http://dspace.dtu.ac.in:8080/jspui/handle/123456789/76 2026-04-28T03:58:00Z 2026-04-28T03:58:00Z DEVI, OINAM LOTIKA Singh, Alka (SUPERVISOR) http://dspace.dtu.ac.in:8080/jspui/handle/repository/22689 2026-03-12T05:09:09Z 2026-02-01T00:00:00Z

Title: DESIGN AND ANALYSIS OF SYNCHRONIZATION TECHNIQUES FOR CONTROL OF POWER ELECTRONIC CONVERTERS Authors: DEVI, OINAM LOTIKA; Singh, Alka (SUPERVISOR) Abstract: The increasing integration of renewable energy sources into electrical power systems has necessitated advanced synchronization techniques for power electronics converters. This thesis investigates synchronization methods, with particular emphasis on Phase-Locked Loop (PLL) technologies, to address challenges in grid-integrated systems under various disturbances. The primary objective is to develop and validate enhanced synchronization algorithms that overcome limitations of conventional PLLs in applications including photovoltaic systems, doubly fed induction generator (DFIG) wind energy converters, and electric vehicles. A comprehensive methodology combining mathematical modelling, stability analysis, extensive MATLAB Simulink simulations, and experimental validation using OPAL- RT real-time simulator was employed. Multiple PLL architectures were evaluated under abnormal grid conditions including voltage sags/swells, frequency jumps, DC offsets, and harmonic distortions. The research examined single-phase and three-phase PLLs, including Synchronous Reference Frame (SRF), Second-Order Generalized Integrator (SOGI), Least Mean Square (LMS), Least Mean Fourth (LMF), Modified Synchronous Reference Frame (MSRF), and fractional-order PLLs. Key findings demonstrate that the LMF PLL outperforms SRF PLL under phase shift and frequency change disturbances, while Type III Enhanced PLL exhibits superior frequency response with polluted grid voltage and DC offset. The proposed fractional- order FO-LPFO-PI MSRF-PLL with optimized parameters shows enhanced stability during grid abnormalities. Additionally, the novel H-LMS-SOGI PLL architecture provides exceptional dynamic responses, surpassing conventional structures under all adverse grid conditions tested. Experimental validation of DFIG systems with LMF- PLL confirms satisfactory performance under variable wind speeds and grid disturbances. This research significantly contributes to grid stability and renewable energy integration by providing validated solutions for maintaining reliable power system operation with high penetration of distributed energy resources. The dual validation approach ensures practical applicability, offering a comprehensive framework for xxi designing robust power electronics-based systems capable of handling complex grid disturbances in modern power networks.

2026-02-01T00:00:00Z KUMAR, CHANDAN Chittora, rakash (SUPERVISOR) http://dspace.dtu.ac.in:8080/jspui/handle/repository/22688 2026-03-12T05:08:58Z 2025-06-01T00:00:00Z

Title: DESIGN AND DEVELOPMENT OF SECURITY FRAMEWORK FOR SMART GRID INFRASTRUCTURE Authors: KUMAR, CHANDAN; Chittora, rakash (SUPERVISOR) Abstract: The smart grid is considered the future of electricity networks because it brings in intelligence, flexibility, and reliability to the power system. Unlike traditional power grids, smart grids use advanced information and communication technologies to enable two-way communication between utility companies and consumers. This makes it possible to integrate renewable energy sources, improve energy efficiency, and ensure better management of resources. However, as the smart grid becomes more connected and dependent on digital systems, it faces serious challenges related to cybersecurity. The openness and interconnectedness that make it efficient also make it vulnerable to different types of cyberattacks, data breaches, and unautho- rized access. If these issues are not addressed properly, they can affect the privacy of consumers, disrupt services, or even cause large-scale blackouts. This thesis presents an advanced, multi-layered framework for secure smart grid in- frastructure, integrating the strengths of deep learning, blockchain technology, and immersive collaborative platforms. Addressing the critical gaps in cybersecurity, privacy, and operational scalability, the research rethinks smart grid protection by unifying decentralized trust, intelligent anomaly detection, and efficient large-scale data management. The first major contribution is a robust secure data sharing architecture combin- ing a hybrid deep learning intrusion detection system using Variational Autoen- iv v coder (VAE) and Attention-based Bidirectional LSTM (ABiLSTM) with blockchain- backed audit trails and off-chain Inter Planetary File System (IPFS) storage. Ex- perimental validation on benchmark ToN-IoT and BoT-IoT datasets demonstrates significant performance improvements. The proposed system achieves near-perfect detection in percentage, accuracy (99.99), precision (98.99), recall (99.9), and F1 score (99.91), outperforming classical approaches (Naive Bayes, Decision Tree, Ran- dom Forest) by wide margins. Importantly, the hybrid on/off-chain design substan- tially reduces blockchain overhead, enabling real-time scalability lacking in earlier ledger-centric models. The research extends to IoT-enabled Electric Vehicles (EVs), devising a secure and privacy-preserving framework that leverages Stacked Sparse Denoising Autoencoders (SSDAE) and Attention-based LSTM for anomaly detection and data anonymiza- tion. Coupled with smart contract-driven authentication, this approach achieves highly effective multi-class threat detection and privacy protection, with detection and recall rates surpassing leading prior Long Short Term Memory (LSTM) and Artificial Neural Network (ANN) models while ensuring low-latency communication essential for mobile EV-grid integration. A novel facet of this thesis is the application of metaverse and digital twin technolo- gies, which enable unprecedented real-time, immersive collaboration and situational awareness for grid operators. Through federated and collaborative intrusion detec- tion, multi-operator security, and grid incident response now occur with reduced detection latency and enhanced visibility, an improvement over the isolated or man- ual supervision that dominated earlier solutions. In summary, this thesis offers (1) higher detection accuracy and reliability through advanced deep learning architectures; (2) integrated, scalable security and privacy vi solutions across grid and IoT-vehicle domains; (3) immersive, collaborative security and operational platforms; and (4) efficient, tamper-evident storage and auditing suitable for next-generation smart grid requirements. Collectively, these contribu- tions pave the way for intelligent, secure, and sustainable energy systems addressing technical, economic, and social imperatives in real-world smart grid deployments.

