Time-varying Loading Conditions Research Articles

Optimal Design of Volt/VAR Control Rules for Inverter-Interfaced Distributed Energy Resources

The IEEE 1547 Standard for the interconnection of distributed energy resources (DERs) to distribution grids provisions that smart inverters could be implementing Volt/VAR control rules among other options. Such rules enable DERs to respond autonomously in response to time-varying grid loading conditions. The rules comprise affine droop control augmented with a deadband and saturation regions. Nonetheless, selecting the shape of these rules is not an obvious task, and the default options may not be optimal or dynamically stable. To this end, this work develops a novel methodology for customizing Volt/VAR rules on a per-bus basis for a single-phase feeder. The rules are adjusted by the utility every few hours depending on anticipated demand and solar scenarios. Using a projected gradient descent-based algorithm, rules are designed to improve the feeder’s voltage profile, comply with IEEE 1547 constraints, and guarantee stability of the underlying nonlinear grid dynamics. The stability region is inner approximated by a polytope and the rules are judiciously parameterized so their feasible set is convex. Numerical tests using real-world data on the IEEE 141-bus feeder corroborate the scalability of the methodology and explore the trade-offs of Volt/VAR control with alternatives.

Efficient Control of a Switched Inertance Hydraulic Converter With a Time-Varying Load

Abstract Digital hydraulics is a novel alternative to proportional or servovalve-controlled systems in fluid power engineering, providing hydraulic systems with high-energy efficiency, good controllability, and insensitivity to contamination. Switched inertance hydraulic converters (SIHCs) are new digital hydraulic devices that can adjust flow and pressure by digital switching instead of throttling the flow. In this paper, an efficient closed-loop control system is proposed for SIHCs subject to time-varying loading conditions in which the load pressure and/or flow varies with time. The control system is designed to operate SIHCs at optimized switching frequencies and ratios that maximize system efficiency when the load varies. With the proposed controller, the SIHC can effectively adapt to the time-varying load and has achieved up to 10% efficiency improvement and up to 65% pressure ripple reduction without affecting the system's dynamic responses, compared with using a nonoptimized controller. The work shows the feasibility and advantages of simultaneously controlling the switching ratio and switching frequency of SIHCs with a time-varying load. As time-varying loading conditions are commonly found in hydraulic applications, the research outcomes constitute an important aspect in the design and development of highly efficient SIHCs and their practical use in hydraulic machinery.

Impedance Variation Detection at MISO Receivers

Techniques have been proposed to estimate unknown antenna impedance due to time-varying near-field loading conditions at multiple-input single-output (MISO) receivers. However, it remains unclear when a change occurs and impedance estimation becomes necessary. In this letter, we address this problem by formulating it as a hypothesis test. Our contributions include deriving a generalized likelihood-ratio test (GLRT) detector to decide if the antenna impedance has changed over two groups of packets. This GLRT formulation leads to a novel optimization problem, but we propose a binary search based algorithm to solve it efficiently. Our derived GLRT detector enjoys a better detection and false alarm trade-off when compared with a well-known, reference detector in simulations. As one result, more transmit diversity significantly improves detection accuracy at a given false alarm rate, especially in slow fading channels.

Rapid scan EPR: Automated digital resonator control for low-latency data acquisition

Automation has become an essential component of modern scientific instruments which often capture large amounts of complex dynamic data. Algorithms are developed to read multiple sensors in parallel with data acquisition and to adjust instrumental parameters on the fly. Decisions are made on a time scale unattainable to the human operator. In addition to speed, automation reduces human error, improves the reproducibility of experiments, and improves the reliability of acquired data. An automatic digital control (ADiC) was developed to reliably sustain critical coupling of a resonator over a wide range of time-varying loading conditions. The ADiC uses the computational power of a microcontroller that directly communicates with all system components independent of a personal computer (PC). The PC initiates resonator tuning and coupling by sending a command to MC via serial port. After receiving the command, ADiC establishes critical coupling conditions within approximately 5 ms. A printed circuit board resonator was designed to permit digital control. The performance of the resonator together with the ADiC was evaluated by varying the resonator loading from empty to heavily loaded. For the loading, samples containing aqueous sodium chloride that strongly absorb electromagnetic waves were used. A previously reported rapid scan (RS) electron paramagnetic resonance (EPR) imaging instrument was upgraded by the incorporation of ADiC. RS spectra and an in vivo image of oxygen in a mouse tumor model have been acquired using the upgraded system. ADiC robustly sustained critical coupling of the resonator to the transmission line during these measurements. The design implemented in this study can be used in slow-scan and pulsed EPR with modifications.

