30 research outputs found
Study of the Crowbar's Functioning in Doubly Fed Induction Wind Generators: Towards Achieving Fault Ride Through Capability
No full textThis work examines the analysis of temporary behaviors and crowbar hardware layout for enhancing the fault ride-through capability (FRTC) in doubly fed induction wind generators (DFIWGs) A crowbar that is linked in parallel to the rotor side converter (RSC) is a feature found on the majority of DFIWGs these days to safeguard the RSC and DC-bus capacitor (DCBC). Previous studies demonstrated that the crowbar resistance has an impact on the DFIWG transient response's oscillations and peak values. In order to satisfy the FRTC criterion, the article initially methodically examines the DFIWG dynamics with and without a crowbar during a 100% voltage dip and studies the effects of two resistance values on the DCBC. It has been demonstrated that choosing a crowbar resistance greater than the permitted range may cause the DFIG FRT performance to decline. By actively addressing grid faults and improving performance, stability, and dependability, this integrated crowbar shows the potential of state-of-the-art control approaches for the dependable and efficient use of DFIWGs. MATLAB/Simulink is used to run robust simulations, and the results unambiguously show that the proposed model may significantly improve the FRTC of DFIWGs
Advanced control strategies of PMSM based wind energy conversion systems
No full textThesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of Electrical Engineering & Computer ScienceWind energy conversion system (WECS) is a system helps to produce the electrical energy
by transforming the incoming air stream. This system has two basic steps. First step is
the mechanical power which comes from the wind turbine blades. The second step is the
electrical power which produces by the generator. Due to complexity and dynamic variability
of electrical generator parameters, traditional control systems such as proportional-integraldeferential
(PID) controller has poor performance in case of fast dynamic response. With
WECS, the traditional control systems cause many controlling issues that affect WECS’s
efficiency and lead the system to have poor performance. Overshoot, undershoot, slow rising
time, and chattering are the consequences of applying the traditional control systems to
permanent magnet synchronous machine (PMSM). The main purpose of this dissertation
is to addresses this control issues and solves it which improve the PMSM’s performance
and WECS overall inefficiency. The dissertation proposes two advanced control strategies
that can enhance the electrical generator outcomes variables. Sliding mode control method
(SMC) and state dependent riccate equation control method (SDRE) have been derived,
designed,and applied to PMSM based WECS. The modeling results shows that both control
systems improved the generator dynamic response and limited the overshoot, undershoot,
and chattering effects. The simulation of the proposed models and results were simulated
using MATLAB Simulink software
Optimal Interior Mounted Permanent Magnet Synchronous Motors MTPA and MPPA Control Based on Sliding Mode Approaches
No full textClick on the DOI link to view this conference paper (may not be free).This paper presents novel sliding mode control (SMC) approaches for Maximum Torque Per Ampere (MTPA) and Maximum Power Per Ampere (MPPA) of interior permanent magnet synchronous motors (IPMs). We first derive the first-order sliding mode control methods to improve the field oriented control’s resiliency against the external perturbations, extraneous noise and modeling uncertainties. And after that, we propose the higher-order sliding mode control to significantly reduce the chattering phenomenon which is inherent in the first order sliding mode control method. Based on the comparison studies, the conventional proportional-integral derivative based field oriented control shows sluggish response and is more sensitive to parameter perturbations and external torque disturbances. By introducing the novel sliding mode control methods, both of the speed and torque regulation performance of interior-mounted permanent magnet synchronous motor can be greatly improved. Computer simulation studies have shown the superior performance of the first-order and higher-order sliding mode controllers for interior permanent magnet synchronous motor speed and torque regulation applications.ASM
Transient Stability Assessment of a Power System Using Multi-layer SVM Method
