Single-chip inverter for active filters

Generally inverter-based active filters, which employ pulse-width-modulated (PWM) techniques, use microprocessors for overall control and discrete logic for the generation of switching patterns. Because of the complexity of control required, discrete logic circuits tend to have a very high component count, making system design inflexible, expensive and less reliable than integrated circuit implementation. The work reported here presents a novel design of a single-chip controlled PWM inverter-based active filter, which addresses these issues

A new control technique for active power filters using a combined genetic algorithm/conventional analysis

In this paper, the computational problems associated with the optimization techniques used to evaluate the switching patterns for controlling variable-characteristics active power filters are presented and critically analyzed. Genetic algorithms (GAs) are introduced in this paper to generate a fast and accurate initial starting point in the highly nonlinear optimization space of mathematical optimization techniques. GAs tend to speed up the initialization process by a factor of 13. A combined GA/conventional technique is also proposed and implemented to reduce the associated computational burden associated with the control and, consequently, increasing the speed of response of this class of active filters. Comparisons of these techniques are discussed and presented in conjunction with simulation and practical results for the filter operation

Variable var compensator circuits

A family of two reactive-power compensator circuit is presented. A general model of some basic linear elements and switching function blocks is developed first. Then the two proposed compensator circuits are derived from the generalised model. The proposed circuits are capable of supplying leading as well as lagging reactive currents in stepless variation without using an inverter configuration. The switching frequency is in the range of 2.5 kHz and the largest capacitor utilised does not exceed 60 muF. The generated reactive current, in either the leading or lagging modes, contains less than 2% total harmonic distortio

A new configuration for shunt active power filters

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis presents a new power circuit configuration to be used in shunt active power filters. A new control algorithm based on the linear voltage control suitable for the proposed circuit is introduced. The system is analysed both in time and frequency domains. The practical implementation of the system proves its suitability for the proposed task. The switching frequency of the proposed circuit is much lower than that in other active filters. The switching losses are then considerably reduced, in addition to the fact that the switching devices can withstand larger values of currents being switched on and off at lower frequencies which is an advantage to this circuit. The component sizes (capacitors and inductors) in the proposed circuit are also much smaller than those in other filter configurations. In addition, the thesis presents a new method for categorising the active filter systems proposed in the surveyed literature. The survey includes a comparison of these techniques showing their respective merits and drawbacks. The thesis also includes an implementation of a reference current generator that is suitable for single-phase applications without the need for excessive computations. The technique involves a modified Fourier analysis, which is suitable for active filtering applications

Design and implementation of a modified fourier analysis harmonic current computation technique for power active filters using DSPs

The design and implementation of a harmonic current computation technique based on a modified Fourier analysis, suitable for active power filters incorporating DSPs is presented. The proposed technique is suitable for the monitoring and control of load current harmonics for real-time applications. The derivation of the basic equations based on the proposed technique and the system implementation using the Analogue Devices SHARC processor are presented. The steady state and dynamic performance of the system are evaluated for a range of loading conditions

Regeneración natural y restauración de la zona afectada por el gran incendio del Bages y Berguedà de 1994

Consultable des del TDXTítol obtingut de la portada digitalitzadaEn esta tesis se ha estudiado la capacidad regenerativa post-incendio de Pinus halepensis, Pinus nigra y Pinus sylvestris . En concreto se han desarrollado las siguientes actividades: i) hemos estudiado la tolerancia de las semillas a diferentes temperaturas y tiempo de exposición, dependiendo de la posición de la semilla durante el fuego (semillas dentro las piñas frente a semillas libres). La fenología de la liberación de las semillas y los efectos de la severidad del fuego en abrir las piñas y la germinación de las semillas contribuyen a explicar el éxito de la regeneración de P. halepensis, y el fracaso de P. nigra y P. sylvestris después del fuego; ii) Hemos evaluado el patron de regeneración post-incendio de Pinus halepensis, P. nigra y P. sylvestris tres años después de un incendio en un gran área quemada. P. halepensis muestra una elevada densidad post-incendio de plántulas, mientras que P. nigra y P. sylvestris casi desaparecen en las parcelas quemadas. Con un modelo sucesional predecimos que 77-93% de parcelas dominadas por estos dos pinos cambian después del fuego a bosques de Quercus o matoral. iii) Hemos explorado la respuesta al pastoreo de dos Quercus Mediterráneos, Q. ilex (perenne) y Q cerrioides (caducifolio) en una área afectada por un gran incendio. Los resultados obtenidos indican que ninguna de la dos especie de Quercus fueron favorecidas por el pastoreo en términos de mortalidad de individuos, morfología de la planta y crecimiento. iv) Hemos explorado los patrones de rebrote y la respuesta a diferentes intensidades de resalveo y poda de estas especies mediterráneas de Quercus que coexisten en extensas zonas aparecidas después de grandes incendios. Según nuestros resultados, ambas especies han rebrotado vigorosamente después del fuego en las diferentes condiciones estudiadas, con una influencia importante del tamaño del individuo, al resalvear los individuos aumentó el crecimiento en altura y diámetro basal, con unas diferencias bajas entre las dos intensidades de aclareo. v) En el último estudio, hemos analizado los diferentes tipos de eliminación de la vegetación, la preparación de suelo y métodos de reforestación para restaurar bosques de P. nigra. Hemos comparado estas prácticas en términos de establecimiento de plantas, pero también en el marco de sus costes económicos y el impacto ecológico, mediante un análisis multicriterial. Este análisis reveló la opción preferida ha sido la plantación lineal en áreas sin eliminación de vegetación o ligeramente pastoreadas.In this work we study the post-fire regenerative ability of Pinus halepensis, Pinus nigra and Pinus sylvestris, in the framework of the following activities: i) We have studied seed tolerance to different temperatures and times of exposure, and depending on seed position during the fire event (seeds inside cones versus free seeds) . The seeding phenology and the effects of fire severity on cone opening and seed germination contribute to explain the successful regeneration of P. halepensis, and the failure of P. nigra and P. sylvestris after fire. ii) We have evaluated the post-fire regeneration pattern of Pinus halepensis, P. nigra and P. sylvestris three years after fire in a large burned area. P. halepensis shows high seedling density after fire, but P. nigra and P. sylvestris almost disappear from burned plots. With a succession model we predict that 77-93% of plots dominated by these two pines change after fire to oak woodlands or shrublands. iii) We have explored the response to grazing of two co-occurring Mediterranean oaks, the evergreen Quercus ilex and the deciduous Quercus cerrioides in an area affected by a large wildfire. The results obtained indicate that neither of the two Quercus species was favoured by browsing in terms of mortality of individuals, plant structure and growth. iV) We explore the resprouting patterns and the response to different intensities of stool cleaning and pruning of these co-occurring Mediterranean oak species in mixed extensive coppices which have appeared after large wildfires According to our results, both species resprouted vigorously after fire in the different environmental conditions studied, with an important influence of the size of the stool, while cleaning of stools increased height and basal diameter growth, with low differences between the two cleaning intensities. V) In the last study, we have analyzed different types of vegetation, soil preparation and reforestation methods to restore P. nigra forests. We have compared these practices in terms of seedling establishment, but also in the light of their economic costs and ecological impact, through a new multi-criteria analysis. This analysis revealed that the two most preferred options were planting in uncleared or lightly grazed areas with soil preparation through ripping

