International Journal of Power and Energy Conversion (20 papers in press)
Empirical Wavelet Transform and dual feedforward neural network for classification of power quality disturbances
by Karthik Thirumala, Aditi Kanjolia, Trapti Jain, Amod C. Umarikar
Abstract: This paper proposes a novel approach for classification of single and combined power quality (PQ) disturbances. The EWT based adaptive filtering technique is employed first to decompose the signal into its individual frequency components by estimation of frequencies. The frequency estimation in this paper is done using a divide-to-conquer principle based FFT technique and followed by an adaptive filter design. Then, some unique potential features reflecting the characteristics of disturbances are extracted from the mono-frequency components as well as the signal. A single classifier used for the classification of combined disturbances, whose characteristics are alike, gives less classification accuracy. Therefore, the use of a dual FFNN is proposed for the classification of single and combined PQ disturbances to effectively reduce the misclassification and improve the accuracy. The effectiveness of the proposed approach is evaluated on a broad range of time-varying power signals with varying degree of irregularities, noise, and fundamental frequency deviation. The results obtained for both the simulated as well as the real disturbance signals elucidate the efficiency and robustness of the proposed approach for classification of the most frequent disturbances.
Keywords: Power quality (PQ); Fast Fourier transform (FFT); Empirical wavelet transform (EWT); Adaptive filtering; Dual feedforward neural network.
Variable structure power control under different operating conditions of PM synchronous generator wind farm connected to electrical network
by Youssef Errami, Abdellatif Obbadi, Smail Sahnoun, Mohammed Ouassaid, Mohamed Maaroufi
Abstract: The enlarged penetration of wind power into electrical network brings challenges to control strategies of Variable Speed Wind Energy Conversion Systems (VS-WECS). In this study, a nonlinear control scheme for Wind Farm System (WFS) is proposed. The WFS consists of a 3 PMSG which are connected to a common dc bus system with rectifiers. The dc-bus is connected to the power network through only one inverter system, a grid-side filter as well as the transformer. The control technique is realized using Variable Structure Sliding Mode Control (VSSMC). First, a model is elaborated on the basis of the d-q axes reference frame. Furthermore, a VSSMC scheme is obtained in the sense of theorem of Lyapunov stability for the WFS to satisfy several objectives. The generator side rectifiers control is used to keep the generator rotor velocities at an optimal value obtained from the Maximum Power Point Tracking (MPPT) algorithm to maximize the total extracted power. The grid-side inverter injects the generated power into the AC network, regulates DC-link voltage and it is used to achieve unity power factor. Also, a pitch control scheme is proposed in order to prevent wind turbine destruction from excessive wind velocity. The simulation results demonstrate the effectiveness of the proposed VSSMC strategy in different scenarios, and their advantages are shown in comparison with a conventional Proportional Integral (PI) control approach under grid fault conditions and the possible presence of uncertainties.
Keywords: Variable Speed Wind Farm System; PMSG; MPPT; Nonlinear Control; VSSMC approach; Electric Network Connection.
A Hybrid Hilbert Huang Transform and Improved Fuzzy Decision Tree Classifier for Assessment of Power Quality Disturbances in a Grid Connected Distributed Generation System
by Tatiana Chakravorti, R. Bisoi, N.R. Nayak
Abstract: This paper focuses on Discrete Hilbert Huang transform (HHT) and Improved Fuzzy decision tree (IFDT) based detection and classification of power quality (PQ) disturbances as a new contribution to the literature. A distributed generation (DG) based microgrid has been modeled with wind and solar. Different PQ disturbances have been simulated with various wind speed and PV penetration. The PQ signals are passed through Empirical mode decomposition (EMD) to obtain the intrinsic mode functions (IMFs). These IMFs are enforced to the Hilbert Transform (HT) to extract the instantaneous attributes. These attributes of Hilbert Transform (HT) are used for features extraction. Based on these extracted features Improved Fuzzy rules are formed for classification of the PQ disturbances. Synthetically PQ disturbances are simulated to check the performance of the proposed method. All these signal samples are processed through the proposed algorithm. The proposed method has been found to be capable of accurate detection and classification of PQ disturbances than many other techniques in the literature.