Experimental investigation on the fatigue behavior of laser powder bed fused 316L stainless steel

Additive manufacturing of metal powder materials through Laser Powder Bed Fusion (LPBF) allows for a single-step fabrication process of complex geometries. However, the introduction of such an innovative technology opens new questions about the fatigue life of functional components especially intended for applications where the products are subjected to severe time-varying loading conditions. In this context, the present work aims at evaluating the fatigue strength of 316L stainless steel samples fabricated through laser powder bed fusion by controlling the building orientation and the volumetric energy density. The work at first presents the response of the LPBF fabricated samples to a monotonic tensile load for varying building orientations. It follows the presentation of their fatigue response to a reverse bending loading condition. Quasi-static tensile tests show that LPBF specimens have lower elastic modulus but higher ultimate and yield strength than the original bulk material, whereby the results evidence a strong anisotropy related to the building orientation. Porosity and building orientation are found to strongly affect the fatigue behavior, with the fatigue limit which lowers from 50% of the ultimate strength of the bulk material down to 20% for the LPBF-ed specimens. Finally, the observation of the failure surfaces suggests that the early fracture of the samples is due to the concomitant initiations of cracks at different sites that eventually coalesce and promote the failure.

Estimation of the damping model of a spur gear pair system including a time-varying loading

The integral method was used in a previous research to identify the damping model but this technique has some limitations in estimating the damping model in a gear system including time-varying loading conditions. To overcome these limitations, the integral method is reformulated in this research to identify the damping model on spur gear pair system including variable loading. The motion equations presented in terms of integrals, including time-varying loading conditions, are solved by linear least squares method to characterise the constant piecewise model. Continuous wavelet transform method is used to validate the constant damping model. The new methodology is tested with a signal obtained from numerical simulation.

Integrated Prognosis for Wind Turbine Gearbox Condition-Based Maintenance Considering Time-Varying Load and Crack Initiation Time Uncertainty

Maintenance management in wind energy industry has great impact on the overall wind power cost. Maintenance services are either supported by wind turbine manufacturers within warranty period, or managed by wind farm owners. With condition-based maintenance (CBM) strategy, maintenance activities are scheduled based on the predicted health conditions of wind turbine components, and accurate prognostics methods are critical for effective CBM. The reported studies on integrated health prognostics considered the uncertainty in crack initiation time (CIT) uncertainty, but did not incorporate time-varying loading conditions, which could also have a significant impact on future health condition and remaining useful life (RUL) prediction. Constant loads were generally used to approximate the actual time-varying loading conditions. In this paper, an integrated prognostics method is proposed for wind turbine gearboxes considering both time-varying loading conditions and CIT uncertainty. As new condition monitoring observations are available, the distributions of both material model parameter and CIT are updated via Bayesian inference, and the failure time prediction is updated accordingly. An example is provided to demonstrate that the proposed time-varying load approach presents more benefits considering the uncertainty of CIT, with significant accuracy improvement comparing to the constant-load approach.

Fast and Optimized Calculation of the Cable Pretension Forces in Arch Bridges With Suspended Deck

This paper deals with an effective and fast approach to the optimization of the pretension forces in arched bridges with suspended deck, which makes use of the influence matrix method. The given cable-tensioning procedure leads to a linear system of equations with a reduced number of unknowns and can be effectively implemented within active control procedures that handle time-varying loading conditions. It achieves of a target bending moment distribution over the structure, which significantly mitigates the state of stress of the deck. Numerical results dealing with a Nielsen arch bridge illustrate the versatility of the proposed approach when dealing with different loading conditions

An Integrated Prognostics Approach for Pipeline Fatigue Crack Growth Prediction Utilizing Inline Inspection Data

Fatigue cracking is a key type of defect for liquid pipelines, and managing fatigue cracks has been a top priority and a big challenge for liquid pipeline operators. The existing inline inspection (ILI) tools for pipeline defect evaluation have large fatigue crack measurement uncertainties. Furthermore, the current physics-based methods are mainly used for fatigue crack growth prediction, where the same or a small range of fixed model parameters is used for all pipes. They result in uncertainty that is managed through the use of conservative safety factors such as adding depth uncertainty to the measured depth in deciding integrity management and risk mitigation strategies. In this study, an integrated approach is proposed for pipeline fatigue crack growth prediction utilizing ILI data including consideration of crack depth measurement uncertainty. This approach is done by integrating the physical models, including the stress analysis models, the crack growth model governed by the Paris’ law, and the ILI data. With the proposed integrated approach, the finite element (FE) model of a cracked pipe is built and the stress analysis is performed. ILI data are utilized to update the uncertain physical parameters for the individual pipe being considered so that a more accurate fatigue crack growth prediction can be achieved. Time-varying loading conditions are considered in the proposed integrated method by using rainflow counting method. The proposed integrated prognostics approach is compared with the existing physics-based method using examples based on simulated data. Field data provided by a Canadian pipeline operator are also employed for the validation of the proposed method. The examples and case studies in this paper demonstrate the limitations of the existing physics-based method, and the promise of the proposed method for achieving accurate fatigue crack growth prediction as continuous improvement of ILI technologies further reduces ILI measurement uncertainty.

