Realistic System Model Research Articles

The Effect of FRT Behavior of VSC-HVDC-Connected Offshore Wind Power Plants on AC/DC System Dynamics

Future power systems will contain more converter-based generation, among which are the voltage-source converter–high-voltage direct-current (VSC-HVDC)-connected offshore wind power plants (WPP). Their interaction with the onshore system influences power system dynamics in the transient stability timeframe. The respective protection and control methods which cause this interaction must be taken into account in grid-integration studies performed today. This paper gives insight into the effect of typically required fault ridethrough (FRT) and post-FRT measures of VSC-HVDC-connected offshore WPPs on the combined ac and HVDC system dynamics. Several important sensitivities are addressed, among which are: 1) FRT implementation, 2) the postfault active power-recovery rates, 3) the ac network dynamic characteristics, and 4) the HVDC topology. The analysis is first performed as a proof of concept on a small benchmark system, and subsequently generalized to a realistic dynamic model of the future Northwestern European power system. The results of this paper can be used as a reference for understanding the effects of large-scale VSC-HVDC-connected offshore WPPs on the stability of the onshore interconnected power systems.

Numerical modeling of the proposed WFIRST-AFTA coronagraphs and their predicted performances

The WFIRST-AFTA 2.37 m telescope will provide the opportunity to host a coronagraph for the imaging and spectroscopy of planets and disks in the next decade. The telescope, however, is not ideal, given its obscured aperture. Only recently have coronagraph designs been thoroughly investigated that can efficiently work with this configuration. Three coronagraph designs, the hybrid Lyot, shaped pupil, and phase-induced amplitude apodization complex mask coronagraph have been selected for further development by the Astrophysics Focused Telescope Asset project. Real-world testbed demonstrations of these have just begun, so for now, the most reliable means of evaluating their potential performance comes from numerical modeling incorporating diffraction propagation, realistic system models, and simulated wavefront sensing and control. Here, we present the methods of performance evaluation and results for the current coronagraph designs.

Planning for Uncertainty and Fallbacks Can Increase the Number of Transplants in a Kidney-Paired Donation Program

A kidney-paired donation (KPD) pool consists of transplant candidates and their incompatible donors, along with nondirected donors (NDDs). In a match run, exchanges are arranged among pairs in the pool via cycles, as well as chains created from NDDs. A problem of importance is how to arrange cycles and chains to optimize the number of transplants. We outline and examine, through example and by simulation, four schemes for selecting potential matches in a realistic model of a KPD system; proposed schemes take account of probabilities that chosen transplants may not be completed as well as allowing for contingency plans when the optimal solution fails. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Donation, the simulations extend over 8 match runs, with 30 pairs and 1 NDD added between each run. Schemes that incorporate uncertainties and fallbacks into the selection process yield substantially more transplants on average, increasing the number of transplants by as much as 40% compared to a standard selection scheme. The gain depends on the degree of uncertainty in the system. The proposed approaches can be easily implemented and provide substantial advantages over current KPD matching algorithms.

Stochastic Distribution System Operation Considering Voltage Regulation Risks in the Presence of PV Generation

Variable over voltage, excessive tap counts, and voltage regulator (VR) runaway condition are major operational challenges in distribution network while accommodating generation from photovoltaics (PVs). The conventional approach to achieve voltage control based on offline simulation for voltage set point calculation does not consider forecast errors. In this work, a stochastic optimal voltage control strategy is proposed while considering load and irradiance forecast errors. Stochastic operational risks such as overvoltage and VR runaway are defined through a chance constrained optimization (CCO) problem. This classical formulation to mitigate runaway is further improved by introducing a stochastic index called the Tap Tail Expectation . Operational objectives such as power losses and excessive tap count minimization are considered in the formulation. A sampling approach is proposed to solve the CCO. Along with other voltage control devices, the PV inverter voltage support features are coordinated. The simulation study is performed using a realistic distribution system model and practically measured irradiance to demonstrate the effectiveness of the proposed technique. The proposed approach is a useful operational procedure for distribution system operators. The approach can minimize feeder power losses, avoid voltage violations, and alleviate VR runaway.

