Three-phase optimal power flow for smart grids by iterative nonsmooth optimization

© 2017 by SCITEPRESS Science and Technology Publications, Lda. All Rights Reserved. Optimal power flow is important for operation and planning of smart grids. The paper considers the so called unbalanced thee-phase optimal power flow problem (TOPF) for smart grids, which involves multiple quadratic equality and indefinite quadratic inequality constraints to model the bus interconnections, hardware capacity and balance between power demand and supply. The existing Newton search based or interior point algorithms are often trapped by a local optimum while semidefinite programming relaxation (SDR) even fails to locate a feasible point. Following our previously developed nonsmooth optimization approach, computational solution for TOPF is provided. Namely, an iterative procedure for generating a sequence of improved points that converges to an optimal solution, is developed. Simulations for TOPF in unbalanced distributed networks are provided to demonstrate the practicability and efficiency of our approach

Heart rate control during treadmill exercise

A computer-controlled treadmill and related data collection and processing systems have been developed for the control of heart rate during treadmill exercise. Minimizing deviations of heart rate from a preset profile is achieved by controlling the speed and/or the gradient of the treadmill. A simple and practical heart rate measurement algorithm has been developed to robustly measure the variations of heart rate. Both conventional Proportional-Integral- Derivative (PID) control and fuzzy Proportional-Integral (PI) control approaches have been employed for the controller design. The fuzzy Proportional-Integral algorithm achieved better heart rate tracking performance. Finally, a heart rate based exercising protocol was successfully implemented on the newly designed exercise system. © 2005 IEEE

Oxygen uptake estimation in humans during exercise using a Hammerstein model

This paper aims to establish a block-structured model to predict oxygen uptake in humans during moderate treadmill exercises. To model the steady state relationship between oxygen uptake (oxygen consumption) and walking speed, six healthy male subjects walked on a motor driven treadmill with constant speed from 2 to 7 km/h. The averaged oxygen uptake at steady state (VO 2) was measured by a mixing chamber based gas analysis and ventilation measurement system (AEI Moxus Metabolic Cart). Based on these reliable date, a nonlinear steady state relationship was successfully established using Support Vector Regression methods. In order to capture the dynamics of oxygen uptake, the treadmill velocity was modulated using a Pseudo Random Binary Signal (PRBS) input. Breath by breath analysis of all subjects was performed. An ARX model was developed to accurately reproduce the measured oxygen uptake dynamics within the aerobic range. Finally, a Hammerstein model was developed, which may be useful for implementing a control system for the regulation of oxygen uptake during treadmill exercises. © 2007 Biomedical Engineering Society

Estimation of oxygen consumption for moderate exercises by using a hammerstein model

This paper aims to establish block-structured nonlinear model (Hammerstein model) to predict oxygen uptake during moderate treadmill exercises. In order to model the steady state relationship between oxygen uptake (oxygen consumption) and walking speed, six healthy male subjects walked on a motor driven treadmill at six different speed (2,3,4,5,6, and 7 km/h). The averaged oxygen uptake of exercisers at steady state was measured by a mixing chamber based gas analyzer(AEI Moxus Metabolic Cart). Based on these reliable experiment data, a nonlinear static function was obtained by using Support Vector Regression. In order to capture the dynamics of oxygen uptake, a suitable Pseudo Random Binary Signal (PRBS) input was designed and implemented on a computer controlled treadmill. Breath by breath analysis of all exercisers' dynamic responses (PRBS responses) to treadmill walking was performed. A useful ARX model is identified to justify the measured oxygen uptake dynamics within the aerobic range. Finally, a Hammerstein is achieved, which is useful for the control system design of oxygen uptake regulation during treadmill exercises. © 2006 IEEE

Modeling of a gas concentration measurement system

Energy expenditure can be calculated via measurement of oxygen consumption and carbon dioxide production. Precise measurement of expired gas concentrations and volume is required for this determination. For a given gas concentration measurement system, the establishment of a model is a good way to effectively use the equipments and achieve more accurate energy expenditure calculations. This paper proposes a simple but effective approach for the modeling of a gas concentration measurement system. © 2005 IEEE

Multiple matrix rank constrained optimization for optimal power flow over large scale transmission networks

© Copyright 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. The optimal power flow (OPF) problem for power transmission networks is an NP-hard optimization problem with numerous quadratic equality and indefinite quadratic inequality constraints on bus voltages. The existing nonlinear solvers often fail in yielding a feasible solution. In this paper, we follow our previously developed nonsmooth optimization approach to address this difficult large-scale OPF problem, which is an iterative process to generate a sequence of improved solutions that converge to an optimal solution. Each iteration calls an SDP of a moderate dimension. Intensive simulations for OPF over networks with a large number of buses are provided to demonstrate the efficiency of our approach

A nonlinear dynamic model for heart rate response to treadmill walking exercise

A dynamic model of the heart rate response to treadmill walking exercise is presented. The model is a feedback interconnected system; the subsystem in the forward path represents the neural response to exercise, while the subsystem in the feedback path describes the peripheral local response. The parameters of the model were estimated from 5 healthy adult male subjects, each undertaking 3 sets of walking exercise at different speeds. Simulated responses from the model closely match the experimental data both in the exercise and the recovery phases. The model will be useful in explaining the cardiovascular response to exercise and in the design of exercise protocols for individuals. © 2007 IEEE

Universal algorithm for exercise rate estimation in walking, cycling and rowing using triaxial accelerometry

A technique that can reliably monitor exercise intensity plays an important role for the effectiveness and safety of an exercise prescription. A universal algorithm for the recursive estimation of exercise rate during a variety of aerobic exercises using measurements from a body-mounted triaxial accelerometer (TA) is proposed. Information about the type of exercise is not required by the algorithm and the TA can be mounted at the same location regardless of the exercise type. The algorithm involves period detection and data fusion. Experimental results demonstrate that the algorithm is effective for common aerobic exercises. © The Institution of Engineering and Technology 2009

Estimation of walking energy expenditure by using support vector regression

This paper develops a new predictor of walking energy expenditure from wireless measurements of body movements using triaxial accelerometers. Reliable data were collected from repeated walking experiments in different conditions on a treadmill with simultaneous measurement of expired oxygen and carbon dioxide. Support vector regression, a powerful non-linear regression method, was used to process and model the data. This novel processing method sets this investigation apart from existing papers. Good results were achieved in the robust estimation of walking related energy expenditure from a number of variables derived from triaxial accelerometer and treadmill speed. ©2005 IEEE

Identification and control for heart rate regulation during treadmill exercise

This paper proposes a novel integrated approach for the identification and control of Hammerstein systems to achieve desired heart rate profile tracking performance for an automated treadmill system. For the identification of Hammerstein systems, the pseudorandom binary sequence input is employed to decouple the identification of dynamic linear part from input nonlinearity. The powerful ε-insensitivity support vector regression method is adopted to obtain sparse representations of the inverse of static nonlinearity in order to obtain an approximate linear model of the Hammerstein system. An H ∞ controller is designed for the approximated linear model to achieve robust tracking performance. This new approach is successfully applied to the design of a computer-controlled treadmill system for the regulation of heart rate during treadmill exercise. Minimizing deviations of heart rate from a preset profile is achieved by controlling the speed of the treadmill. Both conventional proportional-integral-derivative (PID) control and the proposed approaches have been employed for the controller design. The proposed algorithm achieves much better heart rate tracking performance. © 2007 IEEE