Analysis and compensation of power amplifier nonlinearity in MIMO transmit diversity systems

The nonlinearity of high-power amplifiers (HPAs) has a crucial effect on the performance of multiple-input-multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (OSTBC) systems in the presence of nonlinear HPAs. Specifically, we propose a constellation-based compensation method for HPA nonlinearity in the case with knowledge of the HPA parameters at the transmitter and receiver, where the constellation and decision regions of the distorted transmitted signal are derived in advance. Furthermore, in the scenario without knowledge of the HPA parameters, a sequential Monte Carlo (SMC)-based compensation method for the HPA nonlinearity is proposed, which first estimates the channel-gain matrix by means of the SMC method and then uses the SMC-based algorithm to detect the desired signal. The performance of the MIMO-OSTBC system under study is evaluated in terms of average symbol error probability (SEP), total degradation (TD) and system capacity, in uncorrelated Nakagami-m fading channels. Numerical and simulation results are provided and show the effects on performance of several system parameters, such as the parameters of the HPA model, output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, modulation order of quadrature amplitude modulation (QAM), and number of SMC samples. In particular, it is shown that the constellation-based compensation method can efficiently mitigate the effect of HPA nonlinearity with low complexity and that the SMC-based detection scheme is efficient to compensate for HPA nonlinearity in the case without knowledge of the HPA parameters.

On the effect of power amplifier nonlinearity on MIMO transmit diversity systems

Nonlinearity of high-power amplifier (HPA) plays a crucial role in the performance of multiple-input multiple-output (MIMO) systems. In this paper, we investigate the performance of MIMO orthogonal space-time block coding (STBC) systems in the presence of nonlinear HPA. Specifically, we assess the impact of HPA nonlinearity on the average symbol error probability (SEP), total degradation (TD), and system capacity of orthogonal STBC in uncorrelated Nakagami-m fading channels. Numerical results are provided and show the effects of several system parameters, such as the output back-off (OBO) of nonlinear HPA, numbers of transmit and receive antennas, and modulation order of quadrature amplitude modulation (QAM), on performance.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Optimal power management strategy for energy storage with stochastic loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.

Annual CO-emissions of combined pellet and solar heating systems

Emissions are an important aspect of a pellet heating system. High carbon monoxide emissions are often caused by unnecessary cycling of the burner when the burner is operated below the lowest combustion power. Combining pellet heating systems with a solar heating system can significantly reduce cycling of the pellet heater and avoid the inefficient summer operation of the pellet heater. The aim of this paper was to study CO-emissions of the different types of systems and to compare the yearly CO-emissions obtained from simulations with the yearly CO-emissions calculated based on the values that are obtained by the standard test methods. The results showed that the yearly CO-emissions obtained from the simulations are significant higher than the yearly CO-emissions calculated based on the standard test methods. It is also shown that for the studied systems the average emissions under these realistic annual conditions were greater than the limit values of two Eco-labels. Furthermore it could be seen that is possible to almost halve the CO-emission if the pellet heater is combined with a solar heating system.

