M. Saravanan

Application of PSO technique for optimal location of FACTS devices considering system loadability and cost of installation

This paper presents the application of particle swarm optimization (PSO) technique to find optimal location of flexible AC transmission system (FACTS) devices to achieve maximum system loadability with minimum cost of installation of FACTS devices. While finding the optimal location, thermal limit for the lines and voltage limit for the buses are taken as constraints. Three types of FACTS devices, thyristor controlled series compensator (TCSC), static VAr compensator (SVC), and unified power flow controller (UPFC) are considered. The optimizations are performed on four parameters namely the location of FACTS devices, their setting, their type, and installation cost of FACTS devices. Two cases namely, single type devices (same type of FACTS devices) and multi type devices (combination of TCSC, SVC, and UPFC) are considered. Simulations are performed on IEEE 6 and 30 bus systems for optimal location of FACTS devices and the results obtained are encouraging and will be useful in electrical restructuring

Application of PSO technique to find optimal settings of TCSC for static security enhancement considering installation cost

This paper describes the application of particle swarm optimization (PSO) technique to find the optimal setting of thyristor-controlled series capacitors (TCSCs) in order to eliminate or minimize line overloads under single contingency or critical double contingency and to minimize the installation cost of TCSCs. The proposed approach uses Contingency Sensitivity Index (CSI) to rank the system branches according to their suitability for installing a TCSC. Once the locations are determined, PSO technique is used to find the best settings for the installed TCSCs to eliminate or minimize the line overloads in case of all the possible single contingencies or critical double contingencies and to minimize the installation cost of TCSCs. The voltage magnitude at each bus and the line flow through each branch for all the buses and branches respectively, have been considered as inequality and equality constraints. The proposed approach enhances the static security of the power system with minimum installation cost of TCSC. The IEEE 6-bus and 30-bus systems are used to validate the proposed approach

Performance Analysis of a Novel Reduced Switch Cascaded Multilevel Inverter

Multilevel inverters have been widely used for high-voltage and high-power applications. Their performance is greatly superior to that of conventional two-level inverters due to their reduced total harmonic distortion (THD), lower switch ratings, lower electromagnetic interference, and higher dc link voltages. However, they have some disadvantages such as an increased number of components, a complex pulse width modulation control method, and a voltage-balancing problem. In this paper, a novel nine-level reduced switch cascaded multilevel inverter based on a multilevel DC link (MLDCL) inverter topology with reduced switching components is proposed to improve the multilevel inverter performance by compensating the above mentioned disadvantages. This topology requires fewer components when compared to diode clamped, flying capacitor and cascaded inverters and it requires fewer carrier signals and gate drives. Therefore, the overall cost and circuit complexity are greatly reduced. This paper presents modulation methods by a novel reference and multicarrier based PWM schemes for reduced switch cascaded multilevel inverters (RSCMLI). It also compares the performance of the proposed scheme with that of conventional cascaded multilevel inverters (CCMLI). Simulation results from MATLAB/SIMULINK are presented to verify the performance of the nine-level RSCMLI. Finally, a prototype of the nine-level RSCMLI topology is built and tested to show the performance of the inverter through experimental results.

Single Parameter Fault Identification Technique for DC Motor through Wavelet Analysis and Fuzzy Logic

DC motors are widely used in industries like cement, paper manufacturing, etc., even today. Early fault identification in dc motors significantly improves its life time and reduces power consumption. Many conventional and soft computing techniques for fault identification in DC motors including a recent work using model based analysis with the help of fuzzy logic are available in literature. In this paper fuzzy logic and norm based wavelet analysis of startup transient current are proposed to identify and quantify the armature winding fault and bearing fault in DC motors, respectively. Results obtained by simulation using Matlab and Simulink are presented in this paper to validate the proposed work.

Simulation and experimental validation of new MPPT algorithm with direct control method for PV application

This paper presents the performance analysis of a new maximum power point tracking (MPPT) algorithm for solar photovoltaic (SPV) system using LUO converter. For effective utilization of the SPV panel, MPPT is essential. Hence, it is significant to simplify the tracking control algorithm with faster response, reduced ripple, higher efficiency, and cost-effective system. The proposed technique performs MPPT using a simple control technique by fine-tuning the duty cycle of the converter so as to make the input resistance of converter equal to the load resistance of the solar panel. Hence, the need for proportional–integral control loop is eliminated. The performance analysis of the proposed MPPT algorithm is compared with an existing perturb-and-observe algorithm in MATLAB simulation and experiment results of the proposed MPPT is implemented with the field programmable gate array controller using LUO converter with 40 W solar panel. From the results, it is proved that the response of the proposed method is f...

