Systematic Integration of Energy-Optimal Buildings With District Networks

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 sec...

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Main Authors: Raluca Suciu, Paul Stadler, Ivan Kantor, Luc Girardin, François Maréchal
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/15/2945
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spelling doaj-2c2550e4feb446c19aacef074bfc2fc32020-11-25T01:57:01ZengMDPI AGEnergies1996-10732019-07-011215294510.3390/en12152945en12152945Systematic Integration of Energy-Optimal Buildings With District NetworksRaluca Suciu0Paul Stadler1Ivan Kantor2Luc Girardin3François Maréchal4Industrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, SwitzerlandIndustrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, SwitzerlandIndustrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, SwitzerlandIndustrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, SwitzerlandIndustrial Process and Energy Systems Engineering (IPESE), École Polytechnique Fédérale de Lausanne, CH-1951 Sion, SwitzerlandThe 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<sub>2</sub>-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&#8364;/100 m<sup>2</sup><sub>ERA</sub> 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.https://www.mdpi.com/1996-1073/12/15/2945optimal citiesenergy autonomylow-carbon resourcesmulti-energy networksparametric optimisationCO<sub>2</sub> networks
collection DOAJ
language English
format Article
sources DOAJ
author Raluca Suciu
Paul Stadler
Ivan Kantor
Luc Girardin
François Maréchal
spellingShingle Raluca Suciu
Paul Stadler
Ivan Kantor
Luc Girardin
François Maréchal
Systematic Integration of Energy-Optimal Buildings With District Networks
Energies
optimal cities
energy autonomy
low-carbon resources
multi-energy networks
parametric optimisation
CO<sub>2</sub> networks
author_facet Raluca Suciu
Paul Stadler
Ivan Kantor
Luc Girardin
François Maréchal
author_sort Raluca Suciu
title Systematic Integration of Energy-Optimal Buildings With District Networks
title_short Systematic Integration of Energy-Optimal Buildings With District Networks
title_full Systematic Integration of Energy-Optimal Buildings With District Networks
title_fullStr Systematic Integration of Energy-Optimal Buildings With District Networks
title_full_unstemmed Systematic Integration of Energy-Optimal Buildings With District Networks
title_sort systematic integration of energy-optimal buildings with district networks
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-07-01
description 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<sub>2</sub>-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&#8364;/100 m<sup>2</sup><sub>ERA</sub> 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.
topic optimal cities
energy autonomy
low-carbon resources
multi-energy networks
parametric optimisation
CO<sub>2</sub> networks
url https://www.mdpi.com/1996-1073/12/15/2945
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AT paulstadler systematicintegrationofenergyoptimalbuildingswithdistrictnetworks
AT ivankantor systematicintegrationofenergyoptimalbuildingswithdistrictnetworks
AT lucgirardin systematicintegrationofenergyoptimalbuildingswithdistrictnetworks
AT francoismarechal systematicintegrationofenergyoptimalbuildingswithdistrictnetworks
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