Specialization

Power Systems

Email

skaggarwal@thapar.edu

Biography

Dr. S. K. Agarwal is currently Professor in the Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering & Technology, Patiala. Dr. Agarwal obtained his MTech in 2004 and PhD in 2010 from NIT, Kurukshetra. He has more than ninteen years of teaching experience and five years of industrial experience with NTPC. His current area of research interest includes power system operation and planning, forecasting issues in power systems, renewable energy systems, engineering optimization and soft computing.

Research Projects

1. “Smart demand response framework for load optimization in an electrical grid” from Haryana State Council (DST) (Ongoing)
2. “Impact analysis of renewable energy sources on power system and energy market operations” from Thapar Institute of Engineering & Technology (Ongoing)

Membership of Professional Institutions, Associations, Societies

1. Member – IEEE
2. Corporate Memebr – IE (India)

Publications and other Research Outputs

SCI: 6 + 1 (Accepted); Non-SCI: 12

Awards and Honours

1. Highly commended research paper” award from Emerald Literati Network for year 2009 for Research Paper in International Journal of Energy Sector Management.
2. Best Paper Award” in the National Conference on RAEPESM-2011 organized at Madan Mohan Malviya Engineering College, Gorakhpur.
3. Participated in the following machine learning competitions with good rankings:
   • AMS 2013-14 Solar Energy Prediction Contest (51st Rank)
   • Global Energy Forecasting Competition 2014 (8th Rank)
   • EEM2016 Real time energy price forecasting competition (3rd Rank)

 Description of Research Interests

Power system operation and planning, forecasting issues in power systems, renewable energy systems, engineering optimization and soft computing.

Publications:

