S. K. Aggarwal

1.5k total citations · 1 hit paper
81 papers, 1.1k citations indexed

About

S. K. Aggarwal is a scholar working on Electrical and Electronic Engineering, Atmospheric Science and Astronomy and Astrophysics. According to data from OpenAlex, S. K. Aggarwal has authored 81 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Electrical and Electronic Engineering, 15 papers in Atmospheric Science and 12 papers in Astronomy and Astrophysics. Recurrent topics in S. K. Aggarwal's work include Energy Load and Power Forecasting (22 papers), Electric Power System Optimization (14 papers) and Ionosphere and magnetosphere dynamics (10 papers). S. K. Aggarwal is often cited by papers focused on Energy Load and Power Forecasting (22 papers), Electric Power System Optimization (14 papers) and Ionosphere and magnetosphere dynamics (10 papers). S. K. Aggarwal collaborates with scholars based in India, United States and United Kingdom. S. K. Aggarwal's co-authors include Lalit Mohan Saini, Ashwani Kumar, Sumit Saroha, S. P. Singal, B. Gera, Arun Goel, Vijay P. Singh, Ashwani Kumar, David Hanrahan and Gordon Hughes and has published in prestigious journals such as Journal of Computational Physics, IEEE Access and Energy.

In The Last Decade

S. K. Aggarwal

71 papers receiving 1.0k citations

Hit Papers

Electricity price forecasting in deregulated markets: A r... 2008 2026 2014 2020 2008 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Electricity price forecasting in deregulated markets: A review and evaluation
    2008 396 citations S. K. Aggarwal, Lalit Mohan Saini et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. K. Aggarwal India 15 675 161 148 132 129 81 1.1k
Jan Kloppenborg Møller Denmark 22 692 1.0× 268 1.7× 111 0.8× 90 0.7× 173 1.3× 79 1.4k
R.E. Abdel-Aal Saudi Arabia 19 526 0.8× 370 2.3× 273 1.8× 82 0.6× 188 1.5× 60 1.2k
Jethro Browell United Kingdom 18 895 1.3× 353 2.2× 131 0.9× 130 1.0× 107 0.8× 40 1.1k
Torben Skov Nielsen Denmark 15 994 1.5× 235 1.5× 94 0.6× 59 0.4× 160 1.2× 31 1.2k
Rudy Calif France 16 306 0.5× 256 1.6× 47 0.3× 152 1.2× 201 1.6× 25 735
Hongmin Li China 18 601 0.9× 265 1.6× 260 1.8× 53 0.4× 269 2.1× 33 1.1k
Henrik Aa. Nielsen Denmark 15 1.2k 1.7× 291 1.8× 99 0.7× 67 0.5× 135 1.0× 24 1.4k
Huanling Hu China 16 494 0.7× 311 1.9× 162 1.1× 33 0.3× 77 0.6× 77 984
Xiao Ling China 15 516 0.8× 171 1.1× 148 1.0× 40 0.3× 85 0.7× 44 909

Countries citing papers authored by S. K. Aggarwal

Since Specialization
Citations

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

Fields of papers citing papers by S. K. Aggarwal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. K. Aggarwal. 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 S. K. Aggarwal. The network helps show where S. K. Aggarwal may publish in the future.

Co-authorship network of co-authors of S. K. Aggarwal

This figure shows the co-authorship network connecting the top 25 collaborators of S. K. Aggarwal. A scholar is included among the top collaborators of S. K. Aggarwal 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 S. K. Aggarwal. S. K. Aggarwal 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.
Shringi, S.N., Lalit Mohan Saini, & S. K. Aggarwal. (2025). Multi-step ahead wind power forecasting based on multi-feature wavelet decomposition and convolution-gated recurrent unit model. Electrical Engineering. 107(7). 9445–9466.
2.
Aggarwal, S. K., et al.. (2019). Performance assessment of a neuro-fuzzy load frequency controller in the presence of system non-linearities and renewable penetration. Computers & Electrical Engineering. 74. 362–378. 20 indexed citations
3.
Saroha, Sumit & S. K. Aggarwal. (2019). Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market. Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering). 13(1). 16–26. 2 indexed citations
4.
5.
Maji, Sanjoy, Sirajuddin Ahmed, Weqar Ahmad Siddiqui, S. K. Aggarwal, & Anil Kumar. (2015). Impact of Di-methyl Ether (DME) as an Additive Fuel for Compression Ignition Engine in Reduction of Urban Air Pollution. American Journal of Environmental Protection. 3(2). 48–52. 5 indexed citations
6.
Saroha, Sumit & S. K. Aggarwal. (2015). Hybrid WT-PSO based Neural Networks for Single Step-Ahead Wind Power Prediction for Ontario Electricity Market. International Journal on Electrical Engineering and Informatics. 7(2). 237–249. 2 indexed citations
7.
Aggarwal, S. K., et al.. (2013). Wind Power Forecasting: A Review of Statistical Models-Wind Power Forecasting. 3(1). 10 indexed citations
8.
Singh, Jaswinder, Ravinder Singh, S. K. Aggarwal, & Lalit Mohan Saini. (2011). Design of Substation AMR and Control System with Reconfigurable Embedded System. 1(2). 1 indexed citations
9.
Aggarwal, S. K., et al.. (2009). Energy aware scheduling on desktop grid environment with static performance prediction. Spring Simulation Multiconference. 105. 5 indexed citations
10.
Aggarwal, S. K., Lalit Mohan Saini, & Ashwani Kumar. (2008). Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model. International Journal of Control Automation and Systems. 6(5). 639–650. 43 indexed citations
11.
12.
Aggarwal, S. K., et al.. (2008). A Fault Tolerance Scheme for Hierarchical Dynamic Schedulers in Grids. 3. 53–58. 7 indexed citations
13.
Aggarwal, S. K., et al.. (2007). Modeling and Verifying Non-DAG Workflows for Computational Grids. 34. 237–243. 13 indexed citations
14.
Aggarwal, S. K. & Vinai Bhagirath. (2006). MDs 'R' Us(R): Gifts for your favourite specialist. Canadian Medical Association Journal. 175(12). 1576–1577. 1 indexed citations
15.
Aggarwal, S. K., et al.. (2005). From Specifications to Code Compliance Checkers.. 287–292. 1 indexed citations
16.
Aggarwal, S. K., et al.. (2004). A technique for extracting grammar from legacy programs.. 652–657. 2 indexed citations
17.
Aggarwal, S. K.. (2004). MDs 'R' Us(R): gifts for your favourite specialist. Canadian Medical Association Journal. 171(12). 1508–1509. 1 indexed citations
18.
Aggarwal, S. K., et al.. (1991). Model evaluation of the year-to-year variability in an 11-year sunspot cycle.. Annales Geophysicae. 9(10). 696–702. 3 indexed citations
19.
Singal, S. P., et al.. (1986). Studies of sodar surface-based shear echo structures. Atmospheric Research. 20(2-4). 125–131. 5 indexed citations
20.
Prabhu, A., et al.. (1975). A Karman-Pohlhausen type approximate method for solving second order boundary layer equations. 1. 546–553. 1 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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