Conducted Under IEEE MTT-S & IEEE-AESS Chapter SBC11474
Joint Delhi Chapter IEEE PES-IAS Delhi Section · PE31/IA34
ABV-Indian Institute of Information Technology and Management, Gwalior

Powering the Future: Innovations in Modern Power Systems and How to Find It

Join an insightful webinar by Dr. Maanvi Bhatnagar on power systems, exploring modern grid technologies, renewable integration, and real-world challenges. Gain practical knowledge, industry insights, and future trends to enhance your understanding and career in electrical engineering and energy systems.

April 25, 2026
06:30 p.m.(IST)
00 Days
00 Hours
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About This Webinar

This webinar introduces power system fundamentals, covering generation, transmission, and distribution, while highlighting modern trends, smart grids, renewable integration, and practical challenges shaping the future of electrical energy systems.

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Power System Fundamentals

Explore the core principles of electrical power system, including generation, transmission,and distribution.Understand how eneergyflow from powe plants to consumer while maintaining efficiency and reliability.

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Power System Analysis Methodology

Learn about advanced techinique used to analyze power system,including load flow studies,fault analysis,and stability assessment.Bridge theoretical concepts with real-world engineering application.

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Practical Applications

Discover how power system are applied in modern infrastructure,inculding smart grids,renewable energy integration,and industial power management Gain insights into solving real-world electrical challenges.

Key Publications & Research

Maanvi Bhatnagar’s research focuses on modern power system engineering, integrating advanced analytical methods with emerging technologies. Her work contributes to improving efficiency, reliability, and sustainability in electrical power networks.

Bhatnagar, Maanvi, Anamika Yadav, and Aleena Swetapadma. "A Fault Detection and Faulty Section Identification Scheme for Micro-Grids."

In 2022 Second International Conference on Power, Control and Computing Technologies (ICPC2T), pp. 1-6. IEEE, 2022.

Bhatnagar, Maanvi, Anamika Yadav, Aleena Swetapadma, and Almoataz Y. Abdelaziz. "LSTM-based low-impedance fault and high-impedance fault detection and classification."

Electrical Engineering 106, no. 5 (2024): 6589-6613.

Bhatnagar, Maanvi, Anamika Yadav, and Aleena Swetapadma. "Enhancing the resiliency of transmission lines using extreme gradient boosting against faults."

Electric Power Systems Research 207 (2022): 107850

Bhatnagar, Maanvi, Anamika Yadav, and Aleena Swetapadma. "Fuzzy based relaying scheme for high impedance faults in DG integrated distribution system

Electric Power Systems Research 202 (2022): 107602

Gupta, Gauri Shanker, Maanvi Bhatnagar, Shikhar Kumar, and Rakesh Kumar Sinha. "A comparative study of application of different non-conventional filters on electroencephalogram."

Biomed. Res 31 (2020): 1-9

Why This Research Matters

Power system research ensures reliable, efficient energy supply, supports renewable integration, improves grid stability, enables smart technologies, reduces losses, and drives sustainable development, economic growth, and future electrification advancements.

Who Should Attend

Electrical engineering students,diploma and polytechnic students,industry professionals,fresh graduates and job seekers,researchers and innovators,technicians and field engineers

Learning Outcomes

Participants will understand power system fundamentals,analyze modern power system components,explore smart grid technologies,interpret power quality issues,learn about renewable energy integration

Featured Speaker

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Dr.Maanvi Bhatnagar

AI/ML Engineer ,SOLIZE PARTNERS INDIA PVT. LTD

PhD from NIT-Raipur in Electrical Engineering and Artificial Intelligence Specialization

Proficient skill in Medical health data analytics,

Research and Literature Review, Project Acquisitiion

B.Tech Silver Medallist

Dr. Bhatnagar completed her Ph.D. in Electrical Engineering from NIT Raipur, specializing in Power Systems and Artificial Intelligence, where her research focused on developing AI-based protection schemes for power transmission and distribution systems with renewable energy integration. Her work combines advanced machine learning techniques—including deep learning models such as CNNs, LSTMs, autoencoders, and gradient boosting methods—to enhance reliability and fault detection in modern power grids.

Professionally, she is currently working as an AI/ML Engineer in Solize technologies, Bengaluru, where she develops LLM-powered chatbots and generative AI applications, building end-to-end solutions using technologies such as LangChain, RAG pipelines, and prompt engineering. Prior to this, she worked as a Data Scientist at NDS Infoserv in Mumbai, applying machine learning and large language models to analyze healthcare data and predict patient outcomes.

Dr. Bhatnagar’s expertise spans power system protection, time-series energy forecasting, machine learning, deep learning, and data analytics, with hands-on experience in tools such as Python, MATLAB/Simulink, TensorFlow, Power BI, and Tableau. She has also contributed to interdisciplinary research, including machine learning applications for malaria detection in medical imaging.

With a strong academic foundation and industry experience in AI, energy systems, and data science, Dr. Bhatnagar brings a unique interdisciplinary perspective to today’s topic.

Research Analysis
Forecasting
Good Presentation Skills
8+
Years Experience
15+
Publications
NDS Infoserv
Data Scientist

Academic Profiles

ORCID: 0000-0002-7385-4512

Powering the Future: Innovations in Modern Power Systems

An advanced exploration of modern grid resilience, integrating transient signal processing, machine learning paradigms, and predictive analytics for robust transmission network protection.

