Dr. Nisha Dagade | Renewable Energy | Best Researcher Award

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Dr. Nisha Dagade | Renewable Energy | Best Researcher Award

Dr. Nisha Dagade | Sinhgad Institutes | India

Dr. Nisha R. Dagade  is an accomplished Assistant Professor at Sinhgad Institutes, Pune, India, specializing in electrical power systems with a particular focus on Distributed Generation  and Reliability Analysis. Her research emphasizes the optimal integration of renewable DG sources into modern distribution networks, addressing both technical and economic challenges through heuristic and metaheuristic optimization approaches such as Ant Colony Optimization (ACO). Dr. Dagade’s scholarly contributions explore multi-objective frameworks that aim to reduce power losses, improve voltage profiles, and enhance the overall reliability and cost-effectiveness of distribution systems. Her notable work, “Ant colony optimization technique for integrating renewable DG in distribution system with techno-economic objectives,” published in Evolving Systems (2022), has gained significant academic recognition. With a strong research portfolio comprising 10 completed and ongoing projects, 7 Scopus-indexed journal publications, and one published book, and maintains an active research profile with 61 citations, an h-index of 5, and an i10-index of 2 , she continues to advance innovation in the domain of sustainable power systems. She has also collaborated with IIT Bombay on research initiatives that bridge academic insights with real-world applications. Her professional memberships in IAENG and I2OR reflect her active engagement in the global engineering research community. Dr. Dagade’s work embodies the integration of renewable energy technologies for efficient, reliable, and environmentally responsible power system development.

Profile: Google Scholar

Featured Publications

  • Godha, N. R., Bapat, V. N., & Korachagaon, I. (2022). Ant colony optimization technique for integrating renewable DG in distribution system with techno-economic objectives. Evolving Systems, 13(3), 485–498.

  • Godha, N. R., Deshmukh, S. R., & Dagade, R. V. (2011). Application of Monte Carlo simulation for reliability cost/worth analysis of distribution system. In 2011 International Conference on Power and Energy Systems (pp. 1–6).

  • Godha, N. R., Deshmukh, S. R., & Dagade, R. V. (2012). Time sequential Monte Carlo simulation for evaluation of reliability indices of power distribution system. In Proceedings of the 2012 IEEE Symposium on Computers and Informatics (ISCI 2012).

  • Godha, N. R., Bapat, V. N., & Korachagaon, I. (2019). Placement of distributed generation in distribution networks: A survey on different heuristic methods. In Techno-Societal 2018: Proceedings of the 2nd International Conference on Techno-Societal.

  • Dagade, N. R. G., Bapat, V. N., & Korachagaon, I. (2020). Improved ACO for planning and performance analysis of multiple distributed generations in distribution system for various load models. In 2020 Second International Sustainability and Resilience Conference.

 

 

Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

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Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

Dr. Aamir Ali | Quaid-e-Awam University of Engineering Science and Technology | Pakistan

Dr. Aamir Ali is currently serving as an Assistant Professor (BPS-19) in the Department of Electrical Engineering at Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan. He is a highly dedicated academic and researcher specializing in power system planning and optimization, distributed generation, and microgrid operations in both islanded and grid-connected modes. Dr. Ali earned his Ph.D. in Electrical Engineering from QUEST in 2020, where his doctoral research focused on single and multi-objective mathematical programming, direct search evolutionary algorithms, and optimization techniques for economic dispatch, optimal power flow, and unit commitment with renewable energy integration such as wind and solar PV systems. Prior to his doctorate, he completed his Master of Engineering in Power System Optimization from the same institution in 2015 and his Bachelor of Engineering in Electrical Power with an outstanding 85% score in 2012. His academic journey began with strong foundational performance at the intermediate and matriculation levels, both from the Board of Intermediate and Secondary Education, Hyderabad, Sindh, where he secured first division and A-1 grade distinctions. With 445 citations by 342 documents, 27 published works, and an h-index of 11, Dr. Aamir Ali has established himself as an active researcher in power systems optimization. He aspires to continue contributing to academia and research while leading a top-tier institution toward excellence in education and innovation.

Profile: Scopus | Orcid

Featured Publications

Akbar Talani, R., Kaloi, G. S., Ali, A., Abbas, G., Emara, A., & Touti, E. (2025, July 29). Fault analysis and performance improvement of grid-connected doubly fed induction generator through an enhanced crowbar protection scheme. PLOS One.

Ali, A., Akbar Talani, R., Kaloi, G. S., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P., & Touti, E. (2025, January 29). Dynamic performance analysis and fault ride-through enhancement by a modified fault current protection scheme of a grid-connected doubly fed induction generator. Machines, 13(2).

Ali, A., Ali, A., Liu, Z., Abbas, G., Touti, E., & Nureldeen, W. (2024). Dynamic multi-objective optimization of grid-connected distributed resources along with battery energy storage management via improved bidirectional coevolutionary algorithm. IEEE Access.

Ali, A., Shah, A., Keerio, M. U., Mugheri, N. H., Abbas, G., Touti, E., Hatatah, M., Yousef, A., & Bouzguenda, M. (2024). Multi-objective security constrained unit commitment via hybrid evolutionary algorithms. IEEE Access.

Abbas, G., Wu, Z., & Ali, A. (2024, December). A two-stage reactive power optimization method for distribution networks based on a hybrid model and data-driven approach. IET Renewable Power Generation.

Ali, A., Aslam, S., Mirsaeidi, S., Mugheri, N. H., Memon, R. H., Abbas, G., & Alnuman, H. (2024, December). Multi-objective multiperiod stable environmental economic power dispatch considering probabilistic wind and solar PV generation. IET Renewable Power Generation.