149 research outputs found

    TOWARDS OPTIMAL OPERATION AND CONTROL OF EMERGING ELECTRIC DISTRIBUTION NETWORKS

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    The growing integration of power-electronics converters enabled components causes low inertia in the evolving electric distribution networks, which also suffer from uncertainties due to renewable energy sources, electric demands, and anomalies caused by physical or cyber attacks, etc. These issues are addressed in this dissertation. First, a virtual synchronous generator (VSG) solution is provided for solar photovoltaics (PVs) to address the issues of low inertia and system uncertainties. Furthermore, for a campus AC microgrid, coordinated control of the PV-VSG and a combined heat and power (CHP) unit is proposed and validated. Second, for islanded AC microgrids composed of SGs and PVs, an improved three-layer predictive hierarchical power management framework is presented to provide economic operation and cyber-physical security while reducing uncertainties. This scheme providessuperior frequency regulation capability and maintains low system operating costs. Third, a decentralized strategy for coordinating adaptive controls of PVs and battery energy storage systems (BESSs) in islanded DC nanogrids is presented. Finally, for transient stability evaluation (TSE) of emerging electric distribution networks dominated by EV supercharging stations, a data-driven region of attraction (ROA) estimation approach is presented. The proposed data-driven method is more computationally efficient than traditional model-based methods, and it also allows for real-time ROA estimation for emerging electric distribution networks with complex dynamics

    Rising stars in energy research: 2022

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    Recognising the future leaders of Energy Research is fundamental to safeguarding tomorrow's driving force in innovation. This collection will showcase the high-quality work of internationally recognized researchers in the early stages of their careers. We aim to highlight research by leading scientists of the future across the entire breadth of Energy Research, and present advances in theory, experiment and methodology with applications to compelling problems

    Applications

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    Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

    A comprehensive review of electric vehicle charging stations with solar photovoltaic system considering market, technical requirements, network implications, and future challenges

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    Electric cars (EVs) are getting more and more popular across the globe. While comparing traditional utility grid-based EV charging, photovoltaic (PV) powered EV charging may significantly lessen carbon footprints. However, there are not enough charging stations, which limits the global adoption of EVs. More public places are adding EV charging stations as EV use increases. However, using the current utility grid, which is powered by the fossil fuel basing generating system, to charge EVs has an impact on the distribution system and could not be ecologically beneficial. The current electric vehicle (EV) market, technical requirements including recent studies on various topologies of electric vehicle/photovoltaic systems, charging infrastructure as well as control strategies for Power management of electric vehicle/photovoltaic system., and grid implications including electric vehicle and Plug-in hybrid electric vehicles charging systems, are all examined in depth in this paper. The report gives overview of present EV situation as well as a thorough analysis of significant global EV charging and grid connectivity standards. Finally, the challenges and suggestions for future expansion of the infrastructure of EV charging, grid integration, are evaluated and summarized. It has been determined that PV-grid charging has the ability to create a profit. However, due to the limited capacity of the PV as well as the batteries, the Power system may not be cost effective. Furthermore, since PV is intermittent, it is probable that it will not be able to generate enough electricity to meet consumer demand

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    Fundamentals

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    Volume 1 establishes the foundations of this new field. It goes through all the steps from data collection, their summary and clustering, to different aspects of resource-aware learning, i.e., hardware, memory, energy, and communication awareness. Machine learning methods are inspected with respect to resource requirements and how to enhance scalability on diverse computing architectures ranging from embedded systems to large computing clusters

    Stand-alone Micro Grid based on Artificially Intelligent Neural Network (AI-NN)

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    INTRODUCTION: Hybrid stand-alone Small Wind Solar Energy System offers a feasible solution in remote areas where grid connectivity is either financially or physically unavailable. A small wind turbine (SWT) and a solar photovoltaic system are part of the hybrid energy system, which is effectively employed to meet the energy needs of rural household loads. OBJECTIVE: This research suggests an effective analysis of wind solar hybrid system controllers taking energy demands into account. The controller should be designed in such a way as to intelligently monitor the availability of wind energy and solar energy and store the energy without spilling it out. METHODS: In order to cope with the challenging factors involved in designing the controller, intelligent power tracking with an artificially intelligent neural network (AI-NN) is designed. Added to that, the whole process has been designed and analysed with the MATLAB SIMULINK tool. RESUSTS: The results of the simulation, infer that AI-NN achieved the regression value of   0.99 when compared with the Perturb & Observe algorithm (P&O), and the Fuzzy Logic Control (FLC) algorithm, and has a higher tracking speed. Also, the AI-NN attained 2.62kW whereas the P&O has attained 2.52kW and Fuzzy logic has attained 2.43W of power which is 3.89% higher than P&O algorithm and 7.52% higher than fuzzy MPPT algorithm. CONCLUSION: The designed controller module enhances the system by artificially intelligent algorithm. The AI-NN attains the better power performance with lesser tracking time and higher efficiency. Thus, it is evident that AI-NN MPPT suits well for the hybrid system

    Rising Stars in Energy Research: 2022

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    Advanced Modeling and Research in Hybrid Microgrid Control and Optimization

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    This book presents the latest solutions in fuel cell (FC) and renewable energy implementation in mobile and stationary applications. The implementation of advanced energy management and optimization strategies are detailed for fuel cell and renewable microgrids, and for the multi-FC stack architecture of FC/electric vehicles to enhance the reliability of these systems and to reduce the costs related to energy production and maintenance. Cyber-security methods based on blockchain technology to increase the resilience of FC renewable hybrid microgrids are also presented. Therefore, this book is for all readers interested in these challenging directions of research

    Power Electronics Applications in Renewable Energy Systems

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    The renewable generation system is currently experiencing rapid growth in various power grids. The stability and dynamic response issues of power grids are receiving attention due to the increase in power electronics-based renewable energy. The main focus of this Special Issue is to provide solutions for power system planning and operation. Power electronics-based devices can offer new ancillary services to several industrial sectors. In order to fully include the capability of power conversion systems in the network integration of renewable generators, several studies should be carried out, including detailed studies of switching circuits, and comprehensive operating strategies for numerous devices, consisting of large-scale renewable generation clusters
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