A review of networked microgrid protection: Architectures, challenges, solutions, and future trends

The design and selection of advanced protection schemes have become essential for the reliable and secure operation of networked microgrids. Various protection schemes that allow the correct operation of microgrids have been proposed for individual systems in different topologies and connections. Nevertheless, the protection schemes for networked microgrids are still in development, and further research is required to design and operate advanced protection in interconnected systems. The interconnection of these microgrids in different nodes with various interconnection technologies increases the fault occurrence and complicates the protection operation. This paper aims to point out the challenges in developing protection for networked microgrids, potential solutions, and research areas that need to be addressed for their development. First, this article presents a systematic analysis of the different microgrid clusters proposed since 2016, including several architectures of networked microgrids, operation modes, components, and utilization of renewable sources, which have not been widely explored in previous review papers. Second, the paper presents a discussion on the protection systems currently available for microgrid clusters, current challenges, and solutions that have been proposed for these systems. Finally, it discusses the trend of protection schemes in networked microgrids and presents some conclusions related to implementation

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Modelling methodologies for railway asset management

Management of railway assets incurs significant expenditure. Railway asset management modelling can predict the cost and efficacy of an asset management plan, and thus support the asset management planning process. Modelling frameworks can be used to facilitate the development of large, multi-asset, whole life cycle models which can be used to represent large sections of rail track and associated assets. This is achieved with libraries of models and tools with a high level of inter-compatibility. This research set out to support the development of modelling frameworks for railway asset management. It sought to determine the state of the art of railway asset management modelling in order to find which assets require further modelling development before they can be suitably represented in a framework’s model library. It also sought to determine the most accurate and suitable modelling methodology to base the framework upon. These aims were met by first carrying out a literature review to determine the state of the art of asset management modelling for major railway asset types. This review found Petri net models solved via Monte Carlo methods to be the most suitable modelling methodology for asset management. The level crossing asset class was chosen for the development of several models to explore the different types of Petri net model, concentrating on the computational resources required. This asset class was chosen as no asset management model was found in literature, and the diversity of the asset interactions. Literature review found several asset classes in need of further development, and some where asset management modelling may not be possible without other advances. The level crossing Petri net models developed demonstrated that computational requirements differ between the various types of Petri net. Stochastic Petri nets were found to simulate quickly, but had a high memory requirement. Coloured Petri nets were found to have the opposite requirements. A novel Petri net type, the Simple Coloured Petri net was developed to create a balance in computational cost. It was further found that complex processes such as scheduling and resource allocation can only be carried out using Coloured Petri nets due to their enhanced feature set. This work has found that further research on modelling specific asset classes is required to enable the development of a complete asset modelling library for use in a framework. If large models are to be developed, it is recommended that the Simple Coloured Petri net be used to balance computational requirements. Any models requiring complex functions should be developed using the Coloured Petri net methodology

Large space structures and systems in the space station era: A bibliography with indexes (supplement 03)

Bibliographies and abstracts are listed for 1221 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1991 and June 30, 1991. Topics covered include large space structures and systems, space stations, extravehicular activity, thermal environments and control, tethering, spacecraft power supplies, structural concepts and control systems, electronics, advanced materials, propulsion, policies and international cooperation, vibration and dynamic controls, robotics and remote operations, data and communication systems, electric power generation, space commercialization, orbital transfer, and human factors engineering

Applied (Meta)-Heuristic in Intelligent Systems

Engineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristic algorithms have emerged as the prevailing methods. A generic metaheuristic framework guides the course of search trajectories beyond local optimality, thus overcoming the limitations of traditional computation methods. The application of modern metaheuristics ranges from unmanned aerial and ground surface vehicles, unmanned factories, resource-constrained production, and humanoids to green logistics, renewable energy, circular economy, agricultural technology, environmental protection, finance technology, and the entertainment industry. This Special Issue presents high-quality papers proposing modern metaheuristics in intelligent systems

