Efficient model-correction-based reliability analysis of uncertain dynamical systems

The scope of this paper is to apply a model-correction-based strategy for efficient reliability analysis of uncertain dynamical systems based on a low-fidelity (LF) model whose outcomes are corrected in a probabilistic sense to represent the more realistic outcomes of a high-fidelity (HF) model. In the model-correction approach utilized, the LF model is calibrated to the HF model close to the so-called most probable point in standard normal space, which allows a more realistic assessment of the considered complex dynamical system. Since only few expensive limit state function evaluations of the HF model are required, an efficient reliability analysis is enabled. In an application example, the LF model describes an existing single-span railway bridge modelled as simply supported Euler–Bernoulli beam subjected to moving single forces representing the axle loads of a moving train. The HF modelling approach accounts for the bridge–train interaction by modelling the passing train as mass-spring-damper system, however increasing the computational effort of the limit state function evaluations. Failure probabilities evaluated with the model-correction approach are contrasted and discussed with failure probabilities of the sophisticated bridge–train interaction model evaluated with the first-order reliability method (FORM). It is demonstrated that the efficiency of the method depends on the correlation between the LF and the HF model. A comparison of the results of FORM and the model-correction-based approach shows that the latter provides reliable failure probability prediction of the HF model while leading to a significant reduction in computational effort

Supporting transient stability in future highly distributed power systems

Incorporating a substantial volume of microgeneration (consumer-led rather than centrally planed) within a system that is not designed for such a paradigm could lead to conflicts in the operating strategies of the new and existing centralised generation technologies. So it becomes vital for such substantial amounts of microgeneration among other decentralised resources to be controlled in the way that the aggregated response will support the wider system. In addition, the characteristic behaviour of such populations requires to be understood under different system conditions to ascertain measures of risk and resilience. Therefore, this paper provides two main contributions: firstly, conceptual control for a system incorporating a high penetration of microgeneration and dynamic load, termed a Highly Distributed Power System (HDPS), is proposed. Secondly, a technical solution that can support enhanced transient stability in such a system is evaluated and demonstrated

Customer Engagement Plans for Peak Load Reduction in Residential Smart Grids

In this paper, we propose and study the effectiveness of customer engagement plans that clearly specify the amount of intervention in customer's load settings by the grid operator for peak load reduction. We suggest two different types of plans, including Constant Deviation Plans (CDPs) and Proportional Deviation Plans (PDPs). We define an adjustable reference temperature for both CDPs and PDPs to limit the output temperature of each thermostat load and to control the number of devices eligible to participate in Demand Response Program (DRP). We model thermostat loads as power throttling devices and design algorithms to evaluate the impact of power throttling states and plan parameters on peak load reduction. Based on the simulation results, we recommend PDPs to the customers of a residential community with variable thermostat set point preferences, while CDPs are suitable for customers with similar thermostat set point preferences. If thermostat loads have multiple power throttling states, customer engagement plans with less temperature deviations from thermostat set points are recommended. Contrary to classical ON/OFF control, higher temperature deviations are required to achieve similar amount of peak load reduction. Several other interesting tradeoffs and useful guidelines for designing mutually beneficial incentives for both the grid operator and customers can also be identified

Bridge expansion joint in road transition curve: effects assessment on heavy vehicles

Properly-designed road surfaces provide a durable surface on which traffic can pass smoothly and safely. In fact, the main causes that determine the structural decay of the pavement and its parts are the traffic loads. These repeated actions can create undesirable unevennesses on the road surface, which induce vertical accelerations on vehicles, up to hindering contact between pavement and tire, with dangerous consequences on traffic safety. The dynamic actions transmitted by the vehicles depend on these irregularities: often, a bridge expansion joint (BEJ), introducing a necessary discontinuity between different materials, determines from the beginning a geometric irregularity in the running surface. Besides, some structural conditions could emphasize the problem (e.g., local cracking due to the settlement of the subgrade near the abutment or the discontinuity of stiffness due to the presence of different materials). When the BEJ is located in a transition curve, an inevitable vertical irregularity between road and joint can reach values of some centimeters, with serious consequences for the road safety. This paper deals with the analysis of a case study of a BEJ. Several test surveys were performed in order to fully characterize the effects on both vehicles and pavement. The three-dimensional representation of the pavement surface and the acceleration measurements on a heavy test vehicle were performed to analyze the joint behavior under traffic. Finally, a finite element model was implemented to evaluate the stress contribution on vehicle components induced by the vertical irregularities

Extension of a discontinuous Galerkin finite element method to viscous rotor flow simulations

Heavy vibratory loading of rotorcraft is relevant for many operational aspects of helicopters, such as the structural life span of (rotating) components, operational availability, the pilot's comfort, and the effectiveness of weapon targeting systems. A precise understanding of the source of these vibrational loads has important consequences in these application areas. Moreover, in order to exploit the full potential offered by new vibration reduction technologies, current analysis tools need to be improved with respect to the level of physical modeling of flow phenomena which contribute to the vibratory loads. In this paper, a computational fluid dynamics tool for rotorcraft simulations based on first-principles flow physics is extended to enable the simulation of viscous flows. Viscous effects play a significant role in the aerodynamics of helicopter rotors in high-speed flight. The new model is applied to three-dimensional vortex flow and laminar dynamic stall. The applications clearly demonstrate the capability of the new model to perform on deforming and adaptive meshes. This capability is essential for rotor simulations to accomodate the blade motions and to enhance vortex resolution

Data-Driven Diagnostics of Mechanism and Source of Sustained Oscillations

Sustained oscillations observed in power systems can damage equipment, degrade the power quality and increase the risks of cascading blackouts. There are several mechanisms that can give rise to oscillations, each requiring different countermeasure to suppress or eliminate the oscillation. This work develops mathematical framework for analysis of sustained oscillations and identifies statistical signatures of each mechanism, based on which a novel oscillation diagnosis method is developed via real-time processing of phasor measurement units (PMUs) data. Case studies show that the proposed method can accurately identify the exact mechanism for sustained oscillation, and meanwhile provide insightful information to locate the oscillation sources.Comment: The paper has been accepted by IEEE Transactions on Power System

Moving vehicle load identification from bridge responses based on method of moments (MOM)

A MOM-based algorithm (MOMA) is proposed for identifying of the time-varying moving vehicle loads on a bridge in this paper. A series of numerical simulations and experiments in laboratory have been studied and the proposed MOMA are compared with the existing time domain method (TDM). A few main parameters, such as basis function terms, executive CPU time, Nyquist fraction of digital filter, two different solutions to the ill-posed system equation, etc, have been investigated. Both the numerical simulation and experimental results show that the MOMA has higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-conditioning cases to some extent, but its CPU execution time is just less than one tenth of the TDM