Keywords: Distributed Generations (DG); Hilbert Huang Transform (HHT); Improved Fuzzy Decision Tree (IFDT); Pattern Recognition; Power Quality Disturbances.
Design Strategies for Speed Control of an Inverter fed Permanent Magnet Synchronous Motor Drive
by RAMANA PILLA, Alice Mary Karlapudy, Surya Kalavathi Munagala
Abstract: Permenant Magnet Synchronous Motor (PMSM) drives are becoming more popular and replaces DC and Induction motor drives in industrial applications like rolling mills, home appliances, transport systems, robotics & factory automation, hybrid electic vehicles etc. Various control schemes are suggested in the literature for variable speed AC drives fed from static power sources. Among them field oriented control employing vector control strategies has become quite popular in recent years. A disadvantage of the scheme when applied to PMSM drives is that the motor always operates at a lagging power factor. In this paper, a generalized design strategy for speed control loop of an inverter fed PMSM drive is suggested. In this design for different combinations of currents, same torque can be generated, which leads to more general control scheme. The closed loop control system for PMSM drive is simulated using MATLAB. The performance figures of various cases such as internal p.f angle control, torque angle control and field oriented control can be obtained and verified through simulation for different power factors of the motor ranging from lagging to leading through unity.
Keywords: Field Oriented Control; Internal Power Factor Angle Control; Permanent Magnet Synchronous Motor; PI controller; Speed Controller; Torque Angle Control.
Reliability Analysis of the PMU Microwave Communication Networks Using Generalized Stochastic Petri Nets
by D.K. Mohanta, Bhargav Appasani
Abstract: The phasor measurement units (PMUs) have evolved as powerful extrapolations of the supervisory control and data acquisition (SCADA) systems due to their profound applications. The PMU combines the measured voltage and current phasors with the time signals received from the global positioning system (GPS), to provide an effective solution for real time monitoring of the smart grid (SG). In the SG several such PMUs continuously generate the time tagged quantitative data which are communicated to a central monitoring station known as the phasor data concentrator (PDC). This quantitative data carries the information pertaining to the grid dynamics. At the PDC the data collected from several PMUs is synchronized and is subsequently analyzed by a decision making expert. The communication system plays a pivotal role in the transfer of the phasor measurements and thus should be highly reliable. This article presents a detailed approach for the construction of the generalized stochastic petri nets (GSPNs) for the reliability analysis of the PMU microwave communication networks (MCNs). These communication networks are optimally planned to achieve maximum reliability without compromising the system observability. Case study results for the North Eastern power grid of India are presented to demonstrate the efficacy of the proposed approach.
Keywords: Reliability; Smart Grid; Phasor Measurement Unit; Generalized Stochastic Petri Nets.
A Control Scheme for Grid-Tied Hybrid Modular Multilevel Converter under Grid Voltage Unbalance
by RASHMI RANJAN BEHERA
Abstract: This paper presents a Finite-Control-Set Predictive Current Control
(FCS-PCC) scheme for the recently proposed Hybrid Modular Multilevel
(HMMC) based grid connected system. The HMMC has several advantages over
the conventional Modular Multilevel Converter (MMC) as well as other multilevel
topologies. This topology has reduced number of switch counts compared to the
conventional MMC, eliminates the problem of circulating current and having
higher efficiency. The required number of Sub-Modules (SM) is half of the
conventional MMC, along with an H bridge circuit per phase. This paper analyses
the real and reactive power control through FCS-PCC and addresses the AC side
grid unbalance by third harmonics injection method. During grid side voltage
unbalance, there is a problem of the unequal amount of power exchange between
per-phase converter and grid, which needs to be taken care of with an appropriate
control method. This study proposed a method to add or subtract an amount of
third harmonic component with the reference current signal given to the predictive controller to maintain the grid current at the desired level. The whole concept has been presented along with a simulation study in Matlab/Simulink environment and the results are presented in support of the described concept.
Keywords: Hybrid modular multilevel converter; grid-connected; predictive current control; grid voltage unbalance control.
