Estimation of Synchronous Generator Parameters using Time-domain Responses
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
Power system stability simulations are of growing importance for studying the operational integrity of modern power systems, especially in developing economies where generating and transmission capacity lead the demand by relatively small margins. The relevant model topologies, i.e. for synchronous generators, automatic voltage regulators (AVR) and governor control systems, and the simulation software tools are well established. The MATLAB® Power System Blockset provides engineers with a versatile power system stability simulation environment, particularly where the focus is on individual units or small systems. In comparison with dedicated power system simulation tools such as DIgSILENT®, the MATLAB® environment features a superior set of advanced data processing and data analysis features. This includes features such as optimisation and parameter estimation functions. The main aim of this project is to make use of the MATLAB® package in a bid to test an alternative platform with which to estimate the synchronous machine parameters. Conditioning of field data can delay the process considerably, thus the secondary task of this thesis is to solve this issue by ensuring that only one platform is needed for the entire process starting in the field and ending in the modelling and parameter estimation environment within MATLAB®. In closing, the following points summarise the essential aims of this project: • An application using MATLAB® Script must be created that is responsible for importing and processing the data, so it is suitable for analysis purposes. The processing could include cropping, scaling and filtering of data. • Once the data has been imported it must be used with appropriate models to estimate for machine parameters. This will require the use of the Power Systems Blockset. The actual estimation process also requires the creation of an effective cost function, thus a number of different scenarios will have to be investigated before a solution can be found.