IMPROVEMENT OF POWER QUALITY OF HYBRID GRID BY NON-LINEAR CONTROLLED DEVICE CONSIDERING TIME DELAYS AND CYBER-ATTACKS

Power Quality is defined as the ability of electrical grid to supply a clean and stable power supply. Steady-state disturbances such as harmonics, faults, voltage sags and swells, etc., deteriorate the power quality of the grid. To ensure constant voltage and frequency to consumers, power quality should be improved and maintained at a desired level. Although several methods are available to improve the power quality in traditional power grids, significant challenges exist in modern power grids, such as non-linearity, time delay and cyber-attacks issues, which need to be considered and solved. This dissertation proposes novel control methods to address the mentioned challenges and thus to improve the power quality of modern hybrid grids.In hybrid grids, the first issue is faults occurring at different points in the system. To overcome this issue, this dissertation proposes non-linear controlled methods like the Fuzzy Logic controlled Thyristor Switched Capacitor (TSC), Adaptive Neuro Fuzzy Inference System (ANFIS) controlled TSC, and Static Non-Linear controlled TSC. The next issue is the time delay introduced in the network due to its complexities and various computations required. This dissertation proposes two new methods such as the Fuzzy Logic Controller and Modified Predictor to minimize adverse effects of time delays on the power quality enhancement. The last and major issue is the cyber-security aspect of the hybrid grid. This research analyzes the effects of cyber-attacks on various components such as the Energy Storage System (ESS), the automatic voltage regulator (AVR) of the synchronous generator, the grid side converter (GSC) of the wind generator, and the voltage source converter (VSC) of Photovoltaic (PV) system, located in a hybrid power grid. Also, this dissertation proposes two new techniques such as a Non-Linear (NL) controller and a Proportional-Integral (PI) controller for mitigating the adverse effects of cyber-attacks on the mentioned devices, and a new detection and mitigation technique based on the voltage threshold for the Supercapacitor Energy System (SES). Simulation results obtained through the MATLAB/Simulink software show the effectiveness of the proposed new control methods for power quality improvement. Also, the proposed methods perform better than conventional methods

Modelling methodologies for railway asset management

Management of railway assets incurs significant expenditure. Railway asset management modelling can predict the cost and efficacy of an asset management plan, and thus support the asset management planning process. Modelling frameworks can be used to facilitate the development of large, multi-asset, whole life cycle models which can be used to represent large sections of rail track and associated assets. This is achieved with libraries of models and tools with a high level of inter-compatibility. This research set out to support the development of modelling frameworks for railway asset management. It sought to determine the state of the art of railway asset management modelling in order to find which assets require further modelling development before they can be suitably represented in a framework’s model library. It also sought to determine the most accurate and suitable modelling methodology to base the framework upon. These aims were met by first carrying out a literature review to determine the state of the art of asset management modelling for major railway asset types. This review found Petri net models solved via Monte Carlo methods to be the most suitable modelling methodology for asset management. The level crossing asset class was chosen for the development of several models to explore the different types of Petri net model, concentrating on the computational resources required. This asset class was chosen as no asset management model was found in literature, and the diversity of the asset interactions. Literature review found several asset classes in need of further development, and some where asset management modelling may not be possible without other advances. The level crossing Petri net models developed demonstrated that computational requirements differ between the various types of Petri net. Stochastic Petri nets were found to simulate quickly, but had a high memory requirement. Coloured Petri nets were found to have the opposite requirements. A novel Petri net type, the Simple Coloured Petri net was developed to create a balance in computational cost. It was further found that complex processes such as scheduling and resource allocation can only be carried out using Coloured Petri nets due to their enhanced feature set. This work has found that further research on modelling specific asset classes is required to enable the development of a complete asset modelling library for use in a framework. If large models are to be developed, it is recommended that the Simple Coloured Petri net be used to balance computational requirements. Any models requiring complex functions should be developed using the Coloured Petri net methodology