No full textClick on the URL link to access this conference paper on the publisher’s website (may not be free.)With the rapid growth of power systems, more large interconnections and the integration of large renewable energies make the systems more complicated. Therefore, transient stability assessment (TSA) has always been considered as one of the top challenges to ensure the security and operation of power systems. The development of Artificial Intelligence (AI) technologies, such as Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been drawn attentions to the power industry recently. Compared with traditional SVM, this paper presents an advanced TSA system using Multi-layer Support Vector Machine (ML-SVM) method. Basically, a Genetic Algorithm (GA) is used in ML-SVM to identify the valued feature subsets with varying numbers of features which makes full use of the input information. Transient stabilities of the system are determined based on the generator relative rotor angles obtained from the time-domain simulation. Data from the time-domain simulation are used as the inputs for ML-SVM training and testing. Then these trained SVMs are integrated to assess the transient stability of the power system. The simulation results show that the proposed method can reduce the possibility of misclassification of the system. Case study of IEEE 9-bus system on PowerWorld Simulator illustrates the effectiveness of the proposed approach
A Novel Sliding Mode Control Method of Interior-Mounted PMSM
No full textClick on the URL link to access this conference paper on the publisher’s website (may not be free.)Energy efficiency and output uncertainty are two of the most challenges that dynamic conversion is facing. Controlling the dynamic system variables is complicated due to the variability and unpredictability of the parameters, especially fast transient response. Sliding mode control is one effective technique that has been used to control and improve dynamic conversion system efficiency and to reach the rated values. Most of the recent research focus on the design, performance, and behaver study of sliding mode control in order to enhance the control system's performance. This paper presents a new Sliding mode control method of Interior-mounted permanent magnet synchronous motor. The proposed model solves many controlling problems that many other controllers facing such as PI controller, LQ regulator, and even PID linear methods. Also, the model has fast control response to the IPMSM fast dynamic transient and can solve the overshoot problem which leads the system to have more efficient performance. The results of SMC have been compared to PID controller applied to the same system. The simulation results have shown better performance of sliding mode control over the PID controller. The results are simulated using MATLAB Simulink software
Transient Stability Prediction Based on Long Short-term Memory Network
No full textClick on the DOI link to view this conference paper (may not be free).Transient stability assessment (TSA) has always been one of the most challenging problems in power system security and operations due to the rapid growth of electricity demand. The transient stability of power systems should be taken in advance to maintain the system stable. In recent years, a variety of Artificial Intelligence (AI) methods have been applied to the transient stability analysis, including Artificial Neural Network (ANN), Support Vector Machine (SVM) and some other technologies. In this paper, a transient stability prediction method using Long Short-term Memory (LSTM) network based Recurrent Neural Network (RNN) is discussed. Case studies using Multi-layer SVM on the IEEE 9 bus system is adopted as a benchmark to validate the proposed method. Then, the method is performed on the New-England 39 bus system to test the validity. The training and testing data of the LSTM network for the new approach are obtained by performing the time-domain simulation (TDS) on the New-England 39-Bus System in PSAT (Power System Analysis Toolbox) toolbox. Simulation results show that the proposed method exhibits significantly better classification accuracy on predicting the stability, which demonstrates the effectiveness of the proposed approach
Maximum torque per ampere and maximum power per ampere sliding mode control for interior permanent magnet synchronous motors
No full text© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This paper presents novel maximum torque per ampere (MTPA) and maximum power per ampere (MPPA) sliding mode control (SMC) approaches for interior permanent-magnet synchronous motors (IPMs). We first derive the first-order SMC methods to improve the field-oriented control's resiliency against the external perturbations, extraneous noise and modelling uncertainties. After that, we propose the higher-order SMC to significantly reduce the chattering phenomenon, which is inherent in the first-order sliding mode method. Based on the comparison studies, the conventional proportional-integral-derivative based field oriented control shows sluggish response and is more sensitive to parameter perturbations and external torque disturbances. By introducing the novel SMC methods, both the speed and torque regulation performance of interior permanent magnet synchronous motor can be greatly improved. Computer simulation studies have demonstrated the superior performance of the first-order and higher-order sliding mode controllers for interior permanent magnet synchronous motor speed and torque regulation applications