Paleoclimate Sampling as a Sensor Placement Problem

Abstract This study formulates the design of optimal observing networks for past surface climate conditions as the solution to a data assimilation problem, given a realistic proxy system model (PSM), paleoclimate observational uncertainties, and a network of current and proposed observing sites. The method is illustrated with the design of optimal networks of coral δ18O records, chosen among candidate sites, and used to jointly infer sea surface temperature (SST) and sea surface salinity (SSS) fields from the Community Climate System Model, version 4, last millennium simulation over the 1850–2005 period. It is shown that an existing paleo-observing network accounts for approximately 20% of the SST variance, and that adding 25 to 100 optimal pseudocoral sites would boost this fraction to 35%–52%. Characterizing the SST variance alone, or jointly with the SSS, leads to similar optimal networks, which justifies using coral δ18O records for SST reconstructions. In contrast, the network design for reconstructing SSS alone is fundamentally different, emphasizing the hydroclimatic centers of action of El Niño–Southern Oscillation. In all cases, network design depends strongly on the amplitude of the observational error, so replicates may be more beneficial than the exploration of new sites; these replicates tend to be chosen where proxies are already informative of the large-scale climate field(s). Finally, extensions to other types of paleoclimatic observations are discussed, and a path to operationalization is outlined.

Implementation of Health Monitoring System using Mixed Environment

Background: Research shows that the health care cost per capita have grown 2.4 percent faster than the gross domestic product (GDP) since 1970. The aim of this paper is to present a useful model of wireless system that can combine both hardware and software environments and it can also integrate with other technologies or infrastructure at a low cost, which can be used for the patient monitoring system. Methods: The biomedical sensor which is attached to the patient, will read analog data. The recorded data will be converted digitally by using Analog to Digital Converter (ADC) and a FPGA transmitter will be used to send this data to Phase Shift Keying (PSK) transmitter. The modulated data will be received by PSK receiver and another FPGA receiver will be used to get the data back on the system. For behavioural modelling Verilog hardware descriptive language is used to provide a high level abstraction and language constructions. And the Simulink software is used to provide a high-level mathematical modelling condition for digital communication system which can be used for the verification and algorithm development.The important modules implemented for the transmitter and receiver FPGA are bus interfacing, compression and the data framing. Findings: A short range wireless health monitoring wireless system is modelled by using a mixed software and hardware simulation environment.At all the stages of the hardware and software designs, different types of languages like Verilog HDL codes and MATLAB used to verify the operation of the modules. The behavioural HDL designed of the FPGA transmitter and receiver will be interfaced with the RF Simulink models of PSK transmitter and receiver by using System Generator (Sysgen) tool that acts as the converter simulator. A realistic design model of health monitoring system is implemented which can be used for future hardware design. Compression and framing are the two main operations used in the transmitter side. Data compression is implemented by Run-Length Encoding method and for data framing high data link control protocol has been used. The unique features of this models simulation are low cost, less complexity, low power dissipation and efficient data transmission. Finally the FPGA based healthcare system allows us to change the design configurations or up gradation of the system based on the requirements. Conclusion: In this paper distributed simulation approach is used for designing the health monitoring system which allows checking the specification of design at all the stages. Simulation by HDL and Simulink mixed models in not the objective of this work, but to prove that realistic design is possible for future health care system design.

PLC System Performance With AF Relaying

The use of repeaters (relays) has recently been introduced in power line communication (PLC) systems for long-distance data transfer and thus, it becomes important to analyze the performance of relay based PLC systems. A simplified system model with distance dependent signal attenuation and additive white Gaussian noise may not cover all the factors affecting the data transfer, such as variation in amplitude (fading) and occurrence of impulsive noise. Hence, a more realistic system model with log-normal fading, distance dependent signal attenuation, and a Bernoulli-Gaussian impulsive noise is considered in this paper to study the end-to-end average bit error rate (BER) and the end-to-end average channel capacity of a PLC system equipped with amplify-and-forward (AF) relays. Approximate closed-form expressions of the end-to-end average BER for binary phase-shift keying and the average channel capacity for high signal-to-noise ratio are obtained. The performance of the PLC system with AF relays is found to be superior compared to that of a direct transmission PLC system for fixed transmission power.

