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Towards social digital twins - an integrated sociotechnical approach for the urban energy transition

Steven Haveman (Onderzoeker); Xiao Peng (Onderzoeker); Ran Zhang (Onderzoeker); Tadeo-Baldiri Salcedo-Rahola (Onderzoeker)

The urban energy transition is crucial for a sustainable future. To support this transition, Digital Twins are employed in an increasing fashion, providing decision makers with data-driven insights from mainly technological perspectives. Based on a case study of a neighbourhood in a Dutch municipality, …

2024Economie & ManagementConferentiebijdrage

Building and building systems energy prediction models to enhance energy flexibility control

Isa Dols (Onderzoeker); Robbert-Jan Dikken (Onderzoeker); Behrouz Eslami Mossallam (Onderzoeker); David Fortini (Onderzoeker); Sander van Gameren (Onderzoeker); Henri ter Hofte (Onderzoeker); Wim Kornaat (Onderzoeker); Yun Li (Onderzoeker); Ruud van der Linden (Onderzoeker); Bram Muller (Onderzoeker); Hossein Rahmani (Onderzoeker); Tadeo Baldiri Salcedo Rahola (Onderzoeker); Nino Visser (Onderzoeker); Kees Wisse (Onderzoeker)

The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable …

2023-08-01TechniekRapport

Time series building energy systems data imputation

Adrien Lucbert (Onderzoeker); Juliën van der Niet (Lid Lectoraat); Albert Corson (Onderzoeker); Michael Weij (Student); Ramon Isaac van der Elst (Lid Lectoraat); Jesús Mª Martínez de Juan (Onderzoeker); Tadeo Baldiri Salcedo Rahola (Docent)

Completeness of data is vital for the decision making and forecasting on Building Management Systems (BMS) as missing data can result in biased decision making down the line. This study creates a guideline for imputing the gaps in BMS datasets by comparing four methods: K Nearest Neighbour algorithm …

2022-05-20TechniekConferentiebijdrage

Times Series Building Energy Systems data Imputation

T.B. Salcedo Rahola (Docent); Juliën van der Niet (Student); MIchiel Weij (Student); Ramon Isaac van der Elst (Student)

2022Techniek; …Conferentiebijdrage

Gaining insights into dwelling characteristics using machine learning for policy making on nearly zero-energy buildings with the use of smart meter and weather data

T.B. Salcedo Rahola (Docent)

Machine learning models have proven to be reliable methods in classification tasks. However, little research has been conducted on the classification of dwelling characteristics based on smart meter and weather data before. Gaining insights into dwelling characteristics, which comprise of the type of …

2021-03-01TechniekArtikel

Samen naar een CO2 neutrale woningvoorraad.

Mark den Haan (Docent); T.B. Salcedo Rahola (Docent)

Woningcorporaties staan aan de voet van een belangrijke fase in de verduurzaming van de woningvoorraad. Er moeten ingrijpende maatregelen doorgevoerd om de woningvoorraad CO2-neutraal te maken. Maar welke beleidskeuzes en -instrumenten zijn ervoor nodig om deze transitie te versoepelen? Dat onderzocht …

2021Techniek; …Artikel

Classification of dwelling characteristics with machine learning algorithms based on smart meter & weather data

T.B. Salcedo Rahola (Lid Lectoraat)

Machine learning models have proven to be reliable methods in classification tasks. However, little research has been done on classifying dwelling characteristics based on smart meter & weather data before. Gaining insights into dwelling characteristics can be helpful to create/improve the policies for …

2020TechniekConferentiebijdrage

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