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Claes Sandels
Claes Sandels
Research Institutes of Sweden (RISE)
Verified email at ri.se - Homepage
Title
Cited by
Cited by
Year
Forecasting household consumer electricity load profiles with a combined physical and behavioral approach
C Sandels, J Widén, L Nordström
Applied Energy 131, 267-278, 2014
1112014
Day-ahead predictions of electricity consumption in a Swedish office building from weather, occupancy, and temporal data
C Sandels, J Widén, L Nordström, E Andersson
Energy and Buildings 108, 279-290, 2015
772015
Vehicle to grid—Monte Carlo simulations for optimal aggregator strategies
C Sandels, U Franke, N Ingvar, L Nordström, R Hamren
2010 International Conference on Power System Technology, 1-8, 2010
712010
Modeling office building consumer load with a combined physical and behavioral approach: Simulation and validation
C Sandels, D Brodén, J Widén, L Nordström, E Andersson
Applied energy 162, 472-485, 2016
522016
A seasonal ARIMA model with exogenous variables for elspot electricity prices in Sweden
M Xie, C Sandels, K Zhu, L Nordström
2013 10th International conference on the European energy market (EEM), 1-4, 2013
422013
Predicting the presence of hazardous materials in buildings using machine learning
PY Wu, C Sandels, K Mjörnell, M Mangold, T Johansson
Building and Environment 213, 108894, 2022
272022
Vehicle to grid—reference architectures for the control markets in Sweden and Germany
C Sandels, U Franke, N Ingvar, L Nordström, R Hamrén
2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2010
182010
Using machine learning to enrich building databases—methods for tailored energy retrofits
J Von Platten, C Sandels, K Jörgensson, V Karlsson, M Mangold, ...
Energies 13 (10), 2574, 2020
172020
A local market model for urban residential microgrids with distributed energy resources
A Jalia, N Honeth, C Sandels, L Nordstrom
2012 45th Hawaii International Conference on System Sciences, 1949-1958, 2012
172012
Simulating occupancy in office buildings with non-homogeneous Markov chains for demand response analysis
C Sandels, J Widén, L Nordström
2015 IEEE Power & Energy Society General Meeting, 1-5, 2015
162015
Domestic heat load aggregation strategies for wind following in electric distribution systems
F Baccino, S Massucco, C Sandels, L Nordström
2013 IEEE Power & Energy Society General Meeting, 1-5, 2013
132013
Trustworthy injection/curtailment of DER in distribution network maintaining quality of service
S Hussain, N Honeth, R Gustavsson, C Sandels, A Saleem
2011 16th International Conference on Intelligent System Applications to …, 2011
122011
Empirical analysis for Distributed Energy Resources' impact on future distribution network
X Han, C Sandels, K Zhu, L Nordström, P Söderström
2012 IEEE International Energy Conference and Exhibition (ENERGYCON), 731-737, 2012
102012
A data-driven approach to assess the risk of encountering hazardous materials in the building stock based on environmental inventories
PY Wu, K Mjörnell, M Mangold, C Sandels, T Johansson
Sustainability 13 (14), 7836, 2021
92021
Clustering Residential Customers with Smart Meter data using a Data Analytic Approach–External Validation and Robustness Analysis
C Sandels, M Kempe, M Brolin, A Mannikoff
2019 9th International Conference on Power and Energy Systems (ICPES), 1-6, 2019
92019
Machine learning in hazardous building material management: research status and applications
PY Wu, K Mjörnell, C Sandels, M Mangold
Recent Progress in Materials 3 (2), 2021
72021
Aggregator strategy for planning demand response resources under uncertainty based on load flexibility modeling
K Paridari, L Nordstrom, C Sandels
2017 IEEE International Conference on Smart Grid Communications …, 2017
72017
Modeling and simulation of electricity consumption profiles in the northern European building stock
C Sandels
KTH Royal Institute of Technology, 2016
72016
Controlling a retailer's short‐term financial risk exposure using demand response
M Brolin, C Sandels
IET Generation, Transmission & Distribution 13 (22), 5160-5170, 2019
62019
Modelling framework and the quantitative analysis of distributed energy resources in future distribution networks
X Han, C Sandels, K Zhu, L Nordström
International Journal of Emerging Electric Power Systems 14 (5), 421-431, 2013
62013
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