Suttichai Premrudeepreechacharn

An Optimal PMU Placement Method Against Measurement Loss and Branch Outage

This paper presents a new method for an optimal measurement placement of phasor measurement units (PMUs) for power system state estimation. The proposed method considers two types of contingency conditions (i.e., single measurement loss and single-branch outage) in order to obtain a reliable measurement system. First, the minimum condition number of the normalized measurement matrix is used as the criteria in conjunction with the sequential elimination approach to obtain a completely determined condition. Next, a sequential addition approach is used to search for necessary candidates for single measurement loss and single-branch outage conditions. These redundant measurements are optimized by binary integer programming. Finally, in order to minimize the number of PMU placement sites, a heuristic technique to rearrange measurement positions is also proposed. Numerical results on the IEEE test systems are demonstrated

An optimal measurement placement method for power system harmonic state estimation

This paper focuses on a new technique for optimal measurement placement for power system harmonic state estimation (HSE). The solution provides the optimal number of measurements and the best positions to place them, in order to identify the locations and magnitudes of harmonic sources. The minimum condition number of the measurement matrix is used as the criteria in conjunction with sequential elimination to solve this problem. Two different test systems are provided to validate the measurement placement algorithm. A three-phase asymmetric power system has been tested using the New Zealand test system, while the IEEE 14-bus test system has been used for testing a balanced power system.

Active power filter for three-phase four-wire electric systems using neural networks

Abstract This paper presents the design of neural networks compared with the conventional technique, a hysteresis controller for active power filter for three-phase four-wire electric system. A particular three-layer neural network structure is studied in some detail. Simulation and experimental results of the active power filter with both controllers are also presented to verify the feasibility of such controller. The simulation and experimental result show that both controller techniques can reduce harmonics in three-phase four-wire electric systems drawn by nonlinear loads and can reduce neutral current. The advantage of the neural network controller technique over hysteresis controller technique are less voltage ripple of d.c. bus, and less switching loss. Furthermore, the neural networks controller has better fault tolerance than the hysteresis controller.

Power system state estimation using singular value decomposition

Abstract This paper presents a new fundamental static state estimation algorithm using weighted least square (WLS) estimation, which is based on singular value decomposition (SVD) rather than the normal equations. In addition, this paper also uses linear WLS estimation, which is quicker than non-linear. The SVD approach does not require the whole network system to be observable prior to estimation. It can provide a solution even if the system under consideration is partially observable. The simulation study was performed on the IEEE 14-bus test system. The simulation results, both linear and non-linear WLS, have shown that the SVD approach can provide a solution even when ill-conditioned occurred while the normal equation approach failed to give satisfactory results. In addition, the SVD approach can identify which parts of the network are unobservable islands.

Fuzzy logic control of predictive current control for grid-connected single phase inverter

Fuzzy logic control is nonlinear and adaptive in nature that gives it robust performance under parameter variation and load disturbances. This paper describes the control strategy applied to a grid-connected single phase inverter with description of predictive current control. Then, fuzzy logic control for a grid-connected single phase inverter is described. Simulation results are provided. The fuzzy logic controllers provide attractive features such as fast response, good performance. Since the fuzzy logic controller requires less complex mathematical operations than classical controllers, its implementation does not require a computationally sophisticated microcontroller.

Solar-array modelling and maximum power point tracking using neural networks

This paper is studying a solar-array modelling and maximum power point tracking by comparing 2 neural networks which are back-propagation neural network and radial basis function neural network. Neural network has the potential to provide an improved method of deriving nonlinear models which is complementary to conventional techniques. The performance of the models and predicted maximum power point of solar cell are evaluated by comparing it with that of the conventional model by simulation. The simulation results has shown that both neural network work very well. In addition, the simulation results have shown that training for back-propagation takes longer time than radial basis function. However, back-propagation neural network needs less information for training. Radial basis function needs more information in order to get accurate modelling.

A Carrier-Based Unbalanced PWM Method for Four-Leg Voltage Source Inverter Fed Unsymmetrical Two-Phase Induction Motor

This paper presents a carrier-based unbalanced pulsewidth-modulated method for a two-phase four-leg voltage source inverter (VSI) and its realization for an unsymmetrical two-phase induction motor. A modulation strategy is developed to synthesize unbalanced two-phase output voltage waveforms based on the unipolar modulation technique with open-loop V/f control. The proposed control scheme allows independent magnitude controllability and quadrature phase angle for unbalanced two-phase output voltages. Thus, the modulation algorithm makes the four-leg VSI inequitable with unbalanced two-phase loads. Simulation and experimental results confirm the feasibility of the control method for the inverter.

Power control of single-phase voltage source inverter for grid-connected photovoltaic systems

This paper presents the design and analysis of both the active and reactive power control of a single-phase voltage source inverter (VSI) for grid-connected photovoltaic (PV) system. The proposed method is based on vector control of power by decoupling control of the active and reactive current components to feed the active and reactive power to the grid. The aim of this research is to control power factor at grid, to improve overall efficiency of transferring power of PV to alternate current power conversion into the grid, and to decrease phase current distortion of VSI. In this work, mathematical model of system has presented in details. The results of simulations of PV system 1kW connected to grid 220V, 50 Hz using MATLAB/Simulink software are also discussed. Simulation results have shown that the grid input power factor is nearly unity, and the distorting of phase current of the proposed system has been reduced, causing the total harmonic distortion for various power conditions falls within 5%.

Measurement placement method for power system state estimation: part I

This paper deals with a simple technique for measurement placement method of power system state estimation. The minimum condition number of the measurement matrix is used as the criteria in conjunction with sequential elimination to generalize the measurement placement. The singular value decomposition (SVD) approach will be used to solve the state estimation. The simulation study is performed on the IEEE 14-bus test system by linear weighted least square (WLS). It is found that, this algorithm can give a solution of measurement placement of injection current and voltage that make the power system observable.

On Harmonic State Estimation of Power System With Uncertain Network Parameters

This paper addresses the problem of harmonic state estimation (HSE) of a power system whose network parameters are known to be within certain tolerance bounds. The harmonic voltage and current phasors at harmonics of interest are measured by using adequate numbers of phasor measurement units. The HSE is formulated based on the weighted least squares (WLS) criterion as a parametric interval linear system of equations. The solutions are obtained as interval numbers representing the outer bound of state variables. A method for adjusting the weight used in WLS which takes uncertain network parameters into consideration is also proposed. The proposed HSE algorithm is applied to the three-phase power systems and the results from numerical experiments show that the bounds of state variables obtained by the proposed method agree with those estimated by performing Monte Carlo simulations but with much shorter computation time.