WIDE AREA VOLTAGE MONITORING AND OPTIMIZATION
With the continual global increase in the demand for electricity, power systems are becoming more complex. In addition, factors such as power market deregulation, unscheduled voltage regulation, transmission line outages may lead to power transfer across areas being even more unpredictable. These issues all contribute to transmission lines carrying electric power nearer to their limits, which causes power systems to being operated under serious stress. Many recent major blackouts are caused by voltage collapse, and this justifies the need for a fast and accurate voltage stability monitoring approach for the modern power system. Conventional voltage monitoring and control is based on SCADA and EMS controls nowadays. As a result of the limitations of these measurements, which include slow data sampling rate, slow data communication, and slow state estimation processing, it may take minutes for a whole snapshot of the measured electrical power system to be obtained. Hence, operators do not really have access to the real time and detailed voltage and current vectors required for on-line voltage control, which makes the actual implementation of on-line voltage control unrealistic. However, with the development and installation of Phasor Measurement Units (PMUs) in power systems, data can be made available at high-sampling rates, allowing for more efficient on-line monitoring of voltages. The development and applications of wide area measurement systems (WAMS) provides the foundation for on-line assessment of voltage stability in large scale power systems.In order to not let the long computational time of the conventional monitoring and optimization methods offset the advantage of the PMUs and WAMS. A model-free voltage monitoring method together with a brand new voltage optimization method is provided in this dissertation. Since the proposed voltage monitoring method get data from PUM directly and purely, the whole monitoring progress is very fast and accurately. And the concept of parallel optimization is introduced in this dissertation as well. With the help of that, the optimization progress can be done fast and accurately, too. Case studies of several different IEEE standard systems show the efficiency and accuracy of the proposed methods.