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Faculty Directory Dr. Ankit Kumar Sharma
Dr. Ankit Kumar Sharma

Dr. Ankit Kumar Sharma

Professor and Head

[email protected]
Vidwan Profile Google Scholar

Academic Information

Ph.D., M.Tech. (Power System) MIEEE, MASHRAE, MIAENG, MASR

Research Areas

Demand Response Techniques and Renewable Integrations Consumer Baseline Load (CBL) Electricity Tariffs AI & ML Neural Nets (Classifications Regression and Clustering) Voltage Stability Assessment and Control FACTS Devices and Costing of FACTS Devices Evolutionary Algorithms and Optimization Techniques

Research Interests

My research interest focuses on AI-driven demand response and voltage stability enhancement in renewable-integrated power systems. It includes consumer baseline load modeling and intelligent electricity tariff design to improve demand-side participation. Machine learning and neural networks—using classification, regression, and clustering—are applied for load forecasting, consumer segmentation, and demand response optimization. Voltage stability assessment and control are addressed through the optimal placement and sizing of FACTS devices, considering technical performance and economic costing. Evolutionary algorithms and advanced optimization techniques are employed to solve multi-objective problems involving system stability, operational efficiency, and cost minimization.

Courses Taught

Digital Electronics, Analog Electronics, Electrical Machine Design, AI & ML, Basic Electrical Engineering, Power Systems, Control Systems, Generation of Electrical Power, Transmission and Distribution, Switch Gear Protection, FACTS devices, etc.

Positions Held

1. I am currently working as Head & Professor in the Department of Electrical Engineering
at University of Engineering & Management, Jaipur since 22nd July 2019.
2. Serving as a coordinator of ICT Academy in University of Engineering & Management,
Jaipur
3. Serving as a coordinator of IEEMA in University of Engineering & Management, Jaipur

Publications

1. Jain, V.K., Soni, B.P. & Sharma, A.K. Impact of class-specific demand response strategies on load profiles and cost reduction in power distribution networks. Electr Eng 108, 108 (2026). (SCI) 2. Sharma, Ankit Kumar, Devendra Kumar Doda, Bhanu Pratap Soni, Ramesh C. Bansal, and Dheeraj Kumar Palwalia. "A Systematic Approach to Improving Consumers’ Comfort through on-Grid Renewable Energy Integration and Battery Storage." Electric Power Components and Systems (2023): 1-25. (SCI) 3. Sharma, Ankit Kumar, Akash Saxena, Dheeraj Kumar Palwalia, and Ramesh C. Bansal. "Calculation of Consumer Baseline Load for Residential Sectors in the Context of Smart Grid." Electric Power Components and Systems, Taylor & Francis (2023): 1-19. (SCI) 4. Sharma, Ankit Kumar, Akash Saxena, and D. K. Palwalia. "Oppositional Slime Mould Algorithm: Development and application for designing demand side management controller." Expert Systems with Applications, Elsevier 214 (2023): 119002. (SCI) 5. Sharma, Ankit Kumar, Ahmad M. Alshamrani, Khalid A. Alnowibet, Adel F. Alrasheedi, Akash Saxena, and Ali Wagdy Mohamed. "A Demand Side Management Control Strategy Using RUNge Kutta Optimizer (RUN)." Axioms, MDPI, 11, no. 10 (2022): 538. (SCI) 6. Sharma, Ankit Kumar, Akash Saxena, and Dheeraj Kumar Palwalia. "Supervised learning‐ based demand response simulator with incorporation of real time pricing and peak time rebate." International Transactions on Electrical Energy Systems, Wiley 31, no. 12 (2021): e13229. (SCI) 7. Jain, V.K., Soni, B.P., Sharma, A.K. (2026). A Comprehensive Review of Demand Response in Smart Grids: Challenges, Opportunities, and Future Directions. In: Yadav, A., Silva, K.M.e., Bhalja, B.R. (eds) AI-Driven Solutions and Emerging Power Technologies for Sustainable Future. ETAEE 2024. Lecture Notes in Electrical Engineering, vol 1485. Springer, Singapore. (SCOPUS) 8. Ratra, S., Soni, B. P., Singh, S., Sharma, A. K., & Goyal, A. (2025). A Hybrid Approach for Coordinated Voltage Stability Control using amalgamation of Fuzzy and Taguchi Method. Procedia Computer Science, Elsevier 259, 826-835. (SCOPUS) 9.Pande, A. S., Soni, B. P., & Sharma, A. K. (2025). Modeling of one and two RC model and state estimation of Lithium-Ion Battery using Thevenin’s equivalent Circuit Model. Procedia Computer Science, Elsevier 259, 494-503. (SCOPUS) 10.Murade, G. B., Sharma, A. K., Soni, B. P., Pande, A. S., & Shirsat, G. K. (2026). "Intelligent HVAC Control Systems Based on Machine Learning and Deep Learning Models." In G. Gupta, S. Gupta, T. Varshney, & T. Han (Eds.), Driving Affordable and Clean Energy Through AI and Intelligent Systems (pp. 107-136). IGI Global Scientific Publishing. (SCOPUS)