A hybrid recursive least square pso based algorithm for harmonic estimation

The presence of harmonics shapes the performance of a power system. Hence harmonic estimation of paramount importance while considering a power system network. Harmonics is an important parameter for power system control and enhance power system relaying, power quality monitoring, operation and control of electrical equipments. The increase in nonlinear load and time varying device causes periodic distortion of voltage and current waveforms which is not desirable electrical network. Due to this nonlinear load or device, the voltage and current waveform contains sinusoidal component other than the fundamental frequency which is known as the harmonics. Some existing techniques of harmonics estimation are Least Square (LS), Least Mean Square (LMS),Recursive Least Square (RLS), Kalman Filtering (KF), Soft Computing Techniques such as Artificial neural networks (ANN),Least square algorithm, Recursive least square algorithm, Genetic algorithm(GA) ,Particle swarm optimization(PSO) ,Ant colony optimization, Bacterial foraging optimization(BFO), Gravitational search algorithm, Cooker search algorithm ,Water drop algorithm, Bat algorithm etc. Though LMS algorithm has low computational complexity and good tracking ability ,but it provides poor estimation performance due to its poor convergence rate as the adaptation step-size is fixed. In case of RLS suitable initial choice of covariance matrix and gain leading to faster convergence. The thesis also proposed a hybrid recurvive least square pso based algorithm for power system harmonics estimation. In this thesis, the proposed hybrid approaches topower system harmonics estimation first optimize the unknown parametersof the regressor of the input power system signal using Particle swarm optimization and then RLS are applied for achieving faster convergence in estimating harmonics of distorted signal

Harmonic Estimation Of Distorted Power Signals Using PSO – Adaline

In recent times, power system harmonics has got a great deal of interest by many Power system Engineers. It is primarily due to the fact that non-linear loads comprise an increasing portion of the total load for a typical industrial plant. This increase in proportion of non-linear load and due to increased use of semi-conductor based power processors by utility companies has detoriated the Power Quality. Harmonics are a mathematical way of describing distortion in voltage or current waveform. The term harmonic refers to a component of a waveform occurs at an integer multiple of the fundamental frequency. Several methods had been proposed, such as discrete Fourier transforms, least square error technique, Kalman filtering, adaptive notch filters etc; Unlike above techniques, which treat harmonic estimation as completely non-linear problem there are some other hybrid techniques like Genetic Algorithm (GA), LS-Adaline, LS-PSOPC which decompose the problem of harmonic estimation into linear and non-linear problem. The results of LS-PSOPC and LS-Adaline has most attractive features of compactness and fastness. . Our new proposed technique tries to reduce the pitfalls in the LS-PSOPC, LS-Adaline techniques. With new technique we tried to estimate the Amplitudes by Least square estimator, frequency of the signal by PSOPC and phases of the harmonics by Adaline technique using MATLAB program. Harmonic signals were estimated by using LS-PSOPC, PSOPC-Adaline. Errors in estimating the signal by both the techniques are calculated and compared with each other

Optimal design of single-tuned passive filters using response surface methodology

This paper presents an approach based on Response Surface Methodology (RSM) to find the optimal parameters of the single-tuned passive filters for harmonic mitigation. The main advantages of RSM can be underlined as easy implementation and effective computation. Using RSM, the single-tuned harmonic filter is designed to minimize voltage total harmonic distortion (THDV) and current total harmonic distortion (THDI). Power factor (PF) is also incorporated in the design procedure as a constraint. To show the validity of the proposed approach, RSM and Classical Direct Search (Grid Search) methods are evaluated for a typical industrial power system

Parameter estimation of electric power transformers using Coyote Optimization Algorithm with experimental verification

In this work, the Coyote Optimization Algorithm (COA) is implemented for estimating the parameters of single and three-phase power transformers. The estimation process is employed on the basis of the manufacturer's operation reports. The COA is assessed with the aid of the deviation between the actual and the estimated parameters as the main objective function. Further, the COA is compared with well-known optimization algorithms i.e. particle swarm and Jaya optimization algorithms. Moreover, experimental verifications are carried out on 4 kVA, 380/380 V, three-phase transformer and 1 kVA, 230/230 V, single-phase transformer. The obtained results prove the effectiveness and capability of the proposed COA. According to the obtained results, COA has the ability and stability to identify the accurate optimal parameters in case of both single phase and three phase transformers; thus accurate performance of the transformers is achieved. The estimated parameters using COA lead to the highest closeness to the experimental measured parameters that realizes the best agreements between the estimated parameters and the actual parameters compared with other optimization algorithms

Power Quality Improvement Based On PSO Algorithm Incorporating UPQC

The usage of the term power quality is increasing day by day with extensive usage of large capacity loads and nonlinear loads. The major power quality issues are voltage disturbances and current disturbances in the present-day power systems. Today, with the advent of power semiconductor devices these power quality issues are solved to a great extent. The unified power quality conditioner is one such power semiconductor device which utilizes active filtering methodology to deal with the concerned power quality issues. Here an attempt is made to control and generate the reference currents and voltages for a unified power quality conditioner with the optimal tuned synchronous reference frame theory. The particle swarm optimization is employed to evolve gains of the proportional-integral controller. The unified power quality conditioner is a combination of shunt and series voltage source converters. The hysteresis band current controller for series and the pulse width modulation current controller for the shunt active filter are used for generation of gating pulses required by the switches of the voltage source converters in the unified power quality conditioner. The performance evaluation of multi-objective convergence fitness function (dealing: the voltage sag, the source current variations, and the load voltage variations) with unified power quality conditioner based on particle swarm optimization algorithm is performed. The efficacy of the proposed work is validated by conducting simulations in MATLAB/SIMULINK software environment.

Power Quality Enhancement in Electricity Grids with Wind Energy Using Multicell Converters and Energy Storage

In recent years, the wind power industry is experiencing a rapid growth and more wind farms with larger size wind turbines are being connected to the power system. While this contributes to the overall security of electricity supply, large-scale deployment of wind energy into the grid also presents many technical challenges. Most of these challenges are one way or another, related to the variability and intermittent nature of wind and affect the power quality of the distribution grid. Power quality relates to factors that cause variations in the voltage level and frequency as well as distortion in the voltage and current waveforms due to wind variability which produces both harmonics and inter-harmonics. The main motivation behind work is to propose a new topology of the static AC/DC/AC multicell converter to improve the power quality in grid-connected wind energy conversion systems. Serial switching cells have the ability to achieve a high power with lower-size components and improve the voltage waveforms at the input and output of the converter by increasing the number of cells. Furthermore, a battery energy storage system is included and a power management strategy is designed to ensure the continuity of power supply and consequently the autonomy of the proposed system. The simulation results are presented for a 149.2 kW wind turbine induction generator system and the results obtained demonstrate the reduced harmonics, improved transient response, and reference tracking of the voltage output of the wind energy conversion system.Peer reviewedFinal Accepted Versio