Master of Science Thesis in Electrical Engineering
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This thesis proposes a method for designing global Power System Stabilizers (PSS) using Phasor Measurement Unit (PMU) data. The method first designs local PSS using existing input/output selection techniques, but finds that the number of selected inputs and outputs is too large. The thesis then suggests a new algorithm that uses bus/generator clustering with independent component analysis and principal component analysis to reduce the number of input/output candidates. Finally, the design of global PSS is performed using the optimized input/output selection from the new method, PMU data, a genetic algorithm optimization method, and linear matrix inequalities.
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This paper is an extension of our previous work, which discussed the
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A0710113
The document proposes an artificial bee colony (ABC) algorithm based neuro fuzzy controller (NFC) to improve the performance of a unified power quality conditioner (UPQC) in compensating for power quality issues like voltage sags. The NFC uses the error and change in error voltage as inputs to a neural network. The ABC algorithm is used to optimize the neural network output. This optimized output is then used to generate optimal fuzzy rules and calculate the discharging capacitor voltage from a bias voltage generator, replacing the DC link capacitor. Simulation results show the proposed ABC-NFC method performs better than ANFIS, ANN, FLC and NFC in compensating for voltage sags.
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HEURISTIC BASED OPTIMAL PMU ROUTING IN KPTCL POWER GRID
Power system monitoring is an important process in an efficient smart grid. The control centers used in smart grid requires restructuring. State measurements rather than state estimationare pre-requisite for the modern control center. The Phasor Measurement Unit (PMU) measures the synchronized voltage and current parameters. Placement of minimum number of PMUs in a bus system such that the wholes system becomes observable is considered as Optimal PMU Placement (OPP) problem. In this paper, Hybrid Distance Optimization (HDO) algorithm is proposed to reduce the number of PMUs for complete observability along with the minimum length of fiber optic cable required for interconnecting the PMU nodes
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Analysis and Implementation of Artificial Neural Network Techniques for Power...
This project shows how to use a back propagation BP control method to execute a three stage delivery static compensator DSTATCOM for its capabilities such as load balancing and zero voltage management of reactive power compensation under non linear loads. In this case, we utilize a BP based control method to determine the crucial dynamic weight. Furthermore, the BP based control method is often used to estimate the receptive power parts of the load streams required for estimating the reference source streams. The new topic of research in the field of power engineering is the regulation of power efficiency devices using neural networks. The output of the balancing instruments is defined by the extraction of the harmonic components. DSTATCOM and UPFC are used as balancing devices in this case. A DSTATCOM model is created with the help of a computerized signal processor, and its implementation is tailored to specific working circumstances. With the suggested control method, the execution of DSTATCOM is shown to be appropriate for a variety of workloads. The BP based control method is used to calculate the basic weighted value of the loads active and reactive power components. The sample trained back propagation method will identify the power quality signal problem in real time. This algorithms main characteristics include continuity, differentiability, and non decreasing momotomy. The UPFC procedure is similar to that of DSTATCOM, with the exception that the device is not turned off under adverse conditions. The simulation model is created using ANFIS, and its output is investigated under various operating circumstances. For various kinds of loads, the ANFIS output is determined to be acceptable using the suggested control method. The proposed technique must be validated using MATLAB Simulink findings. Amrendra Kumar | Pramod Kumar Rathore "Analysis and Implementation of Artificial Neural Network Techniques for Power Quality Enhancement using DSTATCOM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45218.pdf Paper URL: https://www.ijtsrd.com/engineering/other/45218/analysis-and-implementation-of-artificial-neural-network-techniques-for-power-quality-enhancement-using-dstatcom/amrendra-kumar
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Presentation 1 of Phd Ali literature review.pptx
This document summarizes several research papers on maximum power point tracking (MPPT) algorithms for photovoltaic systems. The papers presented and compared different MPPT methods including perturb and observe, incremental conductance, fuzzy logic control, particle swarm optimization, sliding mode control, and adaptive neuro-fuzzy inference system approaches. Simulation and experimental results demonstrated that advanced algorithms like fuzzy logic, particle swarm optimization and sliding mode control methods provided faster tracking speeds, lower power fluctuations, and better performance under changing environmental conditions compared to traditional perturb and observe based MPPT methods.
proposedfaultdetectiononoverheadtransmissionlineusingparticleswarmoptimizatio...