Maximizing Available Delivery Capability of Unbalanced Distribution Networks for High Penetration of Distributed Generators

The network reconfiguration technique has been used to reduce network losses, balance transformer loading, and restore the power supply of the outage area in distribution networks. With a large number of uncontrollable distributed generators (DGs) added to distribution networks, the reconfiguration technique can be applied to enhance the available delivery capability (ADC) of distribution networks. This paper presents a two-stage methodology for determining optimal network topologies for improving the ADC of distribution networks for supporting more renewable energies. The first stage is a group-based binary particles swarm optimization (BPSO), which takes advantage of the BPSO's global capability while improving its slowness in finding optimal solutions. The second stage is a hybrid of greedy-based and domain-knowledge-based methods. When applied to multiple scenarios of DGs, the proposed methodology can effectively deal with the uncertainty of the DGs' outputs and time-varying loading conditions. As a byproduct, the optimal network topology found by the proposed methodology also decreases the network power losses due to the increase of the ADC of the distribution networks. The IEEE 123-bus test network and a practical 1001-node distribution network are used to verify the proposed methodology, and the numerical studies demonstrate the effectiveness of the proposed methodology in greatly increasing the ADC via optimal network reconfigurations.

Effects of variable loading conditions on the dynamic behaviour of planetary gear with power recirculation

Abstract Variable loads to which gearboxes are subjected are considered as one of the main sources of non-stationarity in these transmissions. In order to characterise their dynamic behaviour in such conditions, a torsional lumped parameter model of a planetary gear with power recirculation was developed. The model included time varying loading conditions and took into account the non-linearity of contact between teeth. The meshing stiffness functions were modelled using Finite Element Method and Hertzian contact theory in these conditions. Series of numerical simulations was conducted in stationary conditions, with different loading conditions. Equation of motion was solved using Newmark algorithm. Numerical results agreed with experimental results obtained from a planetary gear test bench. This test bench is composed of two similar planetary gears called test planetary gear set and reaction planetary gear set which are mounted back-to-back so that the power recirculates through the transmission. The external load was applied through an arm attached to the free reaction ring. Data Acquisition System acquired signals from accelerometers mounted on the rings and tachometer which measured instantaneous angular velocity of the carrier’s shaft. The signal processing was achieved using LMS Test.Lab software. Modulation sidebands were obtained from the ring acceleration measurements as well as a non-linear behaviour in case of variable loading resulted by a transfer of the spectral density from the fundamental mesh stiffness to its second harmonic.

A multi-level control architecture for master-slave organized microgrids with power electronic interfaces

This paper presents a multi-level control architecture for autonomous operation of islanded microgrids with power electronic interfaces. An upper layer performs calculations for system dispatch while a lower layer computes appropriate control actions for the power electronic interfaces. The upper layer of communication-based intelligent control is realized through a decentralized multi-agent system (MAS). Two control strategies are implemented in this layer: MAS power balance control and economic dispatch. In MAS power balance control, a rational communication scheme is proposed to construct a minimal spanning tree structure among agents, so that the multi-agent system can efficiently discover system global information and dispatch generation and load to maintain real and reactive power balance; in economic dispatch, by comparing incremental cost with neighbors, generator agents can achieve minimum generation cost for system operation. To demonstrate the speed and effectiveness of the proposed algorithms, IEEE 14, 30, 57 and 118 bus systems are studied for the MAS power balance control and economic dispatch in MATLAB. A demonstration presents implementation of multi-agent system using Java agent development framework and includes a viable implementation of the lower layer, which is used to control power electronic interfaced distributed generators, and is realized through conventional local controllers for master-slave organized microgrids. A case study with time-varying loading conditions is demonstrated to validate the proposed multi-level control architecture.