An improved Kepler optimization algorithm for module parameter identification supporting PV power estimation
No full textIdentification of photovoltaic (PV) module characteristics in solar systems is a vital task, nowadays, for optimal PV power estimation. In this paper, this challenge task has been studied using a novel advanced Kepler optimization algorithm (KOA). The standard version of KOA is adopted and assessed for getting the nine parameters of the PV triple diode model (3DM) considering three different practical PV modules. Kepler's principles of planetary motion are used by KOA to forecast the location and velocity of planets at any particular moment. However, the success rate of the KOA is not compatible, and its efficiency needs to be enhanced. As a result, an Improved KOA (IKOA) is created by incorporating an advanced mechanism of Local Escaping Operator (LEO), resulting in improved process of searching with evading local optima. This mechanism means that the exploitation approach will activate with around half of the solutions for every iteration starting at the initial phase of the iteration journey. The suggested IKOA besides the standard KOA are developed for predicting PV parameters for three distinct PV modules which are Photowatt PWP201, R.T.C France and STM6-40/36. The results corresponding to the latest algorithms are also compared with the proposed IKOA about different published works. The simulation findings reveal that the suggested IKOA exhibits notable average improvement rates for the three modules of 62.27 %, 55.1 %, and 32.12 %, respectively. Furthermore, the suggested IKOA asserts significant superiority and robustness over previously reported results
A Fractional Order-Kepler Optimization Algorithm (FO-KOA) for single and double-diode parameters PV cell extraction
No full textThe primary objective of this study is to investigate the effects of the Fractional Order Kepler Optimization Algorithm (FO-KOA) on photovoltaic (PV) module feature identification in solar systems. Leveraging the strengths of the original KOA, FO-KOA introduces fractional order elements and a Local Escaping Approach (LEA) to enhance search efficiency and prevent premature convergence. The FO element provides effective information and past expertise sharing amongst the participants to avoid premature converging. Additionally, LEA is incorporated to boost the search procedure by evading local optimization. The single-diode-model (SDM) and Double-diode-model (DDM) are two different equivalent circuits that are used for obtaining the unidentified parameters of the PV. Applied to KC-200, Ultra-Power-85, and SP-70 PV modules, FO-KOA is compared to the original KOA technique and contemporary algorithms. Simulation results demonstrate FO-KOA's remarkable average improvement rates, showcasing its significant advantages and robustness over earlier reported methods. The proposed FO-KOA demonstrates exceptional performance, outperforming existing algorithms by 94.42 %–99.73 % in optimizing PV cell parameter extraction, particularly for the KC200GT module, showcasing consistent superiority and robustness. Also, the proposed FO-KOA is validated of on SDM and DDM for the well-known RTC France PV cell
Modified Rime-Ice Growth Optimizer with Polynomial Differential Learning Operator for Single- and Double-Diode PV Parameter Estimation Problem
No full textA recent optimization algorithm, the Rime Optimization Algorithm (RIME), was developed to efficiently utilize the physical phenomenon of rime-ice growth. It simulates the hard-rime and soft-rime processes, constructing the mechanisms of hard-rime puncture and soft-rime search. In this study, an enhanced version, termed Modified RIME (MRIME), is introduced, integrating a Polynomial Differential Learning Operator (PDLO). The incorporation of PDLO introduces non-linearities to the RIME algorithm, enhancing its adaptability, convergence speed, and global search capability compared to the conventional RIME approach. The proposed MRIME algorithm is designed to identify photovoltaic (PV) module characteristics by considering diverse equivalent circuits, including the One-Diode Model (ONE-DM) and Two-Diode Model TWO-DM, to determine the unspecified parameters of the PV. The MRIME approach is compared to the conventional RIME method using two commercial PV modules, namely the STM6-40/36 module and R.T.C. France cell. The simulation results are juxtaposed with those from contemporary algorithms based on published research. The outcomes related to recent algorithms are also compared with those of the MRIME algorithm in relation to various existing studies. The simulation results indicate that the MRIME algorithm demonstrates substantial improvement rates for the STM6-40/36 module and R.T.C. France cell, achieving 1.16% and 18.45% improvement for the ONE-DM, respectively. For the TWO-DM, it shows significant improvement rates for the two modules, reaching 1.14% and 50.42%, respectively. The MRIME algorithm, in comparison to previously published results, establishes substantial superiority and robustness
