From building load profile to district load profile - a comparison of up-scaling methods

Combining buildings into districts aggregates the diverse peak loads from individual buildings to improve the sizing of new energy supply systems.The non-simultaneity of peak loads (both electric and thermal) is evaluated using simultaneity factors.The simultaneity factor is the maximum of the district load profile divided by the maximum of the individual load profile.As the simulation of individual buildings works very well, this publication aims to present algorithms that calculate the combined load profile of district buildings from individual building load profiles using the simultaneity factor.Four different methods are presented for this purpose: (Mean) linear scaling of the load profile to a constant mean value, (Ref. P.) scaling to a reference load profile, (N. D.) normal distribution of the load profile to the neighboring time steps and (N. D. Ref.) normal distribution of the difference between the individual building load profiles and a reference profile to the neighboring time steps.All methods take a predetermined simultaneity factor into account to smooth the maximum load peak until this simultaneity factor is met.All methods are applied to measured electrical and thermal load profiles, and the calculation accuracy is compared.The results show that linear scaling to a reference profile model has the lowest errors.The normal distribution models lead to the lowest fluctuations.

Authors

Publication Details

Journal
Proceedings of BauSIM
Published
2024-09-23
DOI
https://doi.org/10.26868/29761662.2024.21
Primary Topic
Water Systems and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From building load profile to district load profile - a comparison of up-scaling methods

Veronika Richter, Bernd Döring, Christoph van Treeck, Joachim Göttsche et al.
Proceedings of BauSIM
Water Systems and Optimization
article

From building load profile to district load profile - a comparison of up-scaling methods

Veronika Richter, Bernd Döring, Christoph van Treeck, Joachim Göttsche, Jérôme Frisch, Tobias Blanke
article en

Abstract

Combining buildings into districts aggregates the diverse peak loads from individual buildings to improve the sizing of new energy supply systems.The non-simultaneity of peak loads (both electric and thermal) is evaluated using simultaneity factors.The simultaneity factor is the maximum of the district load profile divided by the maximum of the individual load profile.As the simulation of individual buildings works very well, this publication aims to present algorithms that calculate the combined load profile of district buildings from individual building load profiles using the simultaneity factor.Four different methods are presented for this purpose: (Mean) linear scaling of the load profile to a constant mean value, (Ref. P.) scaling to a reference load profile, (N. D.) normal distribution of the load profile to the neighboring time steps and (N. D. Ref.) normal distribution of the difference between the individual building load profiles and a reference profile to the neighboring time steps.All methods take a predetermined simultaneity factor into account to smooth the maximum load peak until this simultaneity factor is met.All methods are applied to measured electrical and thermal load profiles, and the calculation accuracy is compared.The results show that linear scaling to a reference profile model has the lowest errors.The normal distribution models lead to the lowest fluctuations.

Proceedings of BauSIMVol. 10
Bundesministerium für Bildung und Forschung
Sustainable cities and communities
Openalex Percentile: Top 76%
Water Systems and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.