Author Profile
ORCID
⚡ Early academic pursuits
Manoranjan Sahoo’s journey in electrical engineering began with a bachelor’s degree from g.i.t.a., bhubaneswar, where he specialized in electrical engineering, graduating with a cgpa of 7.3 in 2016. motivated by a deep passion for power systems, he pursued an m.tech in power system engineering at n.i.t. silchar, where he achieved a commendable cgpa of 8.3 in 2020. his academic dedication culminated in his doctoral studies at n.i.t. rourkela, where he submitted his thesis with an impressive cgpa of 8.6, demonstrating his expertise in power systems and machine learning applications.
🔧 Professional endeavors
Manoranjan’s professional trajectory includes significant teaching and research contributions. he has taught foundational and advanced courses such as basic electrical lab, electrical machine lab, and power system simulation lab, empowering students with practical and theoretical knowledge. his hands-on expertise with advanced tools like matlab/simulink, python, and real-time simulation platforms such as opal-rt reflects his technical proficiency. his roles have consistently bridged academia and applied research, ensuring impactful learning environments for aspiring engineers.
🌐 Contributions and research focus
His research spans critical areas in power systems, focusing on grid integration, deregulated power markets, and dynamic stability studies. his ph.d. work centers on developing machine-learning-based methods for detecting low-frequency oscillatory modes in power systems using phasor measurement units (pmus). he has also Electrical Power system delved into the challenges of dealing with bad data in pmu signals, implementing both supervised and unsupervised learning techniques. his m.tech project explored optimal bidding strategies in deregulated power markets, while his b.tech work focused on photovoltaic array integration, showcasing a blend of theoretical rigor and practical innovation.
🏅 Accolades and recognition
Manoranjan’s academic journey is marked by his consistent achievements, including a strong cgpa record in his higher education pursuits. his contributions to the Electrical Power system field of power systems and machine learning are highly regarded, reflecting his commitment to excellence in research and innovation. the successful submission of his doctoral thesis stands as a testament to his expertise and diligence in addressing complex problems in electrical engineering.
🌍 Impact and influence
Through his research, Manoranjan has contributed to enhancing the reliability and efficiency of modern power systems. his innovative approaches to tackling Electrical Power system challenges such as low-frequency oscillations in power systems have the potential to influence wide-area monitoring systems worldwide. his commitment to teaching ensures the dissemination of advanced knowledge and practices to the next generation of engineers, amplifying his impact on the field.
🚀 Legacy and future contributions
Manoranjan’s work in power systems and his integration of machine learning into electrical engineering research pave the way for innovative solutions in energy management and stability. his technical expertise and academic contributions position him as a thought leader in modern power systems, ensuring a legacy of impactful research and practical applications in a rapidly evolving energy landscape. with his dedication and skillset, he is poised to make significant advancements in the field, contributing to the global shift towards smarter and more sustainable power systems.
Notable Publications
- Title: A Partitioning Around Medoids (PAM) Based Sequential Clustering Approach for Model Order Estimation of Low-Frequency Oscillations in Wide Area Measurement System
Authors: Manoranjan Sahoo, Shekha Rai
Journal: Sādhanā
- Title: Model Order Estimation for Low-Frequency Oscillations in Power Systems by an Advanced K-Mean Clustering Approach
Authors: Manoranjan Sahoo, Jangam Sandeep, Shekha Rai
Journal: Electric Power Systems Research