Systematic Integration of Energy-Optimal Buildings With District Networks

Raluca Suciu, Paul Stadler, Ivan Kantor, Luc Girardin and François Maréchal
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Raluca Suciu: Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland
Paul Stadler: Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland
Ivan Kantor: Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland
Luc Girardin: Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland
François Maréchal: Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland

Energies, 2019, vol. 12, issue 15, 1-38

Abstract: The residential sector accounts for a large share of worldwide energy consumption, yet is difficult to characterise, since consumption profiles depend on several factors from geographical location to individual building occupant behaviour. Given this difficulty, the fact that energy used in this sector is primarily derived from fossil fuels and the latest energy policies around the world (e.g., Europe 20-20-20), a method able to systematically integrate multi-energy networks and low carbon resources in urban systems is clearly required. This work proposes such a method, which uses process integration techniques and mixed integer linear programming to optimise energy systems at both the individual building and district levels. Parametric optimisation is applied as a systematic way to generate interesting solutions for all budgets (i.e., investment cost limits) and two approaches to temporal data treatment are evaluated: monthly average and hourly typical day resolution. The city center of Geneva is used as a first case study to compare the time resolutions and results highlight that implicit peak shaving occurs when data are reduced to monthly averages. Consequently, solutions reveal lower operating costs and higher self-sufficiency scenarios compared to using a finer resolution but with similar relative cost contributions. Therefore, monthly resolution is used for the second case study, the whole canton of Geneva, in the interest of reducing the data processing and computation time as a primary objective of the study is to discover the main cost contributors. The canton is used as a case study to analyse the penetration of low temperature, CO 2 -based, advanced fourth generation district energy networks with population density. The results reveal that only areas with a piping cost lower than 21.5 k€/100 m 2 ERA connect to the low-temperature network in the intermediate scenarios, while all areas must connect to achieve the minimum operating cost result. Parallel coordinates are employed to better visualise the key performance indicators at canton and commune level together with the breakdown of energy (electricity and natural gas) imports/exports and investment cost to highlight the main contributors.

Keywords: optimal cities; energy autonomy; low-carbon resources; multi-energy networks; parametric optimisation; CO 2 networks (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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