Generation of heat and electricity load profiles with high temporal resolution for Urban Energy Units using open geodata
Bibliographic Data
| ID | 21234284 |
|---|---|
| Authors | Luis Blanco (0000-0002-2300-8385, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR), corresponding author), Alejandro Zabala (0009-0009-3252-4144, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)), Björn Schiricke (0000-0003-0572-2048, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)), Bernhard Hoffschmidt (0000-0003-4068-2053, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)) |
| Year | 2024 |
| Volume | 117 |
| Pages | 105967 |
| Publication date | 2024-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2024.105967 |
| OpenAlex | W4404436735 |
| Language | EN |
| References cited | 30 |
Urban areas account for up to 87% of global energy consumption, with around a third of CO 2 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 9 . 9 ± 7 GWh/a and an electricity demand of 2 . 3 ± 0 . 126 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. • Novel GIS-based data-driven methodology for the new German municipality heat plan. • Generating high temporal and spatial heat and electricity load profiles for any given area within Germany. • Use of the concept of Urban Energy Units (UEUs) to geographically define districts within any city or study area. • Geo-referenced procedure to estimate the urban energy demand Profiles at a district level based on UEUs
Architectural engineering · Electrical engineering · Electricity · Electricity generation · Geography · Meteorology · Physics · Remote sensing · Statistics · Urban heat island · Energy Load and Power Forecasting · Engineering · Environmental Science · Integrated Energy Systems Optimization · Mathematics · Smart Grid Energy Management
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| Highly cited | No |
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