Emissions from realistic operation of residential wood pellets heating systems

Emissions from residential combustion appliances vary significantly depending on the firing behaviours and combustion conditions, in addition to combustion technologies and fuel quality. Although wood pellet combustion in residential heating boilers is efficient, the combustion conditions during start-up and stop phases are not optimal and produce significantly high emissions such as carbon monoxide and hydrocarbon from incomplete combustion. The emissions from the start-up and stop phases of the pellet boilers are not fully taken into account in test methods for ecolabels which primarily focus on emissions during operation on full load and part load. The objective of the thesis is to investigate the emission characteristics during realistic operation of residential wood pellet boilers in order to identify when the major part of the annual emissions occur. Emissions from four residential wood pellet boilers were measured and characterized for three operating phases (start-up, steady and stop). Emissions from realistic operation of combined solar and wood pellet heating systems was continuously measured to investigate the influence of start-up and stop phases on total annual emissions. Measured emission data from the pellet devices were used to build an emission model to predict the annual emission factors from the dynamic operation of the heating system using the simulation software TRNSYS. Start-up emissions are found to vary with ignition type, supply of air and fuel, and time to complete the phase. Stop emissions are influenced by fan operation characteristics and the cleaning routine. Start-up and stop phases under realistic operation conditions contribute 80 – 95% of annual carbon monoxide (CO) emission, 60 – 90% total hydrocarbon (TOC), 10 – 20% of nitrogen oxides (NO), and 30 – 40% particles emissions. Annual emission factors from realistic operation of tested residential heating system with a top fed wood pelt boiler can be between 190 and 400 mg/MJ for the CO emissions, between 60 and 95 mg/MJ for the NO, between 6 and 25 mg/MJ for the TOC, between 30 and 116 mg/MJ for the particulate matter and between 2x10-13 /MJ and 4x10-13 /MJ for the number of particles. If the boiler has the cleaning sequence with compressed air such as in boiler B2, annual CO emission factor can be up to 550 mg/MJ. Average CO, TOC and particles emissions under realistic annual condition were greater than the limits values of two eco labels. These results highlight the importance of start-up and stop phases in annual emission factors (especially CO and TOC). Since a large or dominating part of the annual emissions in real operation arise from the start-up and stop sequences, test methods required by the ecolabels should take these emissions into account. In this way it will encourage the boiler manufacturers to minimize annual emissions. The annual emissions of residential pellet heating system can be reduced by optimizing the number of start-ups of the pellet boiler. It is possible to reduce up to 85% of the number of start-ups by optimizing the system design and its controller such as switching of the boiler pump after it stops, using two temperature sensors for boiler ON/OFF control, optimizing of the positions of the connections to the storage tank, increasing the mixing valve temperature in the boiler circuit and decreasing the pump flow rate. For 85 % reduction of start-ups, 75 % of CO and TOC emission factors were reduced while 13% increase in NO and 15 % increase in particle emissions was observed.

Mathematical analysis of maximum power generated by photovoltaic systems and fitting curves for standard test conditions

The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I- 100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.

Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variable-Structure Control Design of Switched Systems With an Application to a DC-DC Power Converter

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DCM Boost interleaved converter for operation in AC and DC to trolleybus application

This paper is based on the development and experimental analysis of a DCM Boost interleaved converter suitable for application in traction systems of electrical vehicles pulled by electrical motors (Trolleybus), which are powered by urban DC or AC distribution networks. This front-end structure is capable of providing significant improvements in trolleybuses systems and in the urban distribution network costs, and efficiency. The architecture of proposed converter is composed by five boost power cells in interleaving connection, operating in discontinuous conduction mode. Furthermore, the converter can operate as AC-DC converter, or as DC-DC converter providing the proper DC output voltage range required by DC or AC adjustable speed drivers. Therefore, when supplied by single-phase AC distribution networks, and operating as AC-DC converter, it is capable to provide high power factor, reduced harmonic distortion in the input current, complying with the restrictions imposed by the IEC 61000-3-4 standards. The digital controller has been implemented using a low cost FPGA and developed totally using a hardware description language VHDL and fixed point arithmetic. Thus, two control strategies are evaluated considering the compliance with input current restrictions imposed by IEC 61000-3-4 standards, the regular PWM modulation and a current correction PWM modulation. In order to verify the feasibility and performance of the proposed system, experimental results from a 15 kW low power scale prototype are presented, operating in DC and AC conditions.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

ALGORITHM FOR PROBABILISTIC ANALYSIS of DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATION

In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

Dynamics of vibrating systems with tuned liquid column dampers and limited power supply

Tuned liquid column dampers are U-tubes filled with some liquid, acting as an active vibration damper in structures of engineering interest like buildings and bridges. We study the effect of a tuned liquid column damper in a vibrating system consisting of a cart which vibrates under driving by a source with limited power supply (non-ideal excitation). The effect of a liquid damper is studied in some dynamical regimes characterized by coexistence of both periodic and chaotic motion. (c) 2005 Elsevier Ltd. All rights reserved.

Impact dampers for controlling chaos in systems with limited power supply

We investigate numerically the dynamical behavior of a non-ideal mechanical system consisting of a vibrating cart containing a particle which can oscillate back and forth colliding with walls carved in the cart. This system represents an impact damper for controlling high-amplitude vibrations and chaotic motion. The motion of the cart is induced by an in-board non-ideal motor driving an unbalanced rotor. We study the phase space of the cart and the bouncing particle, in particular the intertwined smooth and fractal basin boundary structure. The control of the chaotic motion of the cart due to the particle impacts is also investigated. Our numerical results suggests that impact dampers of small masses are effective to suppress chaos, but they also increase the final-state sensitivity of the system in its phase space. (C) 2004 Elsevier Ltd. All rights reserved.