Dynamic TDD Support in Macrocell-Assisted Small Cell Architecture

Dynamic allocation of subframes to uplink (UL) or downlink (DL) in time division duplex (TDD), termed ‘Dynamic TDD,’ has been studied by the 3rd Generation Partnership Project (3GPP) since the Long Term Evolution (LTE) Release 11 timeframe. At the same time, 3GPP is also standardizing macrocell-assisted small cell heterogeneous architectures for inclusion in LTE Release 12 as a solution offering high data rate to user terminals (UEs) along with high system capacity through spatial reuse of spectrum. In this paper, we focus on a particular small cell architecture proposed by DOCOMO, known as the Phantom Cell architecture, which provides the option to support dynamic TDD. For an arbitrarily-located UE in a small cell network, we apply results from stochastic geometry to derive expressions for the distribution of DL signal to interference plus noise ratio (SINR) at an arbitrary UE and the distribution of UL SINR at its serving base station (BS). The analytical results are verified by system level simulations. These results can be used to study aspects of system design for small cells, and the sensitivity of SINR to the extent of synchronization across small cells employing dynamic TDD. In order to deal with the severe inter-cell interference (ICI) problem in dynamic TDD, we further propose a frequency domain interference coordination technique. Finally, system level simulations based on more realistic system models and assumptions are conducted to evaluate the performance of dynamic TDD systems and the proposed interference coordination technique.

Time slot assignment for convergecast in wireless sensor networks

Convergecast, which is essentially the inverse of broadcast, can be used for data collection in a wireless sensor network. This paper addresses the problem of convergecast in a wireless sensor network that uses time division multiplexing in order to schedule its node-to-node communication in a time-bounded manner. A realistic system model and problem for convergecast with minimum delay and minimum energy consumption is formulated for wireless sensor networks. Then, based on a detailed analysis of this problem, a heuristic solution based on time slot assignments is proposed. Simulation results are used to show that the proposed algorithm performs significantly better than alternative methods for this problem. The simulation results also show that the data delivery time of the proposed algorithm is close to the theoretical bound. Furthermore, total energy consumption is significantly reduced, when compared to the alternatives, due to the time slot assignment method used in the proposed algorithm.

Design of wide-area damping controllers using the block relative gain

A novel technique to determine the best pairing of inputs and outputs for the design of wide-area damping controllers (WADCs) is proposed. The method extends the conventional use of the relative gain array (RGA) for interacting control systems, to the block relative gain (BRG) to analyze interactions among multi-input multi-output (MIMO) controllers. First, geometric measures of controllability and observability are used to screen the most effective stabilizing signals for partially centralized control of large interconnected power systems. Then, the BRG analysis is used to quantify the potential for adverse interactions between a given set of controllers or subsystems. This gives candidate sets for supplementary controllers which are solved using linear matrix inequality (LMI) techniques and are evaluated in closed-loop mode to detect and quantify process interactions. In general, this approach also allows better coordination of control capabilities and the use of interaction measures to help in the choice of control location and structure. The effectiveness of the proposed control scheme on system behavior is tested on a realistic 5-area model of the Mexican interconnected power system.

Converter rating optimisation for a brushless doubly fed induction generator

This article studies the converter rating requirement of a Brushless doubly-fed induction generator (DFIG) for wind turbine applications. Practical constraints such as the generator torque-speed requirement, reactive power management and grid low-voltage ride-through (LVRT) are considered. Experimental data have been used to obtain a realistic system model of a Brushless DFIG in a wind turbine. The study shows that there is a minimum converter rating, dependant on operating point, but this may not be achievable without machine derating. The use of a capacitor bank enables the converter ratings to be reduced without compromising the machine's performance. The effect of the machine's leakage inductance on the interplay of LVRT, achievable system power factor, converter rating and losses is investigated.