1. The Architecture of Modern Interconnected Grids

• Complexities of wide-area transmission and the shift toward inverter-based resources
• Stochastic nature of modern energy demand and distributed generation
• Maintaining stability in highly interconnected and geographically widespread networks

2. Critical Vulnerabilities and Fault Dynamics

• Analyzing irregular and arbitrary faults in transmission infrastructure
• The distinct challenges of High Impedance Faults (HIF) and evolving faults
• Implications of delayed fault detection on system stability and cascading blackouts
• The economic and structural impact of outage times during peak load hours

3. Limitations of Conventional Protection Schemes

• Critique of traditional signal processing methods (DFT, DWT, and standard Fourier analysis)
• Shortcomings of early mathematical models in adapting to varying fault inception angles
• The necessity for sub-cycle detection to abate outage times and enable rapid re-establishment

4. Advanced Feature Extraction Techniques

• Time-frequency analysis of voltage and current transients during system disturbances
• Application of the Teager Kaiser Energy Operator (TKEO) for high-resolution transient detection
• Optimizing dynamic feature vectors for high-speed algorithmic processing

5. Machine Learning Paradigms in Grid Protection

Classification & Detection:
• Evolution from traditional ANN and Support Vector Machines (SVM) to modern ensemble methods
• Deploying Extreme Gradient Boosting (XGBoost) for highly precise fault classification

Location Estimation (Regression):
• Utilizing XGBoost regression modules for accurate fault location estimation
• Overcoming the precision limits of k-Nearest Neighbor (k-NN) and ANFIS models

6. Comparative Analysis of Predictive Models

• Benchmarking proposed TKEO-XGBoost frameworks against existing deterministic and heuristic models
• Evaluating algorithmic robustness under varying noise levels and transient conditions
• Algorithmic implementation strategies for real-time service restoration teams

7. Future Trajectories in AI-Driven Power Systems

• Bridging the gap between theoretical ML models and utility-scale deployment
• Developing self-healing grids and adaptive, autonomous protection schemes
• Identifying open research questions in grid digitalization and data-driven infrastructure

Frequently Asked Questions

What are the prerequisites for this webinar?
Participants should have a basic foundation in power system analysis and transmission protection schemes. Familiarity with digital signal processing and foundational machine learning concepts will be highly beneficial.
How does this webinar address academic research needs?
This webinar focuses on current research challenges in modern grid resilience, presents advanced fault detection algorithms (such as TKEO and XGBoost), and explores predictive modeling for transmission networks—directly addressing the rigorous needs of PhD candidates and academic researchers.
Will I receive supporting academic materials?
Registered participants will receive comprehensive reference materials including the presentation slides, key IEEE papers for academic use.
Can this content be applied to academic research projects?
Absolutely. The transient signal processing techniques (like TKEO) and machine learning paradigms (like XGBoost) presented are directly applicable to PhD-level research in fault detection, modern grid resilience, and AI-driven power systems.
Is this webinar suitable for PhD researchers?
Yes, the content is specifically designed to be valuable for PhD candidates and academic researchers. It addresses current research challenges and presents cutting-edge solutions published in top IEEE journals.
Will recordings be available after the webinar?
All registered participants will receive access to the webinar recording and presentation materials for 30 days after the event.

Register for Free

Join us for an engaging exploration of modern power systems and discover the technical and practical insights behind how electricity is generated, transmitted, and delivered, empowering you to understand the backbone of energy that drives today’s world.

    Previous Webinar Highlights

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    Institutes

    12+

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    Countries

    20+

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    Time

    1h 26m

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    Rating

    4.8/5

    Global Participants

    12+
    Institutes
    20+
    Countries

    IIT Roorkee

    IIT Hyderabad

    NIT Raipur

    Walailak University

    United International University

    University of Bucharest

    Tshwane University of Technology

    Instituto Superior Técnico (Portugal)

    ENSAI – University of Ngaoundere (Cameroon)

    University of Cantabria (Spain)

    UTS (Australia)

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    Supporting UN Sustainable Development Goals

    This systems webinars support SDGs by promoting clean energy adoption, improving efficiency, enabling smart infrastructure, reducing emissions, and educating professionals to build sustainable, reliable, and accessible energy systems worldwide.

    Primary Focus

    SDG 4: Quality Education

    Key Target:
    Target 4.7:Ensure inclusive, equitable quality education, promote lifelong learning opportunities, improve literacy and skills, eliminate gender disparities, enhance teacher training, and provide access to affordable, effective education for all learners.

    Provides technical knowledge and skill development for students and professionals in the energy sector.

    SDG 3: Develop Reliable Infrastructure

    Key Target:
    Target 3.4:Develop reliable, sustainable, and resilient infrastructure to support economic growth, ensure efficient resource use, improve connectivity, enhance public services, and withstand environmental challenges while promoting inclusive and long-term development.

    Build quality, sustainable, and resilient infrastructure to support economic growth and human well-being.

    SDG 9: Industry, Innovation and Infrastructure

    Key Target:
    Target 9.5:Promote resilient infrastructure, sustainable industrialization, innovation, clean technologies, improved resource efficiency, expanded ICT access, and support for small-scale industries to drive inclusive economic growth.

    Encourages development of modern, resilient power infrastructure and adoption of smart grid technologies.

    How This Webinar Contributes to Global Goals

    Promotes Clean Energy Adoption

    Encourages the use of renewable energy sources, supporting global sustainability and reducing carbon emissions.

    Enhances Energy Efficiency

    Highlights modern technologies that reduce power losses and improve overall system performance.

    Supports Reliable Power Access

    Focuses on smart grids and innovations to ensure stable, affordable electricity for growing global needs.