Claes Sandels

531 total citations
30 papers, 425 citations indexed

About

Claes Sandels is a scholar working on Electrical and Electronic Engineering, Building and Construction and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Claes Sandels has authored 30 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Electrical and Electronic Engineering, 9 papers in Building and Construction and 8 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Claes Sandels's work include Smart Grid Energy Management (15 papers), Electric Vehicles and Infrastructure (8 papers) and Building Energy and Comfort Optimization (6 papers). Claes Sandels is often cited by papers focused on Smart Grid Energy Management (15 papers), Electric Vehicles and Infrastructure (8 papers) and Building Energy and Comfort Optimization (6 papers). Claes Sandels collaborates with scholars based in Sweden, Denmark and Italy. Claes Sandels's co-authors include Lars Nordström, Joakim Widén, Ellen Andersson, Mikael Mangold, Kristina Mjörnell, Tim Johansson, Ulrik Franke, Kun Zhu, Shahid Hussain and Kun Zhu and has published in prestigious journals such as Applied Energy, Expert Systems with Applications and Energy and Buildings.

In The Last Decade

Claes Sandels

30 papers receiving 401 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Claes Sandels Sweden 10 263 165 79 60 44 30 425
Charles R. Upshaw United States 8 309 1.2× 228 1.4× 133 1.7× 26 0.4× 33 0.8× 12 489
Yuanyi Chen China 10 154 0.6× 112 0.7× 30 0.4× 44 0.7× 40 0.9× 23 363
Jiaqi Yuan China 11 198 0.8× 226 1.4× 96 1.2× 15 0.3× 34 0.8× 25 431
Rune Grønborg Junker Denmark 9 389 1.5× 275 1.7× 141 1.8× 26 0.4× 75 1.7× 19 533
Yongwen Yang China 10 249 0.9× 108 0.7× 43 0.5× 39 0.7× 76 1.7× 46 391
Nofri Yenita Dahlan Malaysia 14 272 1.0× 112 0.7× 174 2.2× 52 0.9× 86 2.0× 80 516
Xiaojun Liu China 11 224 0.9× 134 0.8× 75 0.9× 17 0.3× 65 1.5× 24 497
Han Zhu China 11 115 0.4× 193 1.2× 31 0.4× 70 1.2× 18 0.4× 27 352
Kyung-Tae Lee South Korea 8 147 0.6× 52 0.3× 47 0.6× 50 0.8× 75 1.7× 20 404
Girish Ghatikar United States 12 400 1.5× 108 0.7× 116 1.5× 28 0.5× 180 4.1× 33 559

Countries citing papers authored by Claes Sandels

Since Specialization
Citations

This map shows the geographic impact of Claes Sandels's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Claes Sandels with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claes Sandels more than expected).

Fields of papers citing papers by Claes Sandels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Claes Sandels. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Claes Sandels. The network helps show where Claes Sandels may publish in the future.

Co-authorship network of co-authors of Claes Sandels

This figure shows the co-authorship network connecting the top 25 collaborators of Claes Sandels. A scholar is included among the top collaborators of Claes Sandels based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Claes Sandels. Claes Sandels is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Johansson, Tim, et al.. (2023). Evaluating the indoor radon concentrations in the Swedish building stock using statistical and machine learning. Journal of Physics Conference Series. 2654(1). 12086–12086. 2 indexed citations
2.
Johansson, Tim, et al.. (2023). Estimating the probability distributions of radioactive concrete in the building stock using Bayesian networks. Expert Systems with Applications. 222. 119812–119812. 5 indexed citations
3.
Mangold, Mikael, et al.. (2022). Modeling Artificial Neural Networks to Predict Asbestos-containing Materials in Residential Buildings. IOP Conference Series Earth and Environmental Science. 1122(1). 12050–12050. 2 indexed citations
4.
Sandels, Claes, et al.. (2022). Predicting the presence of hazardous materials in buildings using machine learning. Building and Environment. 213. 108894–108894. 38 indexed citations
5.
Mjörnell, Kristina, et al.. (2021). Tracing Hazardous Materials in Registered Records: A Case Study of Demolished and Renovated Buildings in Gothenburg. Journal of Physics Conference Series. 2069(1). 12234–12234. 2 indexed citations
6.
Mjörnell, Kristina, et al.. (2021). A Data-Driven Approach to Assess the Risk of Encountering Hazardous Materials in the Building Stock Based on Environmental Inventories. Sustainability. 13(14). 7836–7836. 15 indexed citations
7.
Mjörnell, Kristina, et al.. (2021). Machine Learning in Hazardous Building Material Management: Research Status and Applications. KTH Publication Database DiVA (KTH Royal Institute of Technology). 3(2). 1–15. 7 indexed citations
9.
Sandels, Claes. (2016). Modeling and Simulation of Electricity Consumption Profiles in the Northern European Building Stock. KTH Publication Database DiVA (KTH Royal Institute of Technology). 2 indexed citations
10.
Sandels, Claes, Joakim Widén, & Lars Nordström. (2015). Simulating occupancy in office buildings with non-homogeneous Markov chains for Demand Response analysis. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1–5. 11 indexed citations
11.
Sandels, Claes, Joakim Widén, Lars Nordström, & Ellen Andersson. (2015). Day-ahead predictions of electricity consumption in a Swedish office building from weather, occupancy, and temporal data. Energy and Buildings. 108. 279–290. 55 indexed citations
13.
Han, Xue, Claes Sandels, Kun Zhu, & Lars Nordström. (2013). Modelling Framework and the Quantitative Analysis of Distributed Energy Resources in Future Distribution Networks. International Journal of Emerging Electric Power Systems. 14(5). 421–431. 4 indexed citations
14.
Massucco, S., et al.. (2013). Domestic heat load aggregation strategies for wind following in electric distribution systems. CINECA IRIS Institutial Research Information System (University of Genoa). 26. 1–5. 5 indexed citations
15.
Sandels, Claes, et al.. (2013). Household aggregators development for demand response in Europe. 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013). 1487–1487. 2 indexed citations
16.
Sandels, Claes, et al.. (2013). A seasonal ARIMA model with exogenous variables for elspot electricity prices in Sweden. 1–4. 22 indexed citations
17.
Sandels, Claes, et al.. (2012). A Local Market Model for Urban Residential Microgrids with Distributed Energy Resources. 1. 1949–1958. 8 indexed citations
18.
Sandels, Claes, Ulrik Franke, & Lars Nordström. (2011). Vehicle to Grid communication - Monte Carlo simulations based on Automated Meter Reading reliability. 101(2). 158–70. 2 indexed citations
19.
20.
Sandels, Claes, et al.. (2010). Vehicle to Grid — Monte Carlo simulations for optimal Aggregator strategies. 1–8. 42 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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