Design of sliding mode and model reference adaptive control strategies for multivariable tape transport mechanism: a performance comparison

This paper presents sliding mode control and model reference adaptive control strategies for the tape transport mechanism. A nonlinear multivariable MIMO model of the process, consisting of take-up and supply reel servos for tape tension control and capstan servo for speed control is considered. The sliding mode control is applied for the nonlinear dynamic model of the process, while the model reference adaptive control deals with the linearized one. Moreover, in order to associate with the realistic model of system, design of controllers is accomplished with respect to parametric uncertainties. It is shown that both control strategies can guarantee asymptotic stability of the closed-loop system and tracking of desired outputs with the appropriate pace in the presence of uncertainties. Finally, simulation results demonstrate the effectiveness of the proposed controllers.

Any realistic model of a physical system must be computationally realistic

It is argued that any possible definition of a realistic physics theory – i.e., a mathematical model representing the real world – cannot be considered comprehensive unless it is supplemented with requirement of being computationally realistic. That is, the mathematical structure of a realistic model of a physical system must allow the collection of all the system's physical quantities to compute all possible measurement outcomes on some computational device not only in an unambiguous way but also in a reasonable amount of time.In the paper, it is shown that a deterministic quantum model of a microscopic system evolving in isolation should be regarded as realistic since the NP-hard problem of finding the exact solution to the Schrödinger equation for an arbitrary physical system can be surely solved in a reasonable amount of time in the case, in which the system has just a small number of degrees of freedom. In contrast to this, the deterministic quantum model of a truly macroscopic object ought to be considered as non-realistic since in a world of limited computational resources the intractable problem possessing that enormous amount of degrees of freedom would be the same as mere unsolvable.

Thermodynamic curvature for a two-parameter spin model with frustration.

Microscopic models of realistic thermodynamic systems usually involve a number of parameters, not all of equal macroscopic relevance. We examine a decorated (1+3) Ising spin chain containing two microscopic parameters: a stiff parameter K mediating the long-range interactions, and a sloppy J operating within local spin groups. We show that K dominates the macroscopic behavior, with varying J having only a weak effect, except in regions where J brings about transitions between phases through its conditioning of the local spin groups with which K interacts. We calculate the heat capacity C(H), the magnetic susceptibility χ(T), and the thermodynamic curvature R. For large |J/K|, we identify four magnetic phases: ferromagnetic, antiferromagnetic, and two ferrimagnetic, according to the signs of K and J. We argue that for characterizing these phases, the strongest picture is offered by the thermodynamic geometric invariant R, proportional to the correlation length ξ. This picture has correspondences to other cases, such as fluids.

Joint sensing and power allocation for hybrid spectrum sharing in fading channels

In a sensing-based hybrid spectrum sharing paradigm, cognitive radio first performs spectrum sensing to identify primary users’ states (idle/busy) and then adapts its transmit power according to sensing outcomes and channel conditions. To investigate the capacity of such systems in fading channels, existing works modelled fading channel in transmission phase while additive white Gaussian noise channel in spectrum sensing; however, sensing channels also exhibit fading characteristics in practice. Therefore a more realistic system model with channel fading in both sensing and transmission is considered in this study. Under the new system model, spectrum sensing and power allocation are coupled in the ergodic capacity and an equivalent decoupling processing is proposed via mathematical manipulations. Further, joint sensing and power allocation over Rayleigh fading is studied under average interference and transmit power constraints. The optimal and suboptimal schemes are obtained by alternating optimisation and Lagrangian dual method. Finally, system performance is evaluated via extensive numerical simulations.

