Rotating Electrical Machines: Types, Applications and Recent Advances

The Rotating Electrical Machines (REMs) are classified into Motors and Generators. They powered the industrial, domestic and commercial loads. Because of their importance. This paper discussed different types of REMs, their applications and recent advances. REMs are applied in Teaching, Domestic, Mechatronics, Motorcycle, Three-wheelers, Electric Vehicle, Healthcare, Flywheel Energy Storage and Wind Energy Conversion Systems. It periscopes the advances of REMs in design, Fault diagnostic, control and condition monitoring. Its significance is to shed light on some advances made in REM

Model Parameter Calibration in Power Systems

In power systems, accurate device modeling is crucial for grid reliability, availability, and resiliency. Many critical tasks such as planning or even realtime operation decisions rely on accurate modeling. This research presents an approach for model parameter calibration in power system models using deep learning. Existing calibration methods are based on mathematical approaches that suffer from being ill-posed and thus may have multiple solutions. We are trying to solve this problem by applying a deep learning architecture that is trained to estimate model parameters from simulated Phasor Measurement Unit (PMU) data. The data recorded after system disturbances proved to have valuable information to verify power system devices. A quantitative evaluation of the system results is provided. Results showed high accuracy in estimating model parameters of 0.017 MSE on the testing dataset. We also provide that the proposed system has scalability under the same topology. We consider these promising results to be the basis for further exploration and development of additional tools for parameter calibration

Formal Design of Asynchronous Fault Detection and Identification Components using Temporal Epistemic Logic

Autonomous critical systems, such as satellites and space rovers, must be able to detect the occurrence of faults in order to ensure correct operation. This task is carried out by Fault Detection and Identification (FDI) components, that are embedded in those systems and are in charge of detecting faults in an automated and timely manner by reading data from sensors and triggering predefined alarms. The design of effective FDI components is an extremely hard problem, also due to the lack of a complete theoretical foundation, and of precise specification and validation techniques. In this paper, we present the first formal approach to the design of FDI components for discrete event systems, both in a synchronous and asynchronous setting. We propose a logical language for the specification of FDI requirements that accounts for a wide class of practical cases, and includes novel aspects such as maximality and trace-diagnosability. The language is equipped with a clear semantics based on temporal epistemic logic, and is proved to enjoy suitable properties. We discuss how to validate the requirements and how to verify that a given FDI component satisfies them. We propose an algorithm for the synthesis of correct-by-construction FDI components, and report on the applicability of the design approach on an industrial case-study coming from aerospace.Comment: 33 pages, 20 figure

The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems

Includes bibliographical references (leaves 128-129).The thesis examines the use of two time-frequency domain signal processing tools in its application to condition monitoring of electrical machine drive systems. The mathematical and signal processing tools which are explored are wavelet analysis and a non-stationary adaptive signal processing algorithm. Four specific applications are identified for the research. These applications were specifically chosen to encapsulate important issues in condition monitoring of variable speed drive systems. The main aim of the project is to highlight the need for fault detection during machine transients and to illustrate the effectiveness of incorporating and adapting these new class of algorithms to detect faults in electrical machine drive systems during non-stationary conditions

Low-head pumped hydro storage: A review of applicable technologies for design, grid integration, control and modelling

To counteract a potential reduction in grid stability caused by a rapidly growing share of intermittent renewable energy sources within our electrical grids, large scale deployment of energy storage will become indispensable. Pumped hydro storage is widely regarded as the most cost-effective option for this. However, its application is traditionally limited to certain topographic features. Expanding its operating range to lowhead scenarios could unlock the potential of widespread deployment in regions where so far it has not yet been feasible. This review aims at giving a multi-disciplinary insight on technologies that are applicable for low-head (2-30 m) pumped hydro storage, in terms of design, grid integration, control, and modelling. A general overview and the historical development of pumped hydro storage are presented and trends for further innovation and a shift towards application in low-head scenarios are identified. Key drivers for future deployment and the technological and economic challenges to do so are discussed. Based on these challenges, technologies in the field of pumped hydro storage are reviewed and specifically analysed regarding their fitness for low-head application. This is done for pump and turbine design and configuration, electric machines and control, as well as modelling. Further aspects regarding grid integration are discussed. Among conventional machines, it is found that, for high-flow low-head application, axial flow pump-turbines with variable speed drives are the most suitable. Machines such as Archimedes screws, counter-rotating and rotary positive displacement reversible pump-turbines have potential to emerge as innovative solutions. Coupled axial flux permanent magnet synchronous motor-generators are the most promising electric machines. To ensure grid stability, grid-forming control alongside bulk energy storage with capabilities of providing synthetic inertia next to other ancillary services are required

Multi-agent control and operation of electric power distribution systems

This dissertation presents operation and control strategies for electric power distribution systems containing distributed generators. First, models of microturbines and fuel cells are developed. These dynamic models are incorporated in a power system analysis package. Second, operation of these generators in a distribution system is addressed and load following schemes are designed. The penetration of distributed generators (DGs) into the power distribution system stability becomes an issue and so the control of those DGs becomes necessary. A decentralized control structure based on conventional controllers is designed for distributed generators using a new developed optimization technique called Guided Particle Swarm Optimization. However, the limitations of the conventional controllers do not satisfy the stability requirement of a power distribution system that has a high DG penetration level, which imposes the necessity of developing a new control structure able to overcome the limitations imposed by the fixed structure conventional controllers and limit the penetration of DGs in the overall transient stability of the distribution system. Third, a novel multi-agent based control architecture is proposed for transient stability enhancement for distribution systems with microturbines. The proposed control architecture is hierarchical with one supervisory global control agent and a distributed number of local control agents in the lower layer. Specifically, a central control center supervises and optimizes the overall process, while each microturbine is equipped with its own local control agent.;The control of naval shipboard electric power system is another application of distributed control with multi-agent based structure. In this proposal, the focus is to introduce the concept of multi-agent based control architecture to improve the stability of the shipboard power system during faulty conditions. The effectiveness of the proposed methods is illustrated using a 37-bus IEEE benchmark system and an all-electric naval ship

Method of Testing and Diagnosing Field Programmable Gate Arrays

A method of testing field programmable gate arrays (FPGAs) includes establishing a first group of programmable logic blocks as test pattern generators or output response analyzers and a second group of programmable logic blocks as blocks under test. This is followed by generating test patterns and comparing outputs of two blocks under test with one output response analyzer. Next is the combining of results of a plurality of output response analyzers utilizing an iterative comparator in order to produce a pass/fail indication. The method also includes the step of reconfiguring each block under test so that each block under test is tested in all possible modes of operation. Further, there follows the step of reversing programming of the groups of programmable logic blocks so that each programmable logic block is configured at least once as a block under test