New mathematical model for analysing three-phase controlled rectifier using switching functions

This paper is a postprint of a paper submitted to and accepted for publication in IET Power Electronics and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.The aim of this study is to present a set of closed-form analytical equations in order to enable the computation of the three-phase bridge rectifier steady-state performance estimation. The proposed method presented in this study is a fast, accurate and effective mathematical model for analysing three-phase full-wave controlled rectifiers. The steady-state mathematical model is based on the derivation of an appropriate set of switching functions using the general switching matrix circuit (GSMC) techniques. Once the switching functions are derived, the output current, input current and output dc voltage can all be easily derived and generated from the application of this technique. The effect of overlap is accurately modelled and the distortion (notches), frequency content on the input (voltage and current) and output voltage distortion are derived. The proposed mathematical model, unlike conventional analytical methods, can be integrated in the design of active filters. Furthermore, the output voltage reduction, the rms, average and peak values of voltages and currents for the thyristors and any other semiconductor devices used are readily available for the designer by direct substitution into closed-form equations without any need for the waste of time for worst-case scenario simulations. This method can also be applied to other types of converters, specifically to all voltage fed power converters

Smart Electric Grids Three-Phase Automatic Load Balancing Applications using Genetic Algorithms

Smart power grid is going to be the future grid. Conventional, renewable and alternate sources incorporating for power generation[1]. Smart Electrical Grids require nowadays a large interest in the electrical load distribution balancing problem.  This problem is a well known for not having an optimal solution for large-scale systems, where the number of single phase consumers connected to three phase systems increases especially in very large-scale electrical distribution systems.  This paper presents a new control technique for an automatic circuit phase change as well as an optimisation approach using Genetic Algorithms (GA) used to enhance the solution of electrical load distribution balancing problem.  In the first part of the paper, the system under study is introduced, as well as the various solutions adopted.  In the second part of the paper, a GA formulation and implementation of the solution is presented.  The efficiency of the GA solution is also discussed

Customer active power consumption prediction for the next day based on historical profile

Energy consumption prediction application is one of the most important fieldsthat is artificially controlled with Artificial Intelligence technologies to maintainaccuracy for electricity market costs reduction. This work presents a way to buildand apply a model to each costumer in residential buildings. This model is built by using Long Short Term Memory (LSTM) networks to address a demonstration of time-series prediction problem and Deep Learning to take into consideration the historical consumption of customers and hourly load profiles in order to predict future consumption. Using this model, the most probable sequence of a certain industrial customer’s consumption levels for a coming day is predicted. In the case of residential customers, determining the particular period of the prediction in terms of either a year or a month would be helpful and more accurate due to changes in consumption according to the changes in temperature and weather conditions in general. Both of them are used together in this research work to make a wide or narrow prediction window.A test data set for a set of customers is used. Consumption readings for anycustomer in the test data set applying LSTM model are varying between minimum and maximum values of active power consumption. These values are always alternating during the day according to customer consumption behavior. This consumption variation leads to leveling all readings to be determined in a finite set and deterministic values. These levels could be then used in building the prediction model. Levels of consumption’s are modeling states in the transition matrix. Twenty five readings are recorded per day on each hour and cover leap years extra ones. Emission matrix is built using twenty five values numbered from one to twenty five and represent the observations. Calculating probabilities of being in each level (node) is also covered. Logistic Regression Algorithm is used to determine the most probable nodes for the next 25 hours in case of residential or industrial customers.Index Terms—Smart Grids, Load Forecasting, Consumption Prediction, Long Short Term Memory (LSTM), Logistic Regression Algorithm, Load Profile, Electrical Consumption.</p