Luis Blanco , Alejandro Zabala , Björn Schiricke , Bernhard Hoffschmidt
{"title":"Generation of heat and electricity load profiles with high temporal resolution for Urban Energy Units using open geodata","authors":"Luis Blanco , Alejandro Zabala , Björn Schiricke , Bernhard Hoffschmidt","doi":"10.1016/j.scs.2024.105967","DOIUrl":null,"url":null,"abstract":"<div><div>Urban areas account for up to 87% of global energy consumption, with around a third of CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions from the building sector. Germany recently enacted a law targeting carbon neutrality in heating by 2045, requiring all municipalities to submit transformation plans for their heating infrastructure. Many are in early stages and need innovative methods to achieve these goals. This study proposes an automated GIS-based approach to generate heat and electricity load profiles for geographically referenced residential buildings and districts in Germany, using only open data. The methodology offers hourly temporal resolution and spatial detail from individual buildings to Urban Energy Units (UEUs), a concept introduced in prior studies. Nine distinct heating load profiles and nine electricity load profiles were identified. These profiles can adapt to different weather datasets and to three building refurbishment scenarios. The methodology and energy analysis were applied to a district in Oldenburg, Germany, demonstrating the model’s flexibility under varying boundary conditions. For this district, the analysis revealed a total heat demand of <span><math><mrow><mn>9</mn><mo>.</mo><mn>9</mn><mo>±</mo><mn>7</mn></mrow></math></span> GWh/a and an electricity demand of <span><math><mrow><mn>2</mn><mo>.</mo><mn>3</mn><mo>±</mo><mn>0</mn><mo>.</mo><mn>126</mn></mrow></math></span> GWh/a, with respective errors of 45% and 39% when compared to other local data, this demand is presented in both yearly and hourly resolutions. This methodology intends to support German municipalities by accelerating the initial phases of the municipal heating plans and deliver high-quality data on building heat and electricity demand.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105967"},"PeriodicalIF":10.5000,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724007911","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Urban areas account for up to 87% of global energy consumption, with around a third of CO emissions from the building sector. Germany recently enacted a law targeting carbon neutrality in heating by 2045, requiring all municipalities to submit transformation plans for their heating infrastructure. Many are in early stages and need innovative methods to achieve these goals. This study proposes an automated GIS-based approach to generate heat and electricity load profiles for geographically referenced residential buildings and districts in Germany, using only open data. The methodology offers hourly temporal resolution and spatial detail from individual buildings to Urban Energy Units (UEUs), a concept introduced in prior studies. Nine distinct heating load profiles and nine electricity load profiles were identified. These profiles can adapt to different weather datasets and to three building refurbishment scenarios. The methodology and energy analysis were applied to a district in Oldenburg, Germany, demonstrating the model’s flexibility under varying boundary conditions. For this district, the analysis revealed a total heat demand of GWh/a and an electricity demand of GWh/a, with respective errors of 45% and 39% when compared to other local data, this demand is presented in both yearly and hourly resolutions. This methodology intends to support German municipalities by accelerating the initial phases of the municipal heating plans and deliver high-quality data on building heat and electricity demand.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;