Yingzhong Gu

1.0k total citations
31 papers, 800 citations indexed

About

Yingzhong Gu is a scholar working on Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality and Control and Systems Engineering. According to data from OpenAlex, Yingzhong Gu has authored 31 papers receiving a total of 800 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 11 papers in Safety, Risk, Reliability and Quality and 6 papers in Control and Systems Engineering. Recurrent topics in Yingzhong Gu's work include Electric Power System Optimization (12 papers), Power System Reliability and Maintenance (11 papers) and Energy Load and Power Forecasting (9 papers). Yingzhong Gu is often cited by papers focused on Electric Power System Optimization (12 papers), Power System Reliability and Maintenance (11 papers) and Energy Load and Power Forecasting (9 papers). Yingzhong Gu collaborates with scholars based in United States, China and Saudi Arabia. Yingzhong Gu's co-authors include Le Xie, Xinxin Zhu, Marc G. Genton, M. Ehsani, Dan Li, Yuanhang Zhang, Jiahao Yan, Di Shi, Zhe Yu and Dan Li and has published in prestigious journals such as Journal of Cleaner Production, IEEE Transactions on Power Systems and Energy Conversion and Management.

In The Last Decade

Yingzhong Gu

30 papers receiving 776 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingzhong Gu United States 14 707 191 108 90 79 31 800
Hrvoje Keko Portugal 13 839 1.2× 130 0.7× 90 0.8× 59 0.7× 140 1.8× 31 944
Kurt Rohrig Germany 9 890 1.3× 383 2.0× 155 1.4× 174 1.9× 140 1.8× 22 1.1k
Cameron Potter Australia 10 694 1.0× 138 0.7× 200 1.9× 159 1.8× 54 0.7× 17 760
Mohammed Wadi Türkiye 14 395 0.6× 248 1.3× 68 0.6× 74 0.8× 103 1.3× 49 571
Ying Qiao China 18 955 1.4× 409 2.1× 96 0.9× 89 1.0× 85 1.1× 105 1.1k
Xueshan Han China 20 1.1k 1.5× 447 2.3× 156 1.4× 104 1.2× 136 1.7× 150 1.3k
Junhui Huang China 11 629 0.9× 182 1.0× 74 0.7× 40 0.4× 101 1.3× 34 679
Gonggui Chen China 17 801 1.1× 310 1.6× 136 1.3× 48 0.5× 104 1.3× 49 991
Jean Sumaili Portugal 17 1.3k 1.9× 366 1.9× 121 1.1× 57 0.6× 181 2.3× 45 1.4k
Nikita Tomin Russia 16 551 0.8× 325 1.7× 105 1.0× 24 0.3× 63 0.8× 83 763

Countries citing papers authored by Yingzhong Gu

Since Specialization
Citations

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

Fields of papers citing papers by Yingzhong Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingzhong Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Yingzhong Gu. A scholar is included among the top collaborators of Yingzhong Gu 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 Yingzhong Gu. Yingzhong Gu 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.
Li, Dan, et al.. (2023). Fitting wind speed and wind direction probability distribution using mixture B-spline function. Sustainable Energy Technologies and Assessments. 60. 103513–103513. 3 indexed citations
2.
Liu, Songkai, et al.. (2023). Neyman-Pearson Umbrella Algorithm-Based Static Voltage Stability Assessment With Misclassification Restriction: An Integrated Data-Driven Scheme. IEEE Transactions on Industrial Informatics. 19(12). 11391–11402. 6 indexed citations
3.
Xiong, Haoran, et al.. (2021). A two-phase wind speed simulation model considering diurnal and seasonal patterns and its application to adequacy assessment. Journal of Renewable and Sustainable Energy. 13(5). 4 indexed citations
4.
Gu, Yingzhong, et al.. (2021). Neural-network-based Power System State Estimation with Extended Observability. Journal of Modern Power Systems and Clean Energy. 9(5). 1043–1053. 22 indexed citations
5.
Gu, Yingzhong, Zhe Yu, Qibing Zhang, et al.. (2021). Enhanced denosing autoencoder aided bad data filtering for synchrophasor-based state estimation. CSEE Journal of Power and Energy Systems. 2 indexed citations
6.
Gu, Yingzhong, Zhe Yu, Ruisheng Diao, & Di Shi. (2020). Doubly-fed Deep Learning Method for Bad Data Identification in Linear State Estimation. Journal of Modern Power Systems and Clean Energy. 8(6). 1140–1150. 11 indexed citations
7.
Gu, Yingzhong, et al.. (2019). Determining suitable region wind speed probability distribution using optimal score-radar map. Energy Conversion and Management. 183. 590–603. 26 indexed citations
8.
Li, Chunyan, et al.. (2018). Optimal spatio-temporal scheduling for Electric Vehicles and Load Aggregators considering response reliability. Electric Power Systems Research. 162. 183–193. 38 indexed citations
9.
Yang, Hejun, et al.. (2018). A wind vector simulation model and its application to adequacy assessment. Energy. 148. 324–340. 13 indexed citations
10.
Xie, Le, Yingzhong Gu, Xinxin Zhu, & Marc G. Genton. (2016). Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 1–1. 4 indexed citations
11.
Gu, Yingzhong & Le Xie. (2015). Fast sensitivity analysis approach to assessing congestion induced wind curtailment. 1–1. 6 indexed citations
12.
Xie, Le, Yingzhong Gu, Xinxin Zhu, & Marc G. Genton. (2013). Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch. IEEE Transactions on Smart Grid. 5(1). 511–520. 176 indexed citations
13.
Xie, Le, Lin Cheng, & Yingzhong Gu. (2013). Reliability Assessment at Day-Ahead Operating Stage in Power Systems with Wind Generation. 16. 2245–2251. 6 indexed citations
14.
Gu, Yingzhong & Le Xie. (2013). Fast Sensitivity Analysis Approach to Assessing Congestion Induced Wind Curtailment. IEEE Transactions on Power Systems. 29(1). 101–110. 66 indexed citations
15.
Gu, Yingzhong & Le Xie. (2012). Look-ahead dispatch with forecast uncertainty and infeasibility management. 1–7. 12 indexed citations
16.
Xie, Le, et al.. (2012). Fast MPC-Based Coordination of Wind Power and Battery Energy Storage Systems. Journal of Energy Engineering. 138(2). 43–53. 62 indexed citations
17.
Xie, Le, Anupam A. Thatte, & Yingzhong Gu. (2011). Multi-time-scale modeling and analysis of energy storage in power system operations. 1–6. 10 indexed citations
18.
Gu, Yingzhong, et al.. (2011). Congestion-induced wind curtailment: Sensitivity analysis and case studies. 1–7. 15 indexed citations
19.
Xie, Le, Yingzhong Gu, Xinxin Zhu, & Marc G. Genton. (2011). Power system economic dispatch with spatio-temporal wind forecasts. 20 indexed citations
20.
Gu, Yingzhong & Le Xie. (2010). Look-ahead coordination of wind energy and electric vehicles: A market-based approach. 1–8. 24 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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