Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/312
Authors: C, Thanga Raj
Issue Date: 2009
Abstract: Nowadays, the main concern of policy makers across the world is global warming due to the emission of C02 in the atmosphere and researchers have an important role to play in this regard. Furthermore, India is facing severe energy shortage eventhough the installed capacity of Indian power sector is increasing continuously. To mitigate the shortages, Government of India has set a goal "Mission 2012: Power for All' and one of its objectives is optimal utilization of electrical energy. The energy shortage in India is due to the inefficiencies in power generation, distribution and end use system. Economical and more practical method to limit the energy shortage is "energy conservation", particularly for industrial consumers who account for more than 50 percent of the total energy consumption. In end use systems, the induction motor can be considered as one of the largest consumers of electrical energy due to its well known advantageous including robustness, reliability, low price and maintenance free operation. The induction motors are used in both industrial and commercial sectors in a wide range of applications, such as fans, compressors, pumps, conveyors, winders, mills, transports, elevators, home appliances and office equipments. The influence of these motors (in terms of energy consumption) in energy intensive industries is significant in total input cost. Asmall increment in the efficiency of these motors by providing better control or optimum design can result in substantial saving in the long period. Induction motor is a high efficiency electrical machine when working closed to its rated torque and speed. However, at light loads, imbalance in copper and iron losses, results considerable reduction in its efficiency. The part-load efficiency and power factor can be improved by making the motor excitation adjustment in accordance with load and speed. To achieve this objective, the induction motor should either be fed through an inverter or redesigned with optimization algorithms. The research in the present work is carried out both in optimal design and control of induction motor to achieve maximum efficiency or minimum operating cost. The optimization of induction motor design with Artificial Intelligence (Al) and Nature Inspired Algorithms (NIA) has received considerable attention recently. The optimized design of a three-phase induction motor can be obtained by using standard non-linear programming techniques. But these techniques are computationally very expensive and inefficient whereas NIA is competent tool to solve non-linear programming problems. Different NIA based optimization algorithms for induction motor design have been reported in literature. Particle Swarm Optimization (PSO) technique has become very popular since last decade to solve multi dimension non linear programming problems due to its less complexity, fast convergence, etc., than Genetic Algorithm and Evolutionary Programming. Although the rate of convergence of PSO is good due to fast information flow among the solution vectors, its diversity decreases very quickly in the successive iterations resulting in a suboptimal solution. Aiming at this shortcoming of PSO algorithms, many variations have been developed by the researchers to improve its performance. Improved version of PSO called Quadratic Interpolation based Particle Swarm Optimization (QIPSO) is used in the present work which gave better results than reported in the literature in terms offitness value. SPEED/IMD (Scottish Power Electronics and Electric Drives), a motor design software is used to validate the optimization algorithms in induction motor design. Moreover, many researchers have focused their research on efficiency optimization of induction motors that are working in industries through optimal flux control. In optimal flux control, there are three main approaches to improve the induction motor efficiency at light loads, namely loss model controller (LMC), search controller and hybrid controller (retain good features of loss model and search control by mixing them). Since the induction motor is a large consumer of electrical energy in the industries and its influence is more in energy intensive industries, it is required to focus industrial loads. Economic analysis of some of the industrial loads such as textile and mining industries are carried out in the present work. To maintain good stability (minimum torque ripples and less overshoots in speed) of the motor during flux adjustment, Fuzzy Pre-compensated Proportional Integral (FPPI) controller is used. Acomprehensive literature survey on the induction motor drives, design of materials during construction and efficient control of part-load machine, is carried out in the present work. Common sources affecting induction motor efficiency and their solutions to improve it are discussed in brief. An experimental study is investigated on induction motor with unbalance voltages to study the negative effects of it on motor's efficiency. Economic losses due to voltage unbalance are determined and the available potential of efficiency improvement opportunities in the industrial sectors is discussed. Induction motor design optimization is carried out in the present work with the help of QIPSO algorithms and explored its superiority in comparison with normal design, Rosenbrock, basic PSO and Simulated Annealing (SA) methods. The design of the induction motors includes determination of geometry and data required for manufacturing the machine so as to satisfy the vector of performance variables together with a set of constraints. Optimal design of motors refers to ways of doing efficiently synthesis by repeated analysis such that the objective function is maximized or minimized while all constraints are satisfied. There are large number of design parameters involved in the design of the induction machine. Selection of objective functions, variables and constraints are the main steps. The proper optimization of induction motor design is achieved by intelligent selection of objective function and constraints according to the requirement, and further selection of variables which affect the objective function and the constraints. Material cost, efficiency, starting torque, temperature rise and operating cost are taken as objective functions and nine performance indices as constraints. The design variables which are most sensitive to the objective functions have been judiciously chosen. They are: ampere conductors, ratio of stack length to pole pitch, stator slot depth to width ratio, stator core depth, average air gap flux densities, stator winding current density, and rotor winding current density. The objective functions and constraints are expressed in terms of the above variables. The effectiveness of PSO and QIPSO in terms of variable and constraint values selection is realized by using SPEED software. By using the ranging function of SPEED, effect of various design parameters are plotted against the objective function and some of the constraints. The performance based optimal design of induction motor is also carried out to reduce the required number of variables to design the motor. To achieve this, motor design is carried out by QIPSO algorithm with seven variables. The design realization is then done by SPEED software and selects minimum variables which are affecting the performance of the motor in depth. Again the motor is optimized by QIPSO with reduced variables. In practice, induction motors experience unbalanced terminal voltage when fed from power supply and subjected to harmonics when fed through inverter. It results increased losses due to time harmonics/negative sequence currents. These losses reduce motor's life and hence, derating must be applied to avoid the damages. Moreover, to ensure consistent, efficient and reliable operation of motors, accounting unbalanced stator voltage and harmonics in supply, optimized design of the motor receives considerable attention from industry. The present work investigates the performance and design of the induction motor under both unbalance and harmonics in the supply. For unbalance voltage consideration, positive and negative sequence currents are derived and incorporated in the motor design. For inverter supply, harmonic currents are derived from the equivalent circuit and use them as additional constraint so that motor design is carried out with limited harmonics.
Other Identifiers: Ph.D
Research Supervisor/ Guide: Srivastava, S. P.
metadata.dc.type: Doctoral Thesis
Appears in Collections:DOCTORAL THESES (E & C)

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