Fresh particle crowd optimization of efficiency-oriented control in interior permanent magnet synchronous motor during operation
by Hakchol Jong
Abstract: High-efficiency electric drive systems claim not only optimally designed electric machines but also efficiency-oriented control strategies. Taking machines and drives into synergetic consideration, this paper proposes a fresh particle crowd optimization (FPCO) of efficiency-oriented control algorithm named maximum outer torque per ampere (MOPA) control and maximum efficiency per ampere (MEPA) control, aiming to maximize the efficiency of interior permanent magnet synchronous machines during operation. Difference from conventional id = 0 or maximum torque per ampere control, MOPA and MEPA fully consider the cross effect Core loss, iron loss, supplementary loss and mechanical loss, from which the full-order loss model of interior permanent magnet synchronous motor (IPMSM) is built. In order to identify the accuracy of the efficiency-oriented control algorithm, the efficiency-oriented controlled system on based FPCO using nonsingular terminal sliding (NTS) controller is built, on the base of this, the stabilization of the the current trajectory and the voltage vector from simulation and testing are inspected. After that, the higher effectiveness of MOPA and MEPA is proved through the operation experiment of IPMSM.
Keywords: Fresh particle crowd optimization; interior permanent magnet synchronous motor; maximum outer torque per ampere; maximum efficiency per ampere; nonsingular terminal sliding; space vector pulse width modulated.
Fuel Cell Integration with Grid using Voltage Source Converter and its Control
by Sabha Raj Arya, N. Sharath Kumar, Ashutosh Giri, Amin Qureshi
Abstract: Due to increased burden on the grid, voltage and frequency control becomes very difficult. Moreover nonlinear domestic appliances are also contributing towards power quality problems related with voltage and current. To share the burden of grid and for increasing the power quality at the end users authors have proposed new topology comprising fuel cell along with voltage source converter (VSC) used as DSTATCOM connected in shunt at point of common coupling of load and source. To control the VSC, forward backward least mean square algorithm (FBLMS) is used. In this algorithm, error between desired and estimated signal is calculated in both forward and backward directions. The average error is calculated based on forward path error. Further the active weight components and the reactive weight components are used to calculate reference source current for gate pulse generation. The complete system is simulated and validated in the laboratory environment with one prototype, the results are satisfactory.
Keywords: Voltage source converter; Power Quality; Proton Exchange Membrane (PEM),Fuel Cell,FBLMS.
OPTIMAL REACTIVE POWER ALLOCATION AND SETTLEMENT IN DEREGULATED POWER MARKET
by Sarmila Har Beagam, Jayashree R, Abdullah Khan
Abstract: This paper proposes a new optimal Q flow (OQF) method for market clearing and settlement of pure reactive power market to overcome the variability of loss price due to change in marginal bus. A lumped linear model is proposed for fast convergence. The power balance equality constraint and voltage inequality constraints are incorporated in the OQF method. In this method a unique reference for delivery/withdrawal point for reactive power called Market Center is proposed to share the total transmission loss equitably between the GENCO and DISCO participants in a transparent manner for pure Q Market using incremental loss factor method. The objective function is to minimize the cost of the reactive power payable to GENCOs with respect to market center. The compensation received by GENCO participants and
Locational Marginal Price to be paid by DISCO participants are derived for a single sided auction market.
Keywords: iterative Q flow; market centre; incremental loss factor; loss allocation; market clearing and settlement; locational marginal compensation; LMC; locational marginal price; LMP.
Frequency and Tie-line Power Awareness in Eco-AGC of multi-area Power system with SSO based Fractional Order Controller
by Prakash Chandra Sahu, Ramesh Chandra Prusty
Abstract: The article focuses on how a conventional AGC (Automatic Generation Control) will be economically efficient. A very less research has been carried out owing to this economical aspect of AGC. The main function of AGC is to control mechanical power in accordance with unexpected load variation. AGC aims to keep system frequency and net scheduled interchanges between different control areas (tie-line power) within predetermined values. This conventional AGC tries to keep Area Control Error (ACE) zero to maintain system stable. Though frequency and tie-line power are maintained within predetermined values but generation may not be economically dispatched. So ACE based AGC are economically inefficient to absorb its own load deviation and are economically weak. To generate power economically with scheduled frequency value and to make economically efficient to conventional AGC, it is required to combine Conventional AGC with Economic Load Dispatch (ELD) which combined known as Economic AGC (Eco-AGC). In Eco-AGC concern unlike conventional AGC, deviation in frequency is brought back to zero but scheduled interchanges never comes to zero rather settled to a new value as power always flows from lower incremental fuel cost generating station to higher incremental cost generating station in response to load demand. To perform Eco-AGC, this research article proposes a novel Salp Swarm Optimization (SSO) based Fractional order fuzzy controller for reducing errors and to maintain system stable with economic efficient. To justify robustness of proposed controller different sensitive analysis has been done with wide variation of system parameters. In regard to optimization process Integral of Time Multiplied Absolute Error (ITAE) has been used as objective function due to its improved dynamic response producing capability.
