Faculty

Power System Optimization using AI Techniques

Dr. Ankur Maheshwari received the B.Tech. degree in Electrical Engineering from Gautam Buddha Technical University, Lucknow, Uttar Pradesh, India, in 2010, and the M.Tech. degree in Power Systems from the National Institute of Technology (NIT) Hamirpur, Himachal Pradesh, India, in 2019. He completed his Ph.D. in Electrical Engineering from NIT Hamirpur, specializing in the "Multi-Objective Optimal Operation of Deregulated Power Sector Incorporating Renewable Energy Sources," in 2024. Currently, he is working as an Assistant Professor in the Department of Electrical and Electronics Engineering at KIET Group of Institutions, Ghaziabad, Uttar Pradesh. His research interests include optimal power flow solutions, integration of stochastic renewable energy sources, optimization techniques, and microgrid energy management. Dr. Maheshwari has numerous research publications in high-impact journals and reputed national and international conferences. He has also been published/granted multiple patents. He is a recipient of the prestigious MoE Fellowship for his doctoral and master’s studies and has qualified GATE multiple times in Electrical Engineering.

• Dr. Ankur Maheshwari (2023). A comprehensive review on stochastic optimal power flow problems and solution methodologies. IETE Technical Review. ISSN:0974-5971
• Dr. Ankur Maheshwari (2023). Flow direction algorithm-based optimal power flow analysis in the presence of stochastic renewable energy sources. Electric Power Systems Research. ISSN:0378-7796 (Print), 1873-2046 (Online)
• Dr. Ankur Maheshwari (2023). Social welfare maximization in deregulated power market incorporating wind power plants using metaheuristic algorithm. Wind Engineering. ISSN:0309-524X
• Dr. Ankur Maheshwari (2022). Solution approach for optimal power flow considering wind turbine and environmental emissions. Wind Engineering. ISSN:0309-524X
• Dr. Ankur Maheshwari (2022). Investigation of optimal power flow solution techniques considering stochastic renewable energy sources: Review and analysis. Wind Engineering. ISSN:0309-524X

• Dr. Ankur Maheshwari. Day-ahead power flow optimization with stochastic wind and solar power plants. IEEE ICPEA 2024, Penang Island, Malaysia. ISBN:-
• Dr. Ankur Maheshwari. Power systems resilience enhancement through renewable energy integration: Insights and future directions. IEEE ICPEA 2024, Penang Island, Malaysia. ISBN:-
• Dr. Ankur Maheshwari. Optimal power flow solution based on multi-verse optimizer algorithm incorporating renewable energy sources. IEEE ICPEA 2024, Penang Island, Malaysia. ISBN:-
• Dr. Ankur Maheshwari. Dung beetle optimizer algorithm based OPF solution considering renewable energy sources. IEEE IC2E3 2023, Srinagar Garhwal, India. ISBN:10.1109/IC2E357697.2023.10262592
• Dr. Ankur Maheshwari. Ant lion optimization based OPF solution incorporating wind turbines and carbon emissions. IEEE i-PACT 2021, Kuala Lumpur, Malaysia. ISBN:10.1109/i-PACT52855.2021.9696806
• Dr. Ankur Maheshwari. Game theory based EV charge scheduling: A comprehensive review. IEEE i-PACT 2021, Kuala Lumpur, Malaysia. ISBN:10.1109/i-PACT52855.2021.9696445
• Dr. Ankur Maheshwari. Effective control strategy in microgrid. ICSC 2019, Tehri, India (Springer). ISBN:978-981-15-0633-8_94

• Ankur Maheshwari (1905-07-16). A Comprehensive Review on Metaheuristic Optimization Methods for Efficient Power System Operation. Springer. ISBN:978-981-97-5717-6
• Ankur Maheshwari (1905-07-16). Artificial Intelligence and Machine Learning Applications for Sustainable Development. Taylor & Francis. ISBN:9781032742144
• Ankur Maheshwari (1905-07-14). Modeling and Analysis of Autonomous Hybrid Green Microgrid System for the Electrification of Rural Area. Wiley. ISBN:9781119804017
• Ankur Maheshwari (1905-07-12). Optimal Power Flow and its Vindication in Deregulated Power Sector. Springer. ISBN:978-981-16-2354-7
• Ankur Maheshwari (1905-07-12). Techno-Economic Assessments of Green Hybrid Microgrid. Springer. ISBN:978-981-15-7994-3
• Ankur Maheshwari (1905-07-12). Technoeconomic Feasibility and Sensitivity Analysis of Off-Grid Hybrid Energy System. Springer. ISBN:978-981-16-2354-7