• Shubham, S. Pandey, S. K. Aggarwal, and V. Chopra, “Hybrid fractional-order PIλDµ–PD control scheme for power system with modelling nonlinearities and renewable resources,” Journal of Engineering Research, vol. 14, no. 2, pp. 1759–1772, Jun. 2026.
• S. Shringi, L. M. Saini, and S. K. Aggarwal, “A review of data-driven deep learning models for solar and wind energy forecasting,” Renewable Energy Focus, no. 5, Art. no. 100739, Dec. 2025.
• S. Shringi, L. M. Saini, and S. K. Aggarwal, “Multi-step-ahead wind power forecasting based on multi-feature wavelet decomposition and convolutional gated recurrent unit model,” Electrical Engineering, vol. 107, pp. 9445–9466, 2025.
• N. Rani, S. K. Aggarwal, and S. Kumar, “Short-term load forecasting using a combination of linear and nonlinear models,” IEEE Access, 2024.
• N. Rani, S. K. Aggarwal, S. Kumar, "Combining varying training data-based artificial intelligence models for energy price forecasting," J. Chin. Inst. Eng., vol. 46, no. 7, pp. 766-780, 2023.
• S. K. Aggarwal, L. M. Saini, V. Sood, "Large wind farm layout optimization using nature inspired meta-heuristic algorithms," IETE J. Res., vol. 69, no. 5, pp. 2683-2700, 2023
• P. Jood, S. K. Aggarwal, and V. Chopra, "Adaptive Neuro-Fuzzy Based Load Frequency Control in Presence of Energy Storage Devices," Intell. Autom. Soft Comput., vol. 34, no. 2, pp. 785-804, 2022.
• S Saroha, SK Aggarwal: Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market, Recent Advances in Electrical & Electronic Engineering 13 (1), 16-26,  2020 [ESCI] .
• P Jood, SK Aggarwal, V Chopra: 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 (2019). [SCI Impact Factor 2.189].
• S Saroha, S. K. Aggarwal: Wind power forecasting using wavelet transforms and neural networks with tapped delay; CSEE Journal of Power and Energy Systems 4 (2), 197-209 (2018). [SCI Impact Factor 2.68].
• S. K. Aggarwal, and L.M. Saini, “Solar energy prediction using linear and non-linear regularization models: A study on AMS 2013-14 Solar Energy Prediction Contest,” Energy, Vol. 78, December 2014, pp. 247-256 [SCI Impact Factor 5.537]  
• S. K. Aggarwal, Arun Goel, and V.P. Singh, “Stage and discharge forecasting by ANN and SVM techniques,” Water Resources Management, Vol. 26, 2012, pp. 3705-3724 [SCI Impact Factor 2.987 ]  
• S. K. Aggarwal, L.M. Saini, Ashwani Kumar, “Parameter optimization using Genetic Algorithm for SVM based price-forecasting model in National Electricity Market,” IET – Generation, Transmission and Distribution, vol. 4, no. 1, January 2010, pp. 36-49. [SCI Impact Factor 3.229]
• S. K. Aggarwal, L.M. Saini, Ashwani Kumar, “Electricity Price Forecasting in Deregulated Markets: A Review and Evaluation”, International Journal of Electrical Power and Energy Systems, Vol. 31, Issue 1, January 2009, Pages 13-22. [SCI Impact Factor 4.418]
• S. K. Aggarwal, L.M. Saini, Ashwani Kumar, “Day-ahead price forecasting in Ontario electricity market using variable segmented Support Vector Machine based Model”, Electrical Power Components and Systems, vol. 37, no. 5, May 2009, pp. 495-516. [SCI Impact Factor 0.888]  
• S. K. Aggarwal, L.M. Saini, Ashwani Kumar, “Electric price forecasting in Ontario electricity market using wavelet transform in artificial neural network based model,” International Journal of Control, Automation and Systems,  vol. 6, no. 5, pp. 639-650, October 2008. [SCI Impact Factor 2.181]  
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Price forecasting using wavelet transform and LSE based mixed model in Australian electricity market”, International Journal of Energy Sector Management, vol. 2, no. 4,  pp. 521-546 (2008). [ESCI, Scopus]
• P Jood, SK Aggarwal, V Chopra: 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 (2019). [SCI Impact Factor 2.189].
• S Saroha, SK Aggarwal: Wind power forecasting using wavelet transforms and neural networks with tapped delay; CSEE Journal of Power and Energy Systems 4 (2), 197-209 (2018). [SCI Impact Factor 2.68].
• S.K. Aggarwal, and L.M. Saini, “Solar energy prediction using linear and non-linear regularization models: A study on AMS 2013-14 Solar Energy Prediction Contest,” Energy, Vol. 78, December 2014, pp. 247-256 [SCI Impact Factor 5.537]
• S.K. Aggarwal, Arun Goel, and V.P. Singh, “Stage and discharge forecasting by ANN and SVM techniques,” Water Resources Management, Vol. 26, 2012, pp. 3705-3724 [SCI Impact Factor 2.987 ]  
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Parameter optimization using Genetic Algorithm for SVM based price-forecasting model in National Electricity Market,” IET – Generation, Transmission and Distribution, vol. 4, no. 1, January 2010, pp. 36-49. [SCI Impact Factor 3.229]  
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Electricity Price Forecasting in Deregulated Markets: A Review and Evaluation”, International Journal of Electrical Power and Energy Systems, Vol. 31, Issue 1, January 2009, Pages 13-22. [SCI Impact Factor 4.418]  <li>
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Day-ahead price forecasting in Ontario electricity market using variable segmented Support Vector Machine based Model”, Electrical Power Components and Systems, vol. 37, no. 5, May 2009, pp. 495-516. [SCI Impact Factor 0.888]  
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Electric price forecasting in Ontario electricity market using wavelet transform in artificial neural network based model,” International Journal of Control, Automation and Systems,  vol. 6, no. 5, pp. 639-650, October 2008. [SCI Impact Factor 2.181].
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Price forecasting using wavelet transform and LSE based mixed model in Australian electricity market”, International Journal of Energy Sector Management, vol. 2, no. 4,  pp. 521-546 (2008). [ESCI, Scopus].
• S Saroha, SK Aggarwal: Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market, Recent Advances in Electrical & Electronic Engineering 13 (1), 16-26,  2020 [ESCI]
• J Singh, SK Aggarwal, A Kaur: Distribution transformer monitoring for smart grid using FPGA: a case study implementation in Indian conditions;  International Journal of Systems, Control and Communications 8 (4), 269-290 (2017). [InderScience Publishers, Scopus].
•  A Ahuja, SK Aggarwal: Application of unified Smith predictor for load frequency control with communication delays; WSEAS Transactions on Systems and Control 10, 237-248 (2015) [Scopus].
•  S Saroha, SK Aggarwal: A review and evaluation of current wind power prediction technologies; WSEAS Transaction on Power System, 10, 1-12 (2015) [Scopus].
• A Ahuja, SK Aggarwal: Design of fractional order PID controller for DC motor using evolutionary optimization techniques; WSEAS Transactions on Systems and Control 9, 171-182 (2015) [Scopus].
• S.K. Aggarwal, L.M. Saini, Ashwani Kumar, “Short term price forecasting in deregulated electricity markets: A review of statistical models and key issues”, International Journal of Energy Sector Management, vol. 3, no. 4,  pp. 333-358 (2009). [ESCI, Scopus].
• S Saroha, SK Aggarwal: Hybrid WT-PSO based Neural Networks for Single Step-Ahead Wind Power Prediction for Ontario Electricity Market; International Journal of Electrical Engineering and Informatics, vol. 7, no. 2 (July 2015) [Scopus]

Sponsored Project

• “Impact analysis of renewable energy sources on power system and energy market operations”, Supervised by (PI/CoPI), received Grant of amount pf Rs 4.90 lacs by TIET, Patiala Office Order Ref. No. TU/DORSP/57/529, Dated 04/04/2017 for the duration of 2017 to 2019.
•  "Smart Demand-Response Framework for load optimization in an Electrical Grid”, Supervised by (PI/CoPI), received Grant amount of Rs 7.28 lacs by Haryana State Council for Science and Technology (HSCST) for duration of 2017 to 2019