2025-06-01T00:00:00Z RAO, SHUBHAM SINGH http://dspace.dtu.ac.in:8080/jspui/handle/repository/22650 2026-02-10T04:47:20Z 2020-07-01T00:00:00Z

Title: ANALYSIS AND DESIGN OF A ZERO VOLTAGE TRANSITION DC-DC BOOST CONVERTER FOR PHOTOVOLTAIC (PV) ENERGY SYSTEM Authors: RAO, SHUBHAM SINGH Abstract: India despite being world’s third largest power and energy producer and consumer is considered to have and extremely undependable and fickle electrical infrastructure. It is believed that around 27% of the energy that is generated is either stolen or lost in transmission. When the 2012 grid failure happened, nothing happened to the villages that were not connected to the grid. Some instances include, Meerwada located in Madhya Pradesh because it has a 14KW solar power station.The reason why photovoltaic(PV) energy systems are gaining popularity is because of the systems that are being created and updated to obscure as much energy as it can from the sun that too in the most efficient way and contribute in humungous capacity without really affecting their performance. This thesis talks about the study of boost convertor operating all the switching devices under Zero Voltage Transmission and also a model convertor that can supply a load of 250W that is designed and is also used in a PV energy system. In this methodology, a part of the circuit resonates for a small portion of the switching cycle of the convertor, called as the auxiliary circuit that improves and betters the soft transition or change from ON to OFF state and vice versa, hence improving the convertor efficiency by reducing and lessening the dominating portion in losses i.e. the losses that happen because of difficult transition of the switches. Because of the lesser amount of losses during switching transitions, the heating effect of MOSFETs is also reduced and they have a more durable life. The relative and qualified study between this new methodology and traditional hard switching convertor is studied and analyzed with respect to improvement in efficiency and reduction in switching losses.

2020-07-01T00:00:00Z VERMA, ANEEH http://dspace.dtu.ac.in:8080/jspui/handle/repository/22647 2026-02-10T04:47:08Z 2025-12-01T00:00:00Z

Title: INVESTIGATION AND CONTROL ASPECTS OF SOME DC-DC CONVERTERS WITH EV INTEGRATION Authors: VERMA, ANEEH Abstract: As more and more people around the world use electric cars (EVs) as a more environmentally friendly way to get around, it becomes harder to keep the power grid stable. As more people start using electric vehicles (EVs), large-scale integration might cause problems with voltage drops, phase imbalances, and overloading in the grid infrastructure. In addition, changes in grid voltage and current might make EV charging operations less efficient and less reliable. This thesis suggests an intelligent bidirectional EV charging system that will help solve these problems while making sure that energy flows smoothly between the grid and EV batteries. The suggested system has two main converters: one that converts AC to DC on the grid side and one that converts DC to AC on the EV battery side. A second-order generalized integrator (SOGI)-based technique controls the AC-DC converter. This separates the basic current components from the harmonic distortions, making sure that the power flows in a sinusoidal way. The DC-DC converter uses a constant current charging algorithm to effectively control the battery's voltage and current while it is charging and discharging. These converters work together to create a strong way to transfer energy. They can switch between grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes while keeping the system stable even when the grid circumstances change. A lot of simulations with different situations, such as harmonics injection, load changes, and short-term disruptions, to see how well the system works. The results show that the SOGI-based control works well to stop distortions caused by the grid from spreading into charging and discharging currents. The technology also does a great job of regulating voltage, keeping the DC link constant even when the grid supply changes. The bidirectional DC-DC converter smoothly switches between buck and boost modes, making sure that power flows in both ways without harming the battery. The results of this study show that an enhanced EV charging architecture is possible and will improve the stability of the grid while also improving the performance of EV batteries.

2025-12-01T00:00:00Z