Method for the systematic integration of multi-energy networks and low carbon resources in cities

The design and operation of building energy systems (BES) has become a subject of great interest, given the latest energy policies adapted around the world, namely increasing the energy efficiency and the share of renewable energy sources (RES) while reducing greenhouse gas emissions related to the provision of domestic energy services. Within the latter context, this work addresses the issue of optimal sizing and operation of BES while integrating an advanced CO2 based district energy network. Indeed, unlike common water based networks which use sensible heat, the former exploits the phase change enthalpy to realize the heat transfer when interacting with the different end users as well as with the environment [1]–[4]. The related optimization problem is formulated using a mixed integer linear programming (MILP) technique, a suitable method to represent both the continuous and discrete behaviour of BES [5]. The objective function is represented by the sum of the operating and annualized investment costs (i.e. the total annual project expenses) while the integrated system is subject to mass and energy balances, heat cascade and other additional constraints. In order to decrease the computational complexity of the aforementioned problem a PAM algorithm is implemented, thus generating several typical operating periods regarding the region of interest [6]. Different case studies are performed in view of fully assessing the potential of advanced CO2 based district energy network; the different technologies include water-water heat pumps, photovoltaic arrays, water based buffer tanks and electric storage units. In addition, in regard to the implemented model formulation [7], [8], heat might be stored directly in the dwelling, thus providing a further storage capacity. The presented study hence tackles multiple research questions among which, the optimal network distribution operating conditions (i.e. supply and return temperatures) when considering optimal on the end-user side. Indeed, in regard to the different temperature thresholds related to the different domestic heating requirements, trade-off solutions must be defined to assess the best system efficiency, i.e. considering the COPs of both the network and the dwelling operators. Another aspect considered is the building construction period, which has a strong impact on both the thermal energy demand and the required temperatures of supply. Therefore, two types of buildings are considered, namely existing and new, during the different case studies, based on their respective shares in the built environment. Finally, in order to address the impact of the novel district energy network on the use of electricity storage units, different RES penetration levels are analysed. References [1] C. Weber, “CO2 BASED DISTRICT ENERGY SYSTEM,” 2008. [2] S. Henchoz, C. Weber, F. Maréchal, and D. Favrat, “Performance and profitability perspectives of a CO2 based district energy network in Geneva’s City Centre,” Energy, vol. 85, pp. 221–235, Jun. 2015. [3] Raluca Suciu, Paul Stadler, Araz Ashouri, and François Maréchal, “Towards energy-autonomous cities using CO2 networks and Power to Gas storage, ECOS Proceedings 2016.” ECOS Proceedings 2016, 2016. [4] R. Suciua, L. Girardin, and F. Marechal, “Energy integration of CO2 networks and Power to Gas for emerging energy autonomous cities in Europe,” Submitt. 30th Int. Conf. Effic. Cost Optim. Simul. Environ. Impact Energy Syst., 2017. [5] A. Bemporad and M. Morari, “Control of systems integrating logic, dynamics, and constraints,” Automatica, vol. 35, no. 3, pp. 407–427, Mar. 1999. [6] J. M. F. Rager, “Urban Energy System Design from the Heat Perspective using mathematical Programming including thermal Storage,” EPFL thesis nr. 6731. [7] A. Ashouri, “Simultaneous Design and Control of Energy Systems,” Diss., Eidgenössische Technische Hochschule ETH Zürich, Nr. 21908, 2014, 2014. [8] L. Girardin, F. Marechal, M. Dubuis, N. Calame-Darbellay, and D. Favrat, “EnerGis: A geographical information based system for the evaluation of integrated energy conversion systems in urban areas,” Energy, vol. 35, no. 2, pp. 830–840, 2010.