Keywords: Automatic Generation Control (AGC); Area Control Error (ACE); Economic Load Dispatch (ELD); Salp Swarm Optimization (SSO); Step Load Perturbation (SLP); Fractional Order Fuzzy PID (FO-FPID).
Design of Fractional Order Proportional Integral (FOPI) Controller for Load Frequency Control of Multi Area Power System under Deregulated Environment
by KURAKULA VIMAL, V. GANESH
Abstract: The main objective of the present article is introduced to focus how efficiently to minimize the deviations in frequency and Area Control Error caused by load fluctuations and uncertainties in load under the deregulated environment of power system. This work is carried out to eliminate the frequency errors by using Fractional Order Proportional Integral (FOPI) Controller under deregulated environment by considering the effect of one possible bilateral contract scenario. In Electrical industry under deregulated environment, the Load Frequency Control and Automatic Generation Control system have been considered by taking the effect of bilateral contracts. So a DISCO has liberty to have agreements with GENCOs in other areas also. The proposed work is to enhance the system parameters such as line transmitted power, frequency deviation error, and area control error (ACE) using Fractional Order PI Controller for hydro-thermal, thermal-thermal power system under deregulated power system. Because of system nonlinearities, uncertainties and continuously fluctuant load demand the design of these controllers is quite complicated in deregulated environment. hence it is proposed an integer Fractional order PI (FOPI) Controller is to solve LFC problem of interconnected multi area Hydro-Thermal, Thermal-thermal systems in deregulated environment by considering one bilateral contract scenario. The results have been analyzed with classical integer order PI controller and FOPI controller. It is observed that the efficacy of the results is satisfied and improved when compared with previous work.
Keywords: LFC; AGC;PI Controller; FOPI Controller and Integer Order PI Controller.
Finite Element Validation of the Analytical Model of Variable Reluctance Motor
by Souhir TOUNSI
Abstract: In this paper, we present a methodology for the parameterized modeling of a synchronous motor with variable reluctance. This methodology is based on the analytical method offering the possibility of the coupling of the analytical program to optimization algorithms of large dimensions since this method is fast in term simulation time. The analytical model is validated by the finite element method in two dimensions in linear regime and in saturated regime.
Keywords: Variable Reluctance Motor; Analytic Method; Finite Element Method; Validation.
Solar power forecasting using Robust Kernel Extreme Learning Machine and Decomposition Methods
by Irani Majumder, Ranjeeta Bisoi, Niranjan Nayak, Naeem Hannoon
Abstract: This paper proposes both wavelet and Empirical Mode Decomposition (EMD) based robust Kernel Extreme Learning Machine (RKELM) variants to achieve a precisely predicted value of solar power generation in a smart grid environment with a high penetration of solar power. The non-stationary historical solar power data is initially decomposed into various intrinsic mode functions (IMFs) using EMD technique or several approximate and detailed coefficients using wavelets, which are subsequently passed through the proposed robust Morlet wavelet kernel extreme learning machine (RWKELM) in order to predict 15 minutes, 1 hour and 1 day ahead solar power, respectively. Further a reduced kernel matrix version of RWKELM is used to decrease the training time significantly without appreciable loss of forecasting accuracy. For validation of the proposed solar power forecasting technique, the real time data from a 1 MW Photovoltaic (PV) station in the state of Odisha, India is used. By implementing the real time data for validation of the proposed method for short term solar power prediction it can be observed that the proposed EMD based RWKELM outperforms other kernel functions and other prevalent methods, in terms of different performance matrices and execution time, under various prediction horizons. Further the computational overhead of the proposed EMD-wavelet kernel can be reduced by selecting a subset of randomly chosen support vectors from training samples which drastically reduces the computational time with a slight loss in the forecasting accuracy in solar power prediction. The solar power prediction results on experimental data show the lowest errors which proves the highest prediction accuracy as compared to some of the well known forecasting techniques like ELM, EMD based ELM, WD based ELM, SVM, RBFLNN and other variants of kernel functions.
