Assessment of varying coupling levels between electric and thermal networks at district level using Co-simulation and model-predictive Control

Luca Rava (1, 2) , Audrey Wantier (1, 2) , Mathieu Vallee (1, 3) , Alain Ruby (1, 3) , Nicolas Lamaison (1, 3)

1 DTS - Département des Technologies Solaires
2 DTNM - Département des Technologies des Nouveaux Matériaux (Ex Département des Technologies des NanoMatériaux)
3 DTCH - Département Thermique Conversion et Hydrogène

This study focuses on the co-simulation of the heating and electrical systems of a district. A heat pump, a gas boiler, a biomass cogeneration, a photovoltaic plant and the national electric grid provide electricity and heat consumed by thirteen residential buildings. Two storage units are present: a heat storage (hot water tank) and an electric storage (chemical battery). Architecture design and pre-sizing of components have previously been computed by MILP optimizations. As part of the Trilogy platform, a co-simulation platform Pegase runs the grid control and the detailed physical models developed using Modelica (heat system) and Simulink (electric system). A model predictive control (MPC) based on sliding time window MILP optimisations manages the flexibility of the multi energy system and insures the balance between production and consumption. The objective of the optimizations is to minimise CO2 equivalent emission costs and operational costs of each component, including the purchase of gas, biomass and electricity. A parametric study on the coupling strength between the electric and the heat system is performed by modifying the price of the electricity purchased from the national grid. Multiple scenarios with different thermoelectric coupling strength are analysed to show the dependency of the energy mix on the coupling strength. With increasing coupling, photovoltaic self-consumption increases and heat generation gradually shifts from the heat pump to the biomass cogeneration and to the gas boiler. This study also demonstrates how the Trilogy platform tools enable easy implementation of optimal control on cosimulations of multi energy detailed physical models.

Domaines: Energie électrique

Luca Rava, Audrey Wantier, Mathieu Vallee, Alain Ruby, Nicolas Lamaison. Assessment of varying coupling levels between electric and thermal networks at district level using Co-simulation and model-predictive Control. ECOS 2022 - Efficiency, Cost, Optimization and Simulation of energy conversion systems and processes, Jul 2022, Copenhague, Denmark. pp.919. ⟨cea-04090550⟩