A Multiscale Model for the Feto-placental Circulation in Monochorionic Twin Pregnancies

Abstract We developed a mathematical model of monochorionic twin pregnancies to simulate both the normal gestation and the Twin-Twin Transfusion Syndrome (TTTS), a disease in which the interplacental anastomose create a flow imbalance, causing one of the twin to receive too much blood and liquids, becoming hypertensive and polyhydramnios (the Recipient) and the other to become hypotensive and oligohydramnios (the Donor). This syndrome, if untreated, leads almost certainly to death one or both twins. We propose a compartment model to simulate the flows between the placenta and the fetuses and the accumulation of the amniotic fluid in the sacs. The aim of our work is to provide a simple but realistic model of the twins-mother system and to stress it by simulating the pathological cases and the related treatments, i.e. aminioreduction (elimination of the excess liquid in the recipient sac), laser therapy (removal of all the anastomoses) and other possible innovative therapies impacting on pressure and flow parameters.

Effect of Environmental Conditions on Single and Double Diode PV system : Comparative Study

In this paper, the single and double/bypass diode photovoltaic (PV) systems are designed in MATLAB/SimulinkGUI environment based on mathematical modeling of above PV systems. A comparative study of transient analysis for singleand double/bypass PV systems has been done with a resistive load. The effect of realistic conditions i.e. variable wind speedand irradiation level on single and double/bypass diode PV system is investigated, which shows the satisfactory performancefor realistic model of PV system.

Near-optimal decoding of transient stimuli from coupled neuronal subpopulations.

Coupling between sensory neurons impacts their tuning properties and correlations in their responses. How such coupling affects sensory representations and ultimately behavior remains unclear. We investigated the role of neuronal coupling during visual processing using a realistic biophysical model of the vertical system (VS) cell network in the blow fly. These neurons are thought to encode the horizontal rotation axis during rapid free-flight maneuvers. Experimental findings suggest that neurons of the VS are strongly electrically coupled, and that several downstream neurons driving motor responses to ego-rotation receive inputs primarily from a small subset of VS cells. These downstream neurons must decode information about the axis of rotation from a partial readout of the VS population response. To investigate the role of coupling, we simulated the VS response to a variety of rotating visual scenes and computed optimal Bayesian estimates from the relevant subset of VS cells. Our analysis shows that coupling leads to near-optimal estimates from a subpopulation readout. In contrast, coupling between VS cells has no impact on the quality of encoding in the response of the full population. We conclude that coupling at one level of the fly visual system allows for near-optimal decoding from partial information at the subsequent, premotor level. Thus, electrical coupling may provide a general mechanism to achieve near-optimal information transfer from neuronal subpopulations across organisms and modalities.

Optimizing the Energy Efficiency of Electric Transportation Systems Operation Using a Genetic Algorithm

Energy consumption of a rail transit system depends on many parameters. One of the most effective methods of reducing energy consumption in a rail transit system is optimizing the speed profile of the trains along the route. A genetic algorithm (GA) based approach is proposed to search for the optimal train speed trajectory, given a journey time constraint, and its effectiveness is shown by simulation results. The proposed approach includes realistic system modeling using an integrated electromechanical simulation model to calculate train energy consumption and travelling time under different operating conditions, inter-station distances, track profiles.

Triple‐step method to design non‐linear controller for rail pressure of gasoline direct injection engines

The precise control of rail pressure in gasoline direct injection (GDI) engines is considered as an important issue. This study presents a novel approach for rail pressure control of GDI engines. The control objective is to make the rail pressure track a given reference. Different from the existing non-linear controller design methods, the proposed method can be formalised as a triple-step procedure: (i) a steady-state control is deduced, playing the similar role of the map-based control strategy widely used in automotive control; (ii) a feed-forward control is derived concerning the variation of the tracking reference; and (iii) the previous two steps result in an explicit and affine expression of the tracking error dynamics, based on that a non-linear error feedback can be easily designed for enhancing the closed-loop performance and rearranged into a state-dependent PID. The structure of the designed non-linear controller is concise and is comparable to those widely used in modern automotive control. In addition, this procedure provides a concise design process so that the derivation of the control law is simplified and straightforward. A guideline of the control parameters tuning is given based on robustness analysis. Finally, the simulation results in the environment of AMESim with a realistic common rail injection system model show the efficiency of the proposed approach.