Richard Wies

2.5k total citations
43 papers, 1.2k citations indexed

About

Richard Wies is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Energy Engineering and Power Technology. According to data from OpenAlex, Richard Wies has authored 43 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Electrical and Electronic Engineering, 22 papers in Control and Systems Engineering and 8 papers in Energy Engineering and Power Technology. Recurrent topics in Richard Wies's work include Microgrid Control and Optimization (14 papers), Smart Grid Energy Management (10 papers) and Hybrid Renewable Energy Systems (8 papers). Richard Wies is often cited by papers focused on Microgrid Control and Optimization (14 papers), Smart Grid Energy Management (10 papers) and Hybrid Renewable Energy Systems (8 papers). Richard Wies collaborates with scholars based in United States, Puerto Rico and Canada. Richard Wies's co-authors include John W. Pierre, Daniel Trudnowski, Ronald Angelo Johnson, Ning Zhou, M. G. Anderson, Rorik Peterson, Reinaldo Tonkoski, Mariko Shirazi, Timothy M. Hansen and Jennifer King and has published in prestigious journals such as Proceedings of the IEEE, IEEE Transactions on Power Systems and IEEE Access.

In The Last Decade

Richard Wies

42 papers receiving 1.2k citations

Peers

Richard Wies
Osvaldo R. Saavedra Brazil
Feng Wu China
Mostafa Sahraei‐Ardakani United States
Vasiliki Vita Greece
S. Karaki Lebanon
Dilan Jayaweera United Kingdom
Bernhard Lange Germany
Mingbo Liu China
Nicolaos Antonio Cutululis Denmark
Octavian Curea France
Osvaldo R. Saavedra Brazil
Richard Wies
Citations per year, relative to Richard Wies Richard Wies (= 1×) peers Osvaldo R. Saavedra

Countries citing papers authored by Richard Wies

Since Specialization
Citations

This map shows the geographic impact of Richard Wies'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 Richard Wies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard Wies more than expected).

Fields of papers citing papers by Richard Wies

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard Wies. 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 Richard Wies. The network helps show where Richard Wies may publish in the future.

Co-authorship network of co-authors of Richard Wies

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Wies. A scholar is included among the top collaborators of Richard Wies 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 Richard Wies. Richard Wies 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.
Wies, Richard, et al.. (2022). A Novel Short-Term Residential Load Forecasting Methodology using Two-Stage Stacked LSTM and Hampel Filter. 2022 IEEE Power & Energy Society General Meeting (PESGM). 1–5. 4 indexed citations
2.
Hansen, Timothy M., et al.. (2021). Review of Methods to Accelerate Electromagnetic Transient Simulation of Power Systems. IEEE Access. 9. 89714–89731. 40 indexed citations
3.
Trevizan, Rodrigo D., Fabio Andrade, Mariko Shirazi, et al.. (2021). Review of Dynamic and Transient Modeling of Power Electronic Converters for Converter Dominated Power Systems. IEEE Access. 9. 82094–82117. 56 indexed citations
4.
Wies, Richard, et al.. (2021). Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions. 477–483. 4 indexed citations
5.
Barnes, Arthur K., Eduardo Cotilla‐Sanchez, Bjorn Vaagensmith, et al.. (2021). Resilience in an Evolving Electrical Grid. Energies. 14(3). 694–694. 24 indexed citations
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Aggarwal, Srijan, et al.. (2019). MicroFEWs: A Food–Energy–Water Systems Approach to Renewable Energy Decisions in Islanded Microgrid Communities in Rural Alaska. Environmental Engineering Science. 36(7). 843–849. 19 indexed citations
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Barnes, David L., et al.. (2009). Dust Measurement to Determine Effectiveness of Rural Dust Strategies. 506–511. 1 indexed citations
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Wies, Richard, et al.. (2007). Adaptive Filtering Techniques for Estimating Electromechanical Modes in Power Systems. IEEE Power Engineering Society General Meeting. 1–8. 7 indexed citations
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Wies, Richard, et al.. (2006). Combining least mean squares adaptive filter and auto-regressive block processing techniques for estimating the low-frequency electromechanical modes in power systems. 2006 IEEE Power Engineering Society General Meeting. 8 pp.–8 pp.. 24 indexed citations
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Wies, Richard, et al.. (2005). Optimization of a PV with Diesel-BatterySystemfor Remote Villages. International Energy Journal. 6. 1 indexed citations
18.
Wies, Richard, et al.. (2005). Integration of Wind-Turbine Generators (WTGs) into Hybrid Distributed Generation Systems in Extreme Northern Climates. 2 indexed citations
19.
Anderson, Mark, Ning Zhou, John W. Pierre, & Richard Wies. (2005). Bootstrap-based confidence interval estimates for electromechanical modes from multiple output analysis of measured ambient data. IEEE Power Engineering Society General Meeting, 2005. 762–762. 3 indexed citations
20.
Wies, Richard, John W. Pierre, & Daniel Trudnowski. (2002). Use of ARMA Block Processing for Estimating Stationary Low-Frequency Electromechanical Modes of Power Systems. IEEE Power Engineering Review. 22(11). 57–57. 5 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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