This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called ???efficient least squares algorithm???. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies. The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems

Recent widespread blackouts have indicated the need for more efficient and accurate power system monitoring, control and protection tools. Power system state estimation, which is the major tool that is used nowadays for providing the real-time model of the system, has significant biases resulting mainly from the complexity and geographic spread and separation of an electric power system. Synchrophasor technology is a promising technology that has numerous advantages compared to conventional metering devices. PMUs provide synchronized measurements, where synchronization is achieved via a GPS clock which provides the synchronizing signal with accuracy of 1 μsec. As a result, the computed phasors have a common reference (UTC time) and can be used in local computations, thus distributing the state estimation process. The first part of the work presents a PMU enabled dynamic state estimator (DSE) that can capture with high fidelity the dynamics of the system and extract in real time the dynamic model of the system. The described DSE is performed in a decentralized way, on the substation level based on local measurements which are globally valid. The substation based DSE uses data from relays, PMUs, meters, FDRs etc in the substation only, thus avoiding all issues associated with transmission of data and associated time latencies. This approach enables very fast DSE update rate which can go up to more than 60 executions per second. The distributed state estimation architecture that synchrophasor technology enables, along with the fast sampling rate and the accuracy of the measurements that PMUs provide, enable the computation of the real-time dynamic model of the system and the development of numerous power system applications for more efficient control and protection of the system. In the second part of the work, a transient stability monitoring scheme is presented that utilizes the information given by the dynamic state estimation and enables real-time monitoring of the transient swings of the system and characterizes the stability of the system in real time. In particular, the real-time dynamic model of the system, as given by the DSE, is utilized to evaluate the system's energy function based on Lyapunov's direct method and extract stability properties from the energy function. The two major components of the scheme are a) the calculation of the center of oscillations of the system and b) the derivation of an equivalent, reduced sized model which is used for the calculation of the potential and kinetic energy of the system based on which the stability of the system is determined. Finally, as an application of the transient stability monitoring scheme, an energy based out-of-step protection scheme is proposed. The energy of the generator is continuously monitored and if it exceeds a predefined threshold then instability is asserted and a trip signal can be sent to the generator. The major advantage of the scheme is that the out-of-step condition is predicted before its occurrence and therefore relays can act much faster than today's technology. The scheme is compared to presently available state of the art out-of-step protection schemes in order to verify its superiority.

The Masters Thesis research focuses on reactive power and voltage control during and following major power system disturbances such as faults and subsequent loss of transmission line(s) or generator(s), voltage recovery phenomena following successful fault clearing, dynamic swings of power systems and local voltage suppression, etc. During these events, load and other system dynamics may cause reactive power deficiencies and system voltage issues such as delayed voltage recovery. These phenomena may lead to secondary events such as tripping of loads and/or circuits. Dynamic VAr sources such as generators, static VAr compensators (SVCs), STATCOMs etc and to a lesser degree static VAr sources such as capacitor or reactor banks, can help the system recover from these contingencies by providing fast modulation of the reactive power. Because of the higher cost of dynamic VAr resources, it is important to optimize the deployment of these devices by minimizing the total installed capacity of dynamic VAR resources while meeting the technical requirement and achieving the necessary performance of the system. We refer to this problem as the optimal allocation of dynamic VAR sources (OAODVARS). OAODVARS has been addressed with traditional analytic methods as well as with Artificial Intelligence methods such as genetic algorithms and Tabu search using mostly power flow type models. Both type of methods, as reported in the literature, have not provided satisfactory solutions because they ignore system dynamics and especially load dynamics, in other words they are based on power flow type models. In addition the AI methods have been proved to be extremely inefficient. We propose a new approach that has the following two advantages: (a) it is based on a realistic model that captures system dynamics and (b) it is based on the efficient successive approximation dynamic programming. The solution is provided as a sequence of planning decisions over the planning horizon. The proposed method will be demonstrated on the IEEE 24-bus reliability test system.

M. Tech. Electrical Engineering / Investigates the growing consensus that significant advantages can be achieved through the automation of distribution feeder switches In order to ensure quality and reliability of supply to single phase consumers by electrical utilities, a need arose to minimize unbalance. it is then postulated the unbalance due to uneven distribution of single-phase loads at the secondary side of the distribution network can be minimized using automatic and remote sensing technology.

No description available.

This research work deals with the application of the phase shifting transformer in improving the steady state performance and voltage stability of transmission network that has transmission lines at different voltage levels running in parallel to each other. Transmission power system networks are usually developed using lines built at a certain voltage level initially. As power demand requirements increase, building of the new lines at the same voltage level becomes necessary. However, lesser and lesser improvements in transfer capacity are realised when the additional lines are built. This prompts utilities to consider higher voltages for future lines as these have a higher transfer capacity. Utilities usually lay, i.e., they build in parallel, newer, higher voltage transmission lines along side the existing lower voltage ones. Power flow in power system is mainly influenced by impedances of equipment. If the combined impedance of the existing, lower voltage transmission system is relatively less than the impedance of the newer, higher voltage ones, power may primarily flow through it rather than via the newer, parallel higher voltage transmission network. This may lead to a serious underutilisation of the newer infrastructure with a higher transmission capacity. Transmission networks similar to the one described above are common throughout the world. This study was undertaken towards finding solutions to the problem of under utilisation of such transmission lines. The study was performed by first reviewing the literature on the use of phase shifting transformers to redirect power flow in transmission networks throughout the world. This was followed by analysis of the theory on how and what determines the power flow in power networks. Several simulations of varying the phase of the phase shifting transformer were performed on the Cape network, as a case study, to investigate the impact on the power flow distribution and voltage stability performance of the 765 kV and 400 kV transmission lines carrying power to the Western Cape. In this dissertation, it has been demonstrated that a phase shifting transformer can be used to alter the power flow patterns so that power flows are restructured or redistributed, such that power which originally flowed via the low impedance, lower voltage system is transferred to the parallel higher voltage transmission system of lines. It is shown that once the power flows are redistributed, steady state and voltage stability performance of the total system can be enhanced and an increase in its power transfer capacity can be realised. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2011.

This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called ???efficient least squares algorithm???. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies. The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems

Thesis (M.S.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 153-154).

Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 127-140) Also available in print.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 127-140) Also available online.