Blockchain is an underlying technology for securing many real-time applications and their data. The automobile is one such sector in which auto-manufacturers are looking forward to accepting the advantages of distributed ledger technology in autonomous vehicles or systems and improving their products, customer satisfaction, and other valuable experiences. This work aims to find the significance of blockchain technology in Autonomous Vehicles, including Autonomous Electric Vehicles (AEV), Autonomous Underwater Vehicles (AUV), Autonomous Guided Vehicles (AGV), Autonomous Aerial Vehicles (AAeV), and Autonomous Driving. In this work, a comparative analysis of blockchain-integrated autonomous vehicle systems is explored to identify the present scenario and futuristic challenges. In addition to blockchain technology, the uses and importance of sensors, architectures and infrastructure requirements, vehicle types, driving modes, vehicles target and tracking approaches, intelligent contracts, intelligent data handling, and industry-specific use cases are also explored. This study is based on the exploration of recent technologies and practices. As autonomous vehicles are expected to be the future of intelligent transportation, this paper surveys recent advances in autonomous vehicles and systems and how blockchain can help in improving user experiences and improving industry practices. Finally, limitations of work, future research directions, and challenges associated with different autonomous vehicles and systems are presented.

The microgrid concept is a promising approach for injecting clean, renewable, and reliable electricity into power systems. It can operate in both the grid-connected and the islanding mode. This paper addresses the two main challenges associated with the operation of a microgrid i.e. control and protection. A control strategy for inverter based distributed generation (DG) and an energy storage system (ESS) are proposed to control both the voltage and frequency during islanding operation. The protection scheme is proposed to protect the lines, DG and ESS. Further, the control scheme and the protection scheme are coordinated to avoid nuisance tripping of the DG, ESS and loads. The feasibility of the proposed method is verified by simulation and experimental results.

Intelligent Automation (IA) in automobiles combines robotic process automation and artificial intelligence, allowing digital transformation in autonomous vehicles. IA can completely replace humans with automation with better safety and intelligent movement of vehicles. This work surveys those recent methodologies and their comparative analysis, which use artificial intelligence, machine learning, and IoT in autonomous vehicles. With the shift from manual to automation, there is a need to understand risk mitigation technologies. Thus, this work surveys the safety standards and challenges associated with autonomous vehicles in context of object detection, cybersecurity, and V2X privacy. Additionally, the conceptual autonomous technology risks and benefits are listed to study the consideration of artificial intelligence as an essential factor in handling futuristic vehicles. Researchers and organizations are innovating efficient tools and frameworks for autonomous vehicles. In this survey, in-depth analysis of design techniques of intelligent tools and frameworks for AI and IoT-based autonomous vehicles was conducted. Furthermore, autonomous electric vehicle functionality is also covered with its applications. The real-life applications of autonomous truck, bus, car, shuttle, helicopter, rover, and underground vehicles in various countries and organizations are elaborated. Furthermore, the applications of autonomous vehicles in the supply chain management and manufacturing industry are included in this survey. The advancements in autonomous vehicles technology using machine learning, deep learning, reinforcement learning, statistical techniques, and IoT are presented with comparative analysis. The important future directions are offered in order to indicate areas of potential study that may be carried out in order to enhance autonomous cars in the future.

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This topic represents a technical review of Power Quality problems associated with the Renewable based wind energy system and the investigation of causes of poor power quality issues related with grid connected wind farm. Renewable Energy Source (RES) integrated at distribution level is termed as Distributed Generation(DG).The utility is concerned due to the high penetration level of wind energy in distribution systems, as it may pose a threat to network is terms of Power Quality(PQ) issues , voltage regulation and stability. Therefore the DG systems are required to comply with strict technical and regularity frameworks to ensure safe, reliable and efficient operation of overall network. Wind energy system integration issues and associated PQ problems are discussed.Integrating renewable into grids to any considerable degree can expose the system to issues that need attention lest the functionality of the grid be impaired. such issues can be voltage function, frequency deviation of power Quality.