Improve the Flexibility of Power Distribution Network by Using Back-to-back Voltage Source Converter

Employing increasing distributed generations (DGs) into existing distribution networks is an inevitable trend of the development of modern electric power systems because of the benefits including the environmentally friendly generation, higher efficiency and improved flexibility and reliability. However, high DG penetration level could pose various issues among which the voltage violation and fault level increase are the most concerned. According to the current situation of UK distribution networks, voltage violation is likely to be the first constraint to be met when DG penetration level is increased to certain level. Therefore, compensators are considered to be implemented to regulate the voltage. The reactive power compensators that widely used in transmission systems appear less effective in distribution networks thus active power compensation is desired. Soft-open points (SOPs) are power-electronic devices used replacing the normally-open points which can control active power transfer between two feeders and/or provide reactive power compensation. The back-to-back voltage source converter (B2B-VSC) is preferred as the SOP because of its capability of restricting fault current despite that it has higher power loss and associated capital cost. Two types of controller are developed for the B2B-VSC-based SOP: one is based on the PI control theory and the other is based on the concept of synchronverters. For the former type, the controller design is introduced comprehensively including system modelling and parameters selection. The precise selection of the damping ratio for nonstandard second-order system is derived, and a technique of resetting integrator in output voltage controller loop to achieve fast and smooth islanding transition is proposed. For the latter type, modifications are made to adapt the synchronverter idea to the application of an SOP. Simulations and experiments are carried out to validate the controller designs and both the controllers are verified to be able to provide sufficient performance on voltage regulation, fault current restriction and independent load supply in island mode. In general, the controller based on PI control theory has better performance in fault condition thanks to the current control loop, and the controller based on synchronverter owns better reliability because it does not require additional detections and signal switches inside the controller. At last, the use of an SOP in a dynamic load dominated network after the loss of mains is further investigated. Torque-speed characteristic is used to analyse the influence of the VSC’s filter impedance on the stability margin of an induction motor. Though the filter impedance can significantly decrease the stability margin, the output impedance of the VSC can be mitigated by properly designing the output voltage controller. Simulation and experiment are carried out to validate the analyses and controller design. The results show that the VSC is capable of supplying an induction motor in island mode

Interval Fuzzy Model for Robust Aircraft IMU Sensors Fault Detection

This paper proposes a data-based approach for a robust fault detection (FD) of the inertial measurement unit (IMU) sensors of an aircraft. Fuzzy interval models (FIMs) have been introduced for coping with the significant modeling uncertainties caused by poorly modeled aerodynamics. The proposed FIMs are used to compute robust prediction intervals for the measurements provided by the IMU sensors. Specifically, a nonlinear neural network (NN) model is used as central prediction of the sensor response while the uncertainty around the central estimation is captured by the FIM model. The uncertainty has been also modelled using a conventional linear Interval Model (IM) approach; this allows a quantitative evaluation of the benefits provided by the FIM approach. The identification of the IMs and of the FIMs was formalized as a linear matrix inequality (LMI) optimization problem using as cost function the (mean) amplitude of the prediction interval and as optimization variables the parameters defining the amplitudes of the intervals of the IMs and FIMs. Based on the identified models, FD validation tests have been successfully conducted using actual flight data of a P92 Tecnam aircraft by artificially injecting additive fault signals on the fault free IMU readings

Architecting Integrated System Health Management for Airworthiness

Integrated System Health Management (ISHM) for Unmanned Aerial Systems (UAS) has been a new area of research - seeking to provide situational awareness to mission and maintenance operations, and for improved decision-making with increased self-autonomy. This research effort developed an analytic architecture and an associated discrete-event simulation using Arena to investigate the potential benefits of ISHM implementation onboard an UAS. The objective of this research is two-fold: firstly, to achieve continued airworthiness by investigating the potential extension of UAS expected lifetime through ISHM implementation, and secondly, to reduce life cycle costs by implementing a Condition-Based Maintenance (CBM) policy with better failure predictions made possible with ISHM. Through a series of design experiments, it was shown that ISHM presented the most cost-effective improvement over baseline systems in situations where the reliability of the UAS is poor (relative to manned systems) and the baseline sensor exhibited poor qualities in terms of missed detection and false alarm rates. From the simulation results of the test scenarios, it was observed that failure occurrence rates, sensor quality characteristics and ISHM performance specifications were significant factors in determining the output responses of the model. The desired outcome of this research seeks to provide potential designers with top-level performance specifications of an ISHM system based on specified airworthiness and maintenance requirements for the envisaged ISHM-enabled UAS

EMPIRICAL ASSESSMENT OF THE IMPACT OF USING AUTOMATIC STATIC ANALYSIS ON CODE QUALITY

Automatic static analysis (ASA) tools analyze the source or compiled code looking for violations of recommended programming practices (called issues) that might cause faults or might degrade some dimensions of software quality. Antonio Vetro' has focused his PhD in studying how applying ASA impacts software quality, taking as reference point the different quality dimensions specified by the standard ISO/IEC 25010. The epistemological approach he used is that one of empirical software engineering. During his three years PhD, he's been conducting experiments and case studies on three main areas: Functionality/Reliability, Performance and Maintainability. He empirically proved that specific ASA issues had impact on these quality characteristics in the contexts under study: thus, removing them from the code resulted in a quality improvement. Vetro' has also investigated and proposed new research directions for this field: using ASA to improve software energy efficiency and to detect the problems deriving from the interaction of multiple languages. The contribution is enriched with the final recommendation of a generalized process for researchers and practitioners with a twofold goal: improve software quality through ASA and create a body of knowledge on the impact of using ASA on specific software quality dimensions, based on empirical evidence. This thesis represents a first step towards this goa