This document proposes using Particle Swarm Optimization (PSO) to detect faults on overhead transmission lines. It will involve simulating various fault types using PSCAD/EMTDC software, developing mathematical models of the voltage and current signals, and applying PSO in MATLAB to analyze the signals and detect faults. Preliminary results show simulation of five fault types. The developed method is expected to accurately detect faults before disturbances occur to maintain power system stability.
Rediet's seminar power point presentation .pptx
This document reviews and compares various artificial intelligence techniques for maximum power point tracking in solar power systems. It discusses fuzzy logic control, artificial neural networks, genetic algorithms, and other emerging techniques. It finds that while AI-based MPPT techniques can track the global maximum power point more accurately than conventional methods, especially under partial shading conditions, they tend to be more complex and costly to implement. The review concludes by recommending newer hybrid, swarm intelligence, machine learning and deep learning algorithms for their adaptive learning abilities and fully digitalized systems.
Low Frequency Oscillations Damping by UPFC with GAPOD and GADC-voltage regulator
This document describes a new controller for a Unified Power Flow Controller (UPFC) to damp low frequency oscillations in power systems. The proposed controller is a Multi-Stage Fuzzy (MSF) PID controller with a genetic algorithm-based DC voltage regulator. The MSF controller uses multiple fuzzy logic controllers and a fuzzy switch to better handle system uncertainties. Membership functions for the fuzzy controllers are optimized using a genetic algorithm. Testing on a single machine infinite bus power system model shows the proposed controller more effectively damps low frequency oscillations under different operating conditions compared to other UPFC controllers. The design and implementation of the proposed controller is described to be simpler than other advanced control methods while still providing robust damping performance.
PROPOSED FAULT DETECTION ON OVERHEAD TRANSMISSION LINE USING PARTICLE SWARM ...
PROPOSED FAULT DETECTION ON OVERHEAD TRANSMISSION LINE USING PARTICLE SWARM ...Politeknik Negeri Ujung Pandang
Transmission line is one the important compnent in protection of electric power system because the transmission line connects the power station with load centers.
The fault includes storms, lightning, snow, damage to insulation, short circuit fault [1].
Fault needs to be predicted earlier in order to be prevented before it occurComparison of Different Design Methods for Power System Stabilizer Design - A...
In the past two decades, the utilization of supplementary excitation control signals for improving the dynamic stability of power systems has received much attention. In recent years, several approaches based on intelligent control and optimization techniques have been applied to PSS design problem. This paper introduces a review on the techniques applied on the conventional PSS design only. Power System Stabilizer (PSS) is the most cost effective approach of increase the system positive damping, improve the steady-state stability margin, and suppress the low-frequency oscillation of the power system. A PSS has to perform well under operating point variations. This paper introduces a review on the techniques applied on the conventional PSS design only. The techniques could be mainly classified into linear and nonlinear.
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This document is a seminar report submitted by Dhiraj Machhindra Bhalerao to North Maharashtra University in partial fulfillment of the requirements for a Bachelor of Engineering degree in Electrical Engineering. The seminar topic is "POWER SYSTEM AUTOMATION". The report includes a certificate from the seminar guide, a declaration by the author, acknowledgements, an abstract, and multiple chapters on topics related to power system automation including literature review, components of a power system, automation, and the status of automation in India.
Dhiraj power system automation
This document provides information about a seminar submitted by Dhiraj Machhindra Bhalerao to North Maharashtra University in partial fulfillment of the requirements for a Bachelor of Engineering degree in Electrical Engineering. The seminar topic was "POWER SYSTEM AUTOMATION" and was conducted under the guidance of Prof. G. K. Andulkar of the Electrical Engineering department at Government College of Engineering, Jalgaon. The document includes a certificate of completion, declaration, acknowledgements, abstract, and table of contents outlining the various chapters to be included in the seminar report.
