Predictive Optimal Matrix Converter Control for a Dynamic Voltage Restorer with Flywheel Energy Storage

This paper presents a predictive optimal matrix converter controller for a flywheel energy storage system used as Dynamic Voltage Restorer (DVR). The flywheel energy storage device is based on a steel seamless tube mounted as a vertical axis flywheel to store kinetic energy. The motor/generator is a Permanent Magnet Synchronous Machine driven by the AC-AC Matrix Converter. The matrix control method uses a discrete-time model of the converter system to predict the expected values of the input and output currents for all the 27 possible vectors generated by the matrix converter. An optimal controller minimizes control errors using a weighted cost functional. The flywheel and control process was tested as a DVR to mitigate voltage sags and swells. Simulation results show that the DVR is able to compensate the critical load voltage without delays, voltage undershoots or overshoots, overcoming the input/output coupling of matrix converters.

Tools for testing the Solvency Capital Requirement for life insurance

Longevity risk is one of the major risks that an insurance company or a pension fund has to deal with and it is expected that its importance will grow in the near future. In agreement with these considerations, in Solvency II regulation the Standard formula furnished for calculating the Solvency Capital Requirement explicitly considers this kind of risk. According to the new European rules in our paper we suggest a multiperiod approach to evaluate the SCR for longevity risk. We propose a backtesting framework for measuring the consistency of SCR calculations for life insurance policies.

Fast optimum-predictive control and capacitor voltage balancing strategy for bipolar back-to-back NPC converters in high-voltage direct current transmission systems

Multilevel power converters have been introduced as the solution for high-power high-voltage switching applications where they have well-known advantages. Recently, full back-to-back connected multilevel neutral point diode clamped converters (NPC converter) have been used inhigh-voltage direct current (HVDC) transmission systems. Bipolar-connected back-to-back NPC converters have advantages in long-distance HVDCtransmission systems over the full back-to-back connection, but greater difficulty to balance the dc capacitor voltage divider on both sending and receiving end NPC converters. This study shows that power flow control and dc capacitor voltage balancing are feasible using fast optimum-predictive-based controllers in HVDC systems using bipolar back-to-back-connected five-level NPC multilevel converters. For both converter sides, the control strategytakes in account active and reactive power, which establishes ac grid currents in both ends, and guarantees the balancing of dc bus capacitor voltages inboth NPC converters. Additionally, the semiconductor switching frequency is minimised to reduce switching losses. The performance and robustness of the new fast predictive control strategy, and its capability to solve the DC capacitor voltage balancing problem of bipolar-connected back-to-back NPCconverters are evaluated.

HVDC transmission systems: Bipolar back-to-back diode clamped multilevel converter with fastoptimum-predictive control and capacitor balancing strategy

Voltage source multilevel power converter structures are being considered for high power high voltage applications where they have well known advantages. Recently, full back-to-back connected multilevel neutral diode clamped converters (NPC) have been used in high voltage direct current (HVDC) transmission systems. Bipolar back-to-back connection of NPCs have advantages in long distance HVDC transmission systems, but highly increased difficulties to balance the dc capacitor voltage dividers on both sending and receiving end NPCs. This paper proposes a fast optimum-predictive controller to balance the dc capacitor voltages and to control the power flow in a long distance HVDCsystem using bipolar back-to-back connected NPCs. For both converter sides, the control strategy considers active and reactive power to establish ac grid currents on sending and receiving ends, while guaranteeing the balancing of both NPC dc bus capacitor voltages. Furthermore, the fast predictivecontroller minimizes the semiconductor switching frequency to reduce global switching losses. The performance and robustness of the new fast predictive control strategy and the associated dc capacitors voltage balancing are evaluated. (C) 2011 Elsevier B.V. All rights reserved.

Distributed Model Predictive Control for Housing with Hourly Auction of Available Energy

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

Análise por ultra-sons no controlo de condição

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Inverse dynamics based predictive control for unified power flow controllers without DC bus

This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

Evaluation of the influence of testing parameters on the melt flow index of thermoplastics

The main goals of the present work are the evaluation of the influence of several variables and test parameters on the melt flow index (MFI) of thermoplastics, and the determination of the uncertainty associated with the measurements. To evaluate the influence of test parameters on the measurement of MFI the design of experiments (DOE) approach has been used. The uncertainty has been calculated using a "bottom-up" approach given in the "Guide to the Expression of the Uncertainty of Measurement" (GUM). Since an analytical expression relating the output response (MFI) with input parameters does not exist, it has been necessary to build mathematical models by adjusting the experimental observations of the response variable in accordance with each input parameter. Subsequently, the determination of the uncertainty associated with the measurement of MFI has been performed by applying the law of propagation of uncertainty to the values of uncertainty of the input parameters. Finally, the activation energy (Ea) of the melt flow at around 200 degrees C and the respective uncertainty have also been determined.

On performance of distributed model predictive control in power system frequency regulation

This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).

Confronting predictive texture zeros in lepton mass matrices with current data

Several popular Ansatze of lepton mass matrices that contain texture zeros are confronted with current neutrino observational data. We perform a systematic chi(2) analysis in a wide class of schemes, considering arbitrary Hermitian charged-lepton mass matrices and symmetric mass matrices for Majorana neutrinos or Hermitian mass matrices for Dirac neutrinos. Our study reveals that several patterns are still consistent with all the observations at the 68.27% confidence level, while some others are disfavored or excluded by the experimental data. The well-known Frampton-Glashow-Marfatia two-zero textures, hybrid textures, and parallel structures (among others) are considered.

Viscosity and self-diffusion coefficients of dialkyl adipates: a correlation scheme with predictive capabilities

A correlation and predictive scheme for the viscosity and self-diffusivity of liquid dialkyl adipates is presented. The scheme is based on the kinetic theory for dense hard-sphere fluids, applied to the van der Waals model of a liquid to predict the transport properties. A "universal" curve for a dimensionless viscosity of dialkyl adipates was obtained using recently published experimental viscosity and density data of compressed liquid dimethyl (DMA), dipropyl (DPA), and dibutyl (DBA) adipates. The experimental data are described by the correlation scheme with a root-mean-square deviation of +/- 0.34 %. The parameters describing the temperature dependence of the characteristic volume, V-0, and the roughness parameter, R-eta, for each adipate are well correlated with one single molecular parameter. Recently published experimental self-diffusion coefficients of the same set of liquid dialkyl adipates at atmospheric pressure were correlated using the characteristic volumes obtained from the viscosity data. The roughness factors, R-D, are well correlated with the same single molecular parameter found for viscosity. The root-mean-square deviation of the data from the correlation is less than 1.07 %. Tests are presented in order to assess the capability of the correlation scheme to estimate the viscosity of compressed liquid diethyl adipate (DEA) in a range of temperatures and pressures by comparison with literature data and of its self-diffusivity at atmospheric pressure in a range of temperatures. It is noteworthy that no data for DEA were used to build the correlation scheme. The deviations encountered between predicted and experimental data for the viscosity and self-diffusivity do not exceed 2.0 % and 2.2 %, respectively, which are commensurate with the estimated experimental measurement uncertainty, in both cases.