Keywords: Solar power forecasting; Empirical Mode Decomposition (EMD); Wavelet transform decomposition (WD); extreme learning machine (ELM); Robust Kernel based Extreme Learning Machine (RKELM); Reduced kernel matrix.
Design and Simulation of a Low-Power Low-Cost High-Frequency Transformer Based Dynamic Voltage Restorer for Household Applications
by Mohammad Farhadi-Kangarlu
Abstract: Sudden variations of voltage can be damaging for voltage-sensitive loads. Dynamic voltage restorer (DVR), which is a power-electronic converter based device, is an economical solution for voltage variations compensation. In this paper, a high-frequency (HF) transformer based DVR is designed for household applications. As the household application is considered, the DVR will be low-power and it should be designed to be compact and economic. Therefore, the HF transformer is used in the design in order the system to be more compact and economic. Also, unlike other HF transformer based DVR structures, no energy storage is used and the number of active converter stages is minimized. The topology selection and compensation capacity is justified in the paper. The simulation results of the designed DVR are presented to verify its performance.
Keywords: Dynamic voltage restorer; high-frequency transformer; power quality; voltage sag; voltage compensation.
Modelling and control design of a multi-source renewable energy system with coupled DC/DC converters power compensation
by Sihem Djebbri, Abderezzak Metatla, Samir Ladaci
Abstract: This paper investigates the electrical energy transfers control in a multi-source renewable energy system. The considered system is composed of two sources (photovoltaic and lead-acid battery bank), a specific zero voltage switch full-bridge isolated buck DC/DC power converter and the load.
The main contribution of this paper is to propose a modelling approach that details the coupling and uncoupling of DC/DC power converter on a DC bus of multisource renewable energy systems. The proposed model is suitable for control and performance evaluation. This modelization, results in a system with two cascade loops, the inner loop which allows the control of the current and the outer loop which controls the output voltage using a PI and a PID two controllers respectively. We show by means of numerical simulation tests that the proposed control gives good results in terms of robustness and stability despite the fluctuations of renewable sources and the load variations.
Keywords: Multi-source renewable energy system; modelling; PID control; DC bus; performance; robustness.
Implementation of PWM technique with Soft Starting Algorithm for Three-Phase Induction Motor Drives
by Rajan Vamja, Rakesh Maurya, Mo.Suhel A. Shaikh
Abstract: In this paper, a study on issues related to starting of induction motor are carried out. Performance comparisons of various starting methods are also studied. To investigate the performance of ramp soft starting algorithm, Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques are implemented with voltage source inverter (VSI) fed induction motor. Detailed FFT analysis of stator voltage and current of induction motor is studied under wide range of speed variations. Based on experimental study, few recommendations for implementation of boost start-up and s-curve start-up algorithm in Microcontroller (STM32F407VG) are made for high inertial load. Experimental results are obtained and its performance analysis in view of FFT of motor current is also carried out for aforesaid PWM techniques.
Keywords: Soft Starting; Adjustable Speed Drive (ASD); Sinusoidal Pulse Width Modulation (SPWM); Vector Pulse Width Modulation (SVPWM); control voltage source inverter (VSI); Boost start-up; torque; Synchronous PWM; Asynchronous PWM.
An Intelligent Scheme for Categorizing Fault Events in Compensated Power Network Using K-nearest Neighbor Technique
by Sunil Kumar Singh, D.N. Vishwakarma, R.K. Saket
Abstract: This paper describes a machine learning based intelligent scheme for categorization of fault events in series compensated power network using K-nearest neighbor technique. The wavelet decomposition mechanism is applied on 3-phase post fault current signal for digging out the significant features of the shunt fault events in this proposed scheme. Afterward, K-nearest neighbor based classifier model has been utilized for ascertaining the specific category of the fault events in the network. The category of the shunt events in the network has been ascertained on the basis of the estimated entropy of the wavelet coefficients. The feasibility and strength of proposed scheme for categorizing the fault events in the compensated power network are assessed for different fault events with varying network situations in simulated compensated power network. Finally, it is observed that the proposed discrete wavelet transform and K-nearest neighbor based scheme is very effectual in identifying the specific fault events in the compensated power network and is unaffected by changing system circumstances.
