Joint Energy and Water Management aims at developing a multi-spatial/temporal model that couples the energy systems (i.e., electrical, transportation, heating, and cooling) amongst themselves and the water systems. This model will rely on an efficient and stable renewable energy resource (RES) production optimization and management.
Emphasis will be on the grid integration of RES and the development of an accurate and reliable RES forecasting tool at various timescales. The resulting model will be validated at: a datacenter at the EPFL (see description under WP3) and a real-life demo site in Aigle (VD).
This demo site is representative of a typical Swiss mixed rural/urban area hosting sizable stochastic renewable generation with peak power higher than the local demand. The demonstrator accommodates a total photovoltaic power generation of 3.2 MWp and 4 hydropower plants. The power demand reaches 4.3 MW in winter and 2.9 MW in summer. The demonstrator also hosts a 1.5MW / 2.5 MWh battery energy storage system and a controllable fast EV charging station.
Joint Energy and Water Management tasks include:
- Develop a detailed multi-spatial/temporal model for integrating renewable energy hubs as elements of coupled energy systems in Switzerland and beyond.
- Develop tools for accurate and reliable forecasting of stochastic power generation and consumption, and the corresponding sustainability impacts at various time scales (i.e., seasonal, monthly, daily and quasi real-time).
- Generate a joint predictive model for clean water and energy use, based on advanced monitoring techniques, deep and self-learning, and prospective simulation to set science-based targets for energy transition and efficient clean water collection, treatment and use.
- Produce operation-aware planning of coupled energy/transportation and clean water systems based on techno-economic aspects, and sustainability targets.
- Validation of the developed model at the demo sites in Aigle (VD) and in Lausanne (VD) and at a datacenter at the EPFL.
Research Partners
Industrial Partners
Publications
A Comparative Analysis of Empirical Copula and Quantile Regression Methods for Probabilistic Load Forecasting | |||
Perna, Sara; Austnes, Pal Forr; Gerini, Francesco; Chevron, Max; Di Fazio, Anna Rita; De Falco, Pasquale; Paolone, Mario | |||
2024-06-24 | 18th International Conference on Probabilistic Methods Applied to Power Systems | ||
Decomposition method to evaluate district heating/cooling network potential at urban scale | |||
Gouveia Braz, Ana Catarina; Briguet, Raphael; Girardin, Luc; Liu, Bingqian; Maréchal, François | |||
2024-06-01 | Book of Abstract of the 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering (ESCAPE34/PSE24), June 2-6, 2024, Florence, Italy | ||
SAT-based Exact Modulo Scheduling Mapping for Resource-Constrained CGRAs | |||
Tirelli, Cristian; Sapriza, Juan; Rodriguez Alvarez, Ruben; Ferretti, Lorenzo; Denkinger, Benoit Walter; Ansaloni, Giovanni; Miranda Calero, Jose Angel; Atienza Alonso, David; Pozzi, Laura | |||
2024-04-08 | ACM Journal on Emerging Technologies in Computing Systems |