In an effort to address the growing energy demand while decreasing the environmental impact of power generation, distribution networks are experiencing a progressive shift towards decentralized generation. However, the increasing penetration of highly stochastic and periodic renewable energy sources (e.g. photovoltaics) is rendering the operation of power networks increasingly challenging.
The aim of this work is study both the design and operation of distributed energy system configurations to improve the connection capacity of the current grid without raising the need of overhauling the entire network. Mainly focusing on residential building applications, this research work considers both the interests of the end-users and the grid operator to reach satisfying trade-off solutions. Energy integration and model predictive control schemes are applied to face the aforementioned challenges.
P. Stadler; L. Girardin; A. Ashouri; F. Maréchal : Contribution of Model Predictive Control in the Integration of Renewable Energy Sources within the Built Environment; Frontiers in Energy Research. 2018-05-03. DOI : 10.3389/fenrg.2018.00022.
P. Stadler; L. Girardin; F. Marechal : The swiss potential of model predictive control for building energy systems, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe). 2017. 017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Torino, Italy, september 26-29, 2017. p. 1-6. DOI : 10.1109/ISGTEurope.2017.8260100.
P. Stadler; A. Ashouri; F. Marechal : Distributed model predictive control of energy systems in microgrids. 2016. 2016 Annual IEEE Systems Conference (SysCon), Orlando, FL, USA, 18-21 April 2016. p. 1-6. DOI : 10.1109/SYSCON.2016.7490607.
P. Stadler; A. Ashouri; F. Maréchal : Model-based optimization of distributed and renewable energy systems in buildings; Energy and Buildings. 2016. DOI : 10.1016/j.enbuild.2016.03.051.