TY - CONF
T1 - Multi-energy systems optimization: a new formulation with linear programming for temperatures and magnitudes of thermal power flows in heating systems
AU - Hachez, Jonathan
AU - Berger, Benjamin
AU - Latiers, Arnaud
AU - Chicherin, Stanislav V.
AU - Mehmood Chaudhry, Afraz
AU - Bram, Svend
PY - 2023
Y1 - 2023
N2 - The motivation behind this work is the need to address the impact of the recent COVID-19 crisis and the Ukrainian war on the European Union’s energy landscape, pushing for sustainable smart energy solutions. The primary issue at hand is the optimization of equipment sizing for technologies like District Heating Network, Heat Pump, Thermal Energy Storage, and Photovoltaic Panels, particularly in the context of low-temperature DHNs. Our approach tackles this challenge by employing a novel formulation based on temperature levels, which effectively enhances the Coefficient of Performance of Heat Pumps and increases the energetic density of Thermal Energy Storage. The results of our methodology are exemplified through a case study of a housing unit equipped with solar panels, linked to a 5th generation DHN. The findings show impressive metrics, including 28% electric autoproduction, a seasonal COP of 4.1, and an 81% electric autoconsumption rate. This work holds significant implications for the future of energy systems in the EU, as it demonstrates a promising avenue for optimizing low-temperature DHNs. By considering equipment performance sensitivity to network temperatures, it enables the maximization of renewable energy utilization, marking a crucial step towards more sustainable and cost-effective energy solutions.
AB - The motivation behind this work is the need to address the impact of the recent COVID-19 crisis and the Ukrainian war on the European Union’s energy landscape, pushing for sustainable smart energy solutions. The primary issue at hand is the optimization of equipment sizing for technologies like District Heating Network, Heat Pump, Thermal Energy Storage, and Photovoltaic Panels, particularly in the context of low-temperature DHNs. Our approach tackles this challenge by employing a novel formulation based on temperature levels, which effectively enhances the Coefficient of Performance of Heat Pumps and increases the energetic density of Thermal Energy Storage. The results of our methodology are exemplified through a case study of a housing unit equipped with solar panels, linked to a 5th generation DHN. The findings show impressive metrics, including 28% electric autoproduction, a seasonal COP of 4.1, and an 81% electric autoconsumption rate. This work holds significant implications for the future of energy systems in the EU, as it demonstrates a promising avenue for optimizing low-temperature DHNs. By considering equipment performance sensitivity to network temperatures, it enables the maximization of renewable energy utilization, marking a crucial step towards more sustainable and cost-effective energy solutions.
M3 - Poster
ER -