Control and monitoring of solar photovoltaic panel using PLC

A renewable energy source plays an important role in electricity generation. Various renewable energy sources like wind, solar, geothermal, ocean thermal, and biomass can be used for generation of electricity and for meeting our daily energy needs. Energy from the sun is the best option for electricity generation as it is available everywhere and is free to harness. On an average the sunshine hour in Malaysia is about eight hours annually also the sun shine shines in Malaysia for about nine months in a year. Electricity from the sun can be generated through the solar photovoltaic modules (SPV). The SPV comes in various power output to meet the load requirement. Maximization of power from a solar photo voltaic module (SPV) is of special interest as the efficiency of the SPV module is very low. A peak power tracker is used for extracting the maximum power from the SPV module. The present work describes the potential system benefits of simple tracking solar system using stepper motor and light sensor. This method increases power collection efficiency by developing a device that tracks the sun to keep the panel at the right angle to its rays. A solar tracking system is designed, implemented and experimentally tested. The design details and the experimental results are shown

Analysis and robust decentralized control of power systems using FACTS devices

Today\u27s changing electric power systems create a growing need for flexible, reliable, fast responding, and accurate answers to questions of analysis, simulation, and design in the fields of electric power generation, transmission, distribution, and consumption. The Flexible Alternating Current Transmission Systems (FACTS) technology program utilizes power electronics components to replace conventional mechanical elements yielding increased flexibility in controlling the electric power system. Benefits include decreased response times and improved overall dynamic system behavior. FACTS devices allow the design of new control strategies, e.g., independent control of active and reactive power flows, which were not realizable a decade ago. However, FACTS components also create uncertainties. Besides the choice of the FACTS devices available, decisions concerning the location, rating, and operating scheme must be made. All of them require reliable numerical tools with appropriate stability, accuracy, and validity of results. This dissertation develops methods to model and control electric power systems including FACTS devices on the transmission level as well as the application of the software tools created to simulate, analyze, and improve the transient stability of electric power systems.;The Power Analysis Toolbox (PAT) developed is embedded in the MATLAB/Simulink environment. The toolbox provides numerous models for the different components of a power system and utilizes an advanced data structure that not only increases data organization and transparency but also simplifies the efforts necessary to incorporate new elements. The functions provided facilitate the computation of steady-state solutions and perform steady-state voltage stability analysis, nonlinear dynamic studies, as well as linearization around a chosen operating point.;Applying intelligent control design in the form of a fuzzy power system damping scheme applied to the Unified Power Flow Controller (UPFC) is proposed. Supplementary damping signals are generated based on local active power flow measurements guaranteeing feasibility. The effectiveness of this controller for longitudinal power systems under dynamic conditions is shown using a Two Area - Four Machine system. When large disturbances are applied, simulation results show that this design can enhance power system operation and damping characteristics. Investigations of meshed power systems such as the New England - New York power system are performed to gain further insight into adverse controller effects

Fuzzy-based estimation of reference flux, reference torque and sector rotation for performance improvement of DTC-IM drive

In this study, the fuzzy-based reference flux estimator (RFE), reference torque estimator (RTE) and sector rotation strategy called fuzzy logic estimator are proposed to direct torque control of induction motor (DTC-IM) drive for performance improvement. The basic DTC-IM drive with conventional RFE, RTE and sector division causes large torque ripple, variable switching frequency and uneven voltage vector contribution in stator flux. The torque and speed responses of the proposed system are investigated with load variations. The simulation results of the proposed DTC-IM drive are compared with the basic DTC-IM drive. The assessment of the proposed system shows improved performance. A hardware is developed using Xilinx Spartan-6XC6SLX45-Field Programmable Gate Array (FPGA) Kit for experimental verification of the results. Moreover, sinusoidal pulse width modulation and space vector pulse width modulation techniques are applied to reduce the torque ripples. The performance of the drive is investigated for various speed ranges. The comparison of the simulated and experimental results proves that the proposed fuzzy-based DTC-IM drive provides better performance than the basic DTC-IM drive

Hardware Implementation of a Mamdani Fuzzy Logic Controller for a Static Compensator in a Multimachine Power System

