abstract: In modern electric power systems, energy management systems (EMSs) are responsi-ble for monitoring and controlling the generation system and transmission networks. State estimation (SE) is a critical `must run successful' component within the EMS software. This is dictated by the high reliability requirements and need to represent the closest real time model for market operations and other critical analysis functions in the EMS. Tradi-tionally, SE is run with data obtained only from supervisory control and data acquisition (SCADA) devices and systems. However, more emphasis on improving the performance of SE drives the inclusion of phasor measurement units (PMUs) into SE input data. PMU measurements are claimed to be more accurate than conventional measurements and PMUs `time stamp' measurements accurately. These widely distributed devices meas-ure the voltage phasors directly. That is, phase information for measured voltages and currents are available. PMUs provide data time stamps to synchronize measurements. Con-sidering the relatively small number of PMUs installed in contemporary power systems in North America, performing SE with only phasor measurements is not feasible. Thus a hy-brid SE, including both SCADA and PMU measurements, is the reality for contemporary power system SE. The hybrid approach is the focus of a number of research papers. There are many practical challenges in incorporating PMUs into SE input data. The higher reporting rates of PMUs as compared with SCADA measurements is one of the salient problems. The disparity of reporting rates raises a question whether buffering the phasor measurements helps to give better estimates of the states. The research presented in this thesis addresses the design of data buffers for PMU data as used in SE applications in electric power systems. The system theoretic analysis is illustrated using an operating electric power system in the southwest part of the USA. Var-ious instances of state estimation data have been used for analysis purposes. The details of the research, results obtained and conclusions drawn are presented in this document. / Dissertation/Thesis / M.S. Electrical Engineering 2013

Recently, there has been a significant rise in the Hyper-Text Transfer Protocol (HTTP) video streaming usage worldwide. However, the knowledge of performance of HTTP video streaming is still limited, especially in the aspect of factors which affect video quality. The reason is that HTTP video streaming has different characteristics from other video streaming systems. In this thesis, we show how the delivered quality of a Flash video playback is affected by different factors from diverse layers of the video delivery system, including congestion control algorithm, delay variation, playout buffer length, video bitrate and so on. We introduce Quality of Delivery Degradation (QoDD) then we use it to measure how much the Quality of Delivery (QoD) is degraded in terms of QoDD. The study is processed in a dedicated controlled environment, where we could alter the influential factors and then measure what is happening. After that, we use statistic method to analyze the data and find the relationships between influential factors and quality of video delivery which are expressed by mathematic models. The results show that the status and choices of factors have a significant impact on the QoD. By proper control of the factors, the quality of delivery could be improved. The improvements are approximately 24% by TCP memory size, 63% by congestion control algorithm, 30% by delay variation, 97% by delay when considering delay variation, 5% by loss and 92% by video bitrate.