Smart sensing of damage in flexible plates through MEMS

In this work, we present a methodology to monitor the state of damage- or crack-containing flexible plates through low-cost, commercial off-the-shelf MEMS accelerometers. Under quasi-static, time-varying loading conditions we track the evolution of the damaged zone (e.g., the length of an inner crack) accounting for the drift in the compliance of the specimens, measured by means of the magnitude of the load-induced rotation at MEMS position. We then validate this health monitoring methodology, showing that it turns out to be sensitive to the damage and provides results in good accordance with theoretical findings. Next, we propose a technique to optimally deploy the MEMS sensors over the plate. Referring to an isotropic square plate containing damaged zones of reduced bending stiffness, we numerically investigate the sensitivity of the load-induced state (in terms of out-of-plane displacement and rotation of the normal to the mid-plane) to the position of the damaged area, and we adopt a constrained topology optimisation tool to determine the best sensor deployment to efficiently sense the damage.

Serial manipulator functional calibration for in vitro biomechanical testing

Serial manipulators are often used in biomechanical testing of human joints because they are precise, repeatable instruments that can create interesting loading scenarios. Unfortunately, commercial serial manipulators often do not have acceptable global positional accuracy due to manufacturing tolerances, assembly errors, and other mechanical imperfections. Numerous calibration methods have been reported which calibrate geometric and non-geometric parameters to reduce static position errors under constant loading conditions. However, the manipulator's global accuracy during continuous motion with time-varying external loading conditions is often not addressed but is necessary for joint biomechanical testing. Using the Mitsubishi PA10-6CE as a case study, a novel functional calibration procedure was developed that performs both static and dynamic calibration. The calibration uses optimization techniques to populate a 34-parameter model that accounts for the robot's geometric and non-geometric parameters and significantly reduces the mean/peak static and dynamic position errors to 0.368/0.67mm and 0.353/0.81mm, respectively, while externally loaded.

Damage assessment of pre-stressed structures: A SVD-based approach to deal with time-varying loading

Vibration-based methods are well-established and effective tools to assess the health state of civil, mechanical and aerospace engineering structures. However, their reliability is still affected by the variability of the features commonly used for damage detection. Environmental effects and changes in operational conditions are the main sources of variability in the structural response. As a consequence, the modal identification used to extract damage sensitive features has to face constricting requirements in terms of signals stationarity and performance accuracy. Moreover, with reference to the damage assessment, large variations of monitored features mask subtle effects due to damage, which remain undetected. This study is conceived to address both these issues by focusing, in particular, on the non-stationarity of the loading conditions of tensioned structures, such as cables and pre-stressed beams. The capability of spectral methods to deal with the modal identification of non-stationary systems is enhanced by a curve-fitting procedure based on nonlinear least squares optimization. Wavelet analysis is applied for comparison and validation of the FFT-based technique. Identified natural frequencies are then used for the damage detection, exploiting the capacity of singular values decomposition to discriminate between damage-related events and the intrinsic non-stationary nature of the structural response. A reduced-order realization of the features set is performed to amplify changes not belonging to measurement variability but deriving from exogenous events, such as damage. The proposed methodology is validated by experimental analyses carried out on beams subjected to time-varying loading conditions in order to simulate the health monitoring of quasi and non-stationary systems.

Effect of Load Shape in Cyclic Load Variation on Dynamic Behavior of Spur Gear System

Transmissions including spur gears are widely used in several industrial applications. They are characterized by high efficiency and capability to transmit high torques. A special attention should be made for transmissions running under varying loading conditions which have to be well monitored. The presence of this variability associated with defects that may occur in the transmission will complicate its condition monitoring. The first step to overcome this difficulty is to identify and characterize the dynamic response of the transmission in healthy conditions subjected to variable loading conditions. In this paper, a model based approach is presented in order investigate the influence of the loading shape on the vibration characteristics of the transmission. A dynamic model of a one stage spur gear transmission including a time varying loading conditions is developed. Two cases of loading conditions are considered. A parametric study is achieved and main conclusions are discussed.

Optimizing qos routing in hierarchical atm networks using computational intelligence techniques

In this paper, the use of a computational intelligence approach -a reinforcement learning algorithm (RLA)-for optimizing the routing in asynchronous transfer mode (ATM) networks based on the private network-to-network interface (PNNI) standard is proposed. This algorithm which is specially designed for the quality of service (QoS) routing problem, aims at maximizing the network revenue (allocating efficiently the network resources) while ensuring the QoS requirements for each connection. In this study, large-scale networks are considered where it becomes necessary to be organized hierarchically so that a scale in terms of computation, communication and storage requirements will be achieved. A comparative performance study of the proposed and other commonly used routing schemes is demonstrated by means of simulation on existing commercial networks. Simulation results over a wide range of uniform, time-varying and skewed loading conditions show the effectiveness of the proposed routing algorithm, and disclose the strength and weakness of the various schemes.