A Mamdani-type fuzzy logic controller is designed and implemented in hardware for controlling a static compensator (STATCOM), which is connected to a ten-bus multimachine power system. Such a controller does not need any mathematical model of the plant to be controlled and can efficiently provide control signals for the STATCOM over a wide range of operating conditions of the power system and during different disturbances. The proposed controller is implemented using the M67 digital signal processor board and is interfaced to the multimachine power system simulated on a real-time digital simulator. Experimental results are provided, showing that the proposed Mamdani fuzzy logic controller provides superior damping compared to the conventional proportional-integral (PI) controller for both small and large scale disturbances. In addition, the proposed controller manages to restore the power system to the steady state conditions with less control effort exerted by the STATCOM, which, in turn, leads to smaller megavar rating and, therefore, less cost for the device. The matrix pencil method analysis of the damping provided by the different controllers indicates that the proposed controller provides higher damping than the PI controller and also mitigates the modes present with the conventional PI control

High performance position control for permanent magnet synchronous drives

In the design and test of electric drive control systems, computer simulations provide a useful way to verify the correctness and efficiency of various schemes and control algorithms before the final system is actually constructed, therefore, development time and associated costs are reduced. Nevertheless, the transition from the simulation stage to the actual implementation has to be as straightforward as possible. This document presents the design and implementation of a position control system for permanent magnet synchronous drives, including a review and comparison of various related works about non-linear control systems applied to this type of machine. The overall electric drive control system is simulated and tested in Proteus VSM software which is able to simulate the interaction between the firmware running on a microcontroller and analogue circuits connected to it. The dsPIC33FJ32MC204 is used as the target processor to implement the control algorithms. The electric drive model is developed using elements existing in the Proteus VSM library. As in any high performance electric drive system, field oriented control is applied to achieve accurate torque control. The complete control system is distributed in three control loops, namely torque, speed and position. A standard PID control system, and a hybrid control system based on fuzzy logic are implemented and tested. The natural variation of motor parameters, such as winding resistance and magnetic flux are also simulated. Comparisons between the two control schemes are carried out for speed and position using different error measurements, such as, integral square error, integral absolute error and root mean squared error. Comparison results show a superior performance of the hybrid fuzzy-logic-based controller when coping with parameter variations, and by reducing torque ripple, but the results are reversed when periodical torque disturbances are present. Finally, the speed controllers are implemented and evaluated physically in a testbed based on a brushless DC motor, with the control algorithms implemented on a dsPIC30F2010. The comparisons carried out for the speed controllers are consistent for both simulation and physical implementation

Control of switched reluctance machines

This thesis is concerned with the control of switched reluctance machines for both motoring and generating applications. There are different control objectives in each case. For motoring operation, there are two possible control objectives. If the SRM is being employed in a servo-type application, the desire is for a constant output torque. However, for low performance applications where some amount of torque ripple is acceptable, the aim is to achieve efficient and accurate speed regulation. When the SRM is employed for generating purposes, the goal is to maintain the dc bus voltage at the required value while achieving maximum efficiency. Preliminary investigative work on switched reluctance machine control in both motoring and generating modes is performed. This includes the implementation and testing through simulation of two control strategies described in the literature. In addition, an experimental system is built for the development and testing of new control strategies. The inherent nonlinearity of the switched reluctance machine results in ripple in the torque profile. This adversely affects motoring performance for servo-type applications. Hence, three neuro-fuzzy control strategies for torque ripple minimisation in switched reluctance motors are developed. For all three control strategies, the training of a neurofuzzy compensator and the incorporation of the trained compensator into the overall switched reluctance drive are described. The performance of the control strategies in reducing the torque ripple is examined with simulations and through experimental testing. While the torque ripple is troublesome for servo-type applications, there are some applications where a certain amount of torque ripple is acceptable. Therefore, four simple motor control strategies for torque ripple-tolerant applications are described and tested experimentally. Three of the control strategies are for low speed motoring operation while the fourth is aimed at high speed motoring operation. Finally, three closed-loop generator control strategies aimed at high speed operation in single pulse mode are developed. The three control strategies are examined by testing on the experimental system. A comparison of the performance of the control strategies in terms of efficiency and peak current produced by each is presented