Lyne Woodward

Experimental Investigation on a Hybrid Series Active Power Compensator to Improve Power Quality of Typical Households

In this paper, a transformerless hybrid series active filter using a sliding-mode control algorithm and a notch harmonic detection technique are implemented on a single-phase distribution feeder. This method provides compensation for source current harmonics coming from a voltage fed type of nonlinear load (VSC) and reactive power regulation of a residential consumer. The realized active power filter enhances the power quality while cleaning the point of common coupling (PCC) from possible voltage distortions, sags, and swells initiated through the grid. Furthermore, to overcome drawbacks of real-time control delay, a computational delay compensation method, which accurately generates reference voltages, is proposed. Based on an improved compensation strategy, while the grid current remains clean even with a small compensation gain, voltage disturbances initiated by the power system are obstructed by the compensator, and the PCC became free of voltage harmonics and protected from sag and swell. Simulation and experimental results carried on a 1.6-kVA prototype are presented and discussed.

Maximizing wind energy production with the multi-unit optimization method

Nowadays, wind energy is becoming an attractive source of clean energy. However, this type of power source is subject to power reductions due to losses in wind energy conversion system and to frequently changes in wind velocity. Many researches are turning to develop real-time power optimization techniques in order to maximize wind power production. In this paper, the multi-unit optimization method is used to maximize in real-time the power of a wind energy conversion system (WECS) composed of two wind turbines with permanent magnet synchronous generators (PMSG). The performance of the proposed method is compared to the one obtained from the application of the perturbation-observation (PO) method. The simulation results show a faster convergence of the multi-unit optimization method to the optimal operational point without any oscillation around this point. The multi-unit optimization method also showed a better response than the PO method to rapid changes in wind velocity.

Extremum-seeking control with anticipative action of microbial fuel cell's power

During the last decade, the microbial fuel cell (MFC) has been considered as a promising solution to produce renewable energy while reducing the excessive consumption of electrical energy in wastewater treatment centers. One of the problems facing the use of an MFC as a battery is the fact that its internal resistance varies with various external sources of disturbances causing a variation in its optimal point of operation. In this case the use of a real-time optimization method is necessary for the battery to work at its optimum. Extremum seeking control (ESC) can be applied to optimize the system. However, in the case where important external disturbances cause rapid changes in the optimal operating point, ESC converges to a point other than the desired optimum because of its very slow convergence rate. In this paper, a method which judiciously combines an ESC routine with a neural-network based anticipatory action is proposed. The anticipatory action takes into account a measurable external disturbance, namely the inlet substrate concentration. Simulation results show that the proposed scheme leads to an improvement of the convergence rate towards the desired optimum.

An improved maximum power extraction scheme for microbial fuel cells

Microbial fuel cell (MFC) is a recent technology of producing bioelectricity from wastewater by using bacteria as catalyst in the oxydo-reduction reaction. Because of the biological nature of MFC, the level of delivered electrical power is greatly affected by the operating conditions. In order to extract the maximum produced power, extremum-seeking control (ESC) methods are used to keep MFC working at its optimal operating point. As the ESC scheme is based on a feedback control loop, its performance can be limited in presence of high frequency disturbances. In this paper a method is proposed to improve the performance of the well-known perturbation method in presence of frequent variations of the inlet substrate concentration which is considered here as a disturbance for the MFC.

Extremum-seeking control of a microbial fuel cell power using adaptive excitation

Microbial fuel cell (MFC) is a novel bio-renewable energy source, whose maximum produced power is, like most other renewable energy sources (photovoltaic panels, wind turbines, etc.) highly dependent on external disturbances. Hence, an appropriate real-time optimization method should be used so that the MFC always operates at its optimum. Extremum-seeking control (ESC) can be applied to optimize this type of system. However, when the optimal operating point of the MFC varies very fast due to external disturbances, the slow convergence of the ESC induces a lack of precision in the tracking of the optimal power point. In this paper, it is proposed to use adaptive excitation signal amplitude in the ESC scheme to improve the precision of the tracking. The amplitude adaptation is performed using a neural-network (NN) model which estimates in real-time the error between the optimal and the actual point of operation of the MFC based on the external disturbance measurements. The improved ESC performance in terms of convergence speed and precision will be demonstrated at the level of simulation in the case of a comparative study between classic ESC and ESC with adaptive excitation applied to an MFC model subject to variations of a measurable external disturbance, namely, the inlet substrate concentration.

Real-Time Implementation of a Three-Phase THSeAF Based on a VSC and a P+R Controller to Improve the Power Quality of Weak Distribution Systems

This paper proposes a novel three-phase transformerless hybrid series active filter (THSeAF) based on voltage-fed type of converters (VSCs) to address major power quality issues related to residential and commercial buildings. This power quality compensator presents an affordable solution to overcome current-related issues as well as integrating renewables to ensure a sustainable supply to the loads. The controller is based on a novel combination of the synchronous reference frame and pq theory to extract voltage and current harmonics as well as voltage unbalances. A proportional resonant (P+R) regulator is producing gate switching signals for the three-phase THSeAF. The generated duty-cycle waveforms will produce compensating voltage to rectify harmonic currents initiated from typical nonlinear loads. The device ensures a reliable and dynamically restored power supply on the loads point of common coupling by means of three auxiliary dc supplies. This paper describes mitigation of power-quality-related issues of a microgrid systems and smart distribution grids along with the proposed solution to enhance the power system performances. A combination of simulations and experimental laboratory results are carried out to validate the study.

A new approach to Particle Swarm Optimization for dynamic systems with multiple units

Maximum Power Point Trackers (MPPT) are widely used to track in real-time the optimal power output of dynamic systems. These systems are sometimes comprised of multiple units which are similar, but not necessarily identical in terms of power curve and dynamics. A good example of such a system would be a photovoltaic (PV) array, which consists of multiple PV cells. Hence, it can be more profitable to operate each unit to its own optimal operating point instead of operating the whole system to a common optimal operating point. This paper proposes to use Particle Swarm Optimization (PSO) as an MPPT where each particle is assigned to a unit of a system. Although the method is validated both through simulations of a PV model and experimentations using a test bench of PV cells, it can be applied to many different dynamic systems comprising multiple units. The method proved to improve the convergence rate of the system and its total power production.