Design of artificial neuron controller for STATCOM in dSPACE environment

Reactive power compensation is an important issue in the control of electric power system. Reactive power from the source increases the transmission losses and reduces the power transmission capability of the transmission lines. Moreover, reactive power should not be transmitted through the transmission line to a longer distance. Hence Flexible AC Transmission Systems (FACTS) devices such as static compensator (STATCOM) unified power flow controller (UPFC) and static volt-ampere compensator (SVC) are used to alleviate these problems. In this paper, a voltage source converter (VSC) based STATCOM is developed with PI and Artificial Neural Network Controller (ANNC). The conventional PI controller has more tuning difficulties while the system parameter changes, whereas a trained neural network requires less computation time. The ANNC has the ability to generalize and can interpolate in between the training data. The ANNC designed was tested on a 75V, +/-3KVAR STATCOM in real time environment via state-of-the-art of digital signal processor advanced control engineering (dSPACE) DS1104 board and it was found that it was producing better results than the PI controller.

Control of SEPIC converter using neural network tuned PI controller

SEPIC converter control using neural network tuned PI controller is investigated in this paper. SEPIC converter is an AC/DC to DC converter and is very useful for various applications. The performance of the neural network tuned PI controller is compared with that of PI controller for the SEPIC converter by doing simulation in MATLAB-SIMULINK. The performance of the above controllers is tested for getting wide ranges of output reference voltages. It is found that the performance of the neural network tuned PI controller is better than that of the PI controller.

A novel modeling approach to predict the output performance of photovoltaic modules under different environmental conditions

In this paper, an improved mathematical model of a single-diode photovoltaic (PV) module has been developed to predict the maximum power of the PV modules produced by different PV technologies, such as mono crystalline, multi crystalline, and thin film, under varying environmental conditions. The current–voltage characteristic equation of the PV module is used to extract the PV module’s unknown parameters, such as light generated current, saturation current, ideality factor, series resistance, and shunt resistance at standard test condition (STC). In the proposed PV model, numerical methods are used to calculate the parameters of the PV module at STC, by introducing new equations to estimate the value of series resistance and shunt resistance. By introducing new equations IMPP and VMPP, the maximum power of different PV modules manufactured by various PV technologies at different environmental conditions is then found. In the proposed PV model, the percentage relative error obtained at maximum power is calculated and the experimental results are compared with the models that exist in the literature for different PV modules. The maximum power obtained by the proposed PV model is much closer to that obtained by the Sandia model and Ishaque two-diode model. Furthermore, the output performance of the developed PV model has close agreement with the experimentally obtained data and it is verified practically.

Staircase multicarrier SPWM technique for nine level cascaded inverter

In this paper, novel pulse width modulation technique which use staircase carrier waveform is proposed for nine level cascaded inverter. In staircase carrier waveform, different techniques such as phase disposition (PD), inverted phase disposition (IPD), phase opposition disposition (POD) and alternative phase opposition disposition (APOD) are implemented. The fundamental output voltage and harmonics obtained in each method are compared with the output waveform obtained with the triangular carrier waveform. The proposed switching technique enhances the fundamental component of the output voltage and improves total harmonic distortion. The different PWM methodologies adopting the constant switching frequency multicarrier are simulated for a 1KW, 3φ inverter using MATLAB/SIMULINK. The effect of switching frequency on the fundamental output voltage and harmonics are also analyzed.

A PERFOMANCE STUDY OF ANN AND ANFIS CONTROLLER FOR STATCOM IN dSPACE ENVIRONMENT

Reactive power compensation is an important issue in the control of electric power system. Reactive power from the source increases the transmission losses and reduces the power transmission capability of the transmission lines. Moreover, reactive power should not be transmitted through the transmission line to a longer distance. Hence Flexible AC Transmission Systems (FACTS) devices such as static compensator (STATCOM) unified power flow controller (UPFC) and static volt-ampere compensator (SVC) are used to alleviate these problems. In this paper, a voltage source converter (VSC) based STATCOM is developed with Artificial Neural Network Controller (ANNC) and Adaptive Neuro Fuzzy Inference System(ANFIS) controllers. The conventional PI controller has more tuning difficulties while the system parameter changes, whereas a trained neural network and ANFIS controllers requires less computation time. They have the ability to generalize and can interpolate in between the training data. The ANNC and ANFIS controllers designed were tested on a 75 V, 100 VA STATCOM in real time environment via state-of-the-art of digital signal processor advanced control engineering (dSPACE) DS1104 board and it was found that ANFIS controller was producing better results than the ANNC.