The impact of EMERGE can be seen as three-folded:
- (i) scientifically, following the 4M paradigm, an easier transition to the future sampled-values-waveform measurements and information retrieval will be enabled.
- (ii) economically, by an adapted control to the fast changes of systems with low inertial response: 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.
- (iii) 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.