To Study, Analysis and Implementation of Power Quality Improvement Using DSTA...
This project illustrates the execution of a three stage delivery static compensator DSTATCOM by using a back propagation BP control algorithm for its capacities, such as load balancing and zero voltage management of reactive power compensation under non linear loads. We use BP based control algorithm to obtain the critical dynamic weight estimate here. And the BP based control algorithm is often used for estimating the receptive power portions of the load streams necessary for estimating the reference source streams. Regulation of power efficiency devices through neural networks is the new area of study in the field of power engineering. The extraction of the harmonic components defines the output of the balancing instruments. Here we use DSTATCOM and UPFC as balancing instruments. A DSTATCOM model is developed using a computerized signal processor and its implementation is focused on various working conditions. The execution of DSTATCOM is found to be suitable for various kinds of burdens with the proposed control algorithm. The BP based control algorithm is used to derive the fundamental weighted value of the active and reactive power components of the load present. Back propagation algorithm trained by the sample will detect the power quality signal issue in real time. Continuity, differentiability, non decreasing momotomy are the key features of this algorithm. The process of UPFC is close to that of DSTATCOM, although the only difference is that it does not have the device shut down in worse circumstances. The simulation model is developed with ANFIS and its output is studied under different operating conditions. The output of ANFIS is found to be satisfactory with the proposed control algorithm for different types of loads. The suggested method shall be checked by the results of MATLAB Simulink. Rohit Mishra | Ashish Bhargava "To Study, Analysis and Implementation of Power Quality Improvement Using DSTATCOM with ANN (Back Propagation Algorithm)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-6 , October 2021, URL: https://www.ijtsrd.com/papers/ijtsrd47521.pdf Paper URL : https://www.ijtsrd.com/engineering/electrical-engineering/47521/to-study-analysis-and-implementation-of-power-quality-improvement-using-dstatcom-with-ann-back-propagation-algorithm/rohit-mishra
A Comprehensive review on Optimization Algorithms for Best Location of FACTS ...
This document reviews 59 studies on optimization algorithms for determining the optimal placement of flexible AC transmission system (FACTS) controllers. It categorizes the algorithms into analytical optimization techniques using sensitivity analysis, metaheuristic optimization techniques including evolutionary algorithms like genetic algorithm and differential evolution, and swarm-based algorithms like particle swarm optimization. It summarizes several studies applying these various techniques to test cases like IEEE 5, 14, 30 bus systems to optimally place FACTS controllers like thyristor controlled series compensator (TCSC), static VAR compensator (SVC), unified power flow controller (UPFC) with objectives of minimizing losses, improving voltage profile, enhancing security and loadability.
Resume- EE
- Motivated Electrical Engineer with 1 year of experience in power transmission planning, generator interconnection studies, and NERC compliance studies seeking a position in power systems engineering.
- Master's degree in Electrical Engineering with a focus on power systems and experience in software development.
- Skilled in transmission planning tools like PSSE and experience analyzing power flows, contingencies, and reliability standards.
Comparative Study on the Performance of A Coherency-based Simple Dynamic Equi...
Earlier, a simple dynamic equivalent for a power system external area containing a group of coherent generators was proposed in the literature. This equivalent is based on a new concept of decomposition of generators and a two-level generator aggregation. With the knowledge of only the passive network model of the external area and the total inertia constant of all the generators in this area, the parameters of this equivalent are determinable from a set of measurement data taken solely at a set of boundary buses which separates this area from the rest of the system. The proposed equivalent, therefore, does not require any measurement data at the external area generators. This is an important feature of this equivalent. In this paper, the results of a comparative study on the performance of this dynamic equivalent aggregation with the new inertial aggregation in terms of accuracy are presented. The three test systems that were considered in this comparative investigation are the New England 39-bus 10-generator system, the IEEE 162-bus 17-generator system and the IEEE 145-bus 50-generator system.
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