Keywords: Discrete Wavelet Transform; Machine learning; K-nearest Neighbor; Fault Diagnosis; Protection of compensated power network.
Sensorless Control Based on the Improved VM_ NN SC MRAS Method for High Performance SPIM Drives Using LPF
by Ngoc Thuy Pham, Nho Van Nguyen
Abstract: In this paper, a novel Stator Current Model Reference Adaptive System (SC_MRAS) based scheme using neural network (NN) for sensorless controlled of Six Phase Induction Motor (SPIM) drive is presented. For this scheme, the measured stator current components are used as the reference model to avoid the pure integrator problems and reduce influence of motor parameter variation. The two layer linear NN stator current observer is used as an adaptive model with the BP algorithm is used to train the NN online to estiamate rotor speed and update stator resistor value. The voltage model (VM) rotor flux identifier with value of stator resistor is update online is used to provide the rotor flux for the current adaptive model, this helps to overcome the instability problem in the regenerating mode of operation that occur when using current model for rotor flux identifier and enhance the low speed operation performance of the proposed scheme. Simulation results have demonstrated that the proposed observer is significantly improved especially at low and near zero speed range.
Keywords: MRAS observer; Neural network; sensorless vector control; Six phase induction motor drive.
Optimal sizing and placement of the UPQC and DG simultaneously based on sensitivity analysis and firefly algorithm
by Shahram Karimi, Khalil Gholami, M. Rizwan
Abstract: The efficient operation of power system is utmost important for reliable power supply to customers. The distributed generation (DG) and power electronics based custom devices can provide the solution for the reliable and efficient power system. In this paper, simultaneous allocation of distributed generation (DG) and unified power quality conditioner (UPQC) is investigated to minimize the real power loss and improved voltage indices of the radial distribution networks based on the firefly algorithm (FA) and sensitivity analysis. rnIn the proposed work, the loss sensitivity factor (LSF) is estimated to find the specific nodes for the DG and UPQC location. Through LSF, the search space and time of optimization process has been reduced. The firefly algorithm is used to find the optimal size of the DG and UPQC and their locations from the specific nodes determined above. The proposed work is performed on IEEE 34 bus system and IEEE 69 bus systems. The proposed approach rigidly determines the simultaneous optimal placement of the DG and UPQC in the radial distribution network in order to improve the voltage profile and minimize the real power loss of the network without violating the practical system constraints. Obtained results are compared with other existing approaches and found better. It is revealed that the proposed approach is effective and has novelty for the optimal sizing and simultaneous placement of custom devices with DG.
Keywords: Distributed Generation; Unified Power Quality Conditioner; Sensitivity Analysis; Firefly Algorithm.
Optimal Design of Battery Charge Management Controller for Hybrid System PV/Wind Cell with storage battery
by Mohamed Ismail, Ahmed Bendary, Mahmoud Elsisi
Abstract: The renewable energy sources (RES) became a fundamental necessity to the majority of electric systems and also the isolated systems like the water pumping and petroleum excavators systems. The RES typically required energy storage system because of variations in the power during the day. Because of increment popular of utilizing batteries, the charging and discharging procedure of battery system should have been well managed through an adaptive controlled system. In this paper, a standalone power system utilizing photovoltaic, wind energy and batteries are contributed in providing the required load. The charging balance of batteries is accomplished by utilizing a new hybrid genetic algorithm (GA)-based proportional integral (PI) controller with adaptive neuro-fuzzy inference system (ANFIS). This new hybrid GA-based PI with ANFIS control method is compared with the GA-based PI controller and the conventional PI controller based on Ziegler Nichols (ZN) technique. Dynamic simulations exhibit the right performance of the hybrid GA-based PI with ANFIS control for the proposed power system under study and the better performance than the GA-based PI controller and ZN-based PI controller.
Keywords: Photovoltaic; wind generation; batteries; ANFIS; genetic algorithm (GA).