A solar and diesel-wind hybrid power control systems is proposed in the thesis. The system consists of solar power, wind power, diesel-engine, a static synchronous compensator and an intelligent power controller. MATLAB/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system. A static synchronous compensator was used to supply reactive power and regulate the voltage of the hybrid system. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Radial Basis Function Network (RBFN) and the Elman Neural Network (ENN) for maximum power point tracking (MPPT). The pitch angle control of wind power uses ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar system uses RBFN, and the output signal is used to control the DC / DC boost converters to achieve the MPPT.

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.

No description available.

Power system harmonics and interharmonics are power quality concerns that have received a great deal of attention in recent years. These phenomena can have several adverse effects on power system operation. The main harmonic and interharmonic sources are devices based on power electronics. An emerging class of harmonic sources is comprised of power electronic-based home appliances. These appliances are dispersed throughout the low-voltage distribution system, and their collective impact can result in unacceptable levels of voltage distortion. The characterization of home appliances based on their harmonic currents is an important step toward understanding the impact of these devices. This thesis presents an evaluation of the relative severity of the harmonic currents from these devices, and the impact of the disparity of the harmonic current phase angles. Typically, the voltage supplied to each harmonic source is already distorted. This distortion causes a change of the harmonic current magnitudes (traditionally referred to as the attenuation effect). Common harmonic analysis methods cannot take this variation into account because they use a typical harmonic current source model specified by a supply voltage having little or no distortion. This thesis characterizes the harmonic attenuation effect of power electronic-based appliances. One of the findings is that harmonic amplification, rather than attenuation, can occur under credible voltage conditions. This finding had not been made previously. In order to include the harmonic attenuation/amplification in appliance modeling, a measurement-based harmonic modeling technique is proposed. One of the most economic and effective ways to mitigate harmonics in power systems is through the use of harmonic shunt passive filters. These filters can be of many topologies. Selecting these topologies is a task that, today, depends on the experience and judgment of the filter designer. An investigation is carried out on the common filter topologies, and the most cost-effective topologies for mitigating harmonics are identified. As many of the larger harmonic loads also generate interharmonics, interharmonics have become prevalent in today’s medium-voltage distribution system. Mitigation cannot be carried out until the interharmonic-source location is known. A method for interharmonic source determination is proposed and then verified through simulation and field measurement studies.

The main function of the power grid is to transfer electric energy from generating facilities to consumers. To have a reliable and economical supply of electricity, large amounts of electric energy often have to be transferred over long distances. The transmission system has a limited capacity to transfer electric power, called the transfer capacity. Severe system failures may follow if the transfer capacity is reached during operation. Due to uncertainties, such as the random failure of system components, the transfer capacity for the near future is not readily determinable. Also, due to market principles, and reaction times and ramp rates of production facilities, power flow control is not fully flexible. Therefore, a transfer limit, which is below the transfer capacity, is decided and preventative actions are taken when the transfer reaches this limit. In this thesis an approach to deciding an optimal strategy for power flow control through activation of regulating bids on the regulating power market is outlined. This approach leads to an optimal definition of transfer limits as the boundary between the domain where no bid should be activated and the domains where bids should be activated. The approach is based on weighing the expected cost from system failures against the production cost. This leads to a stochastic impulse control problem for a Markov process in continuous time. The proposed method is a novel approach to decide transfer limits in power system operation. The method is tested in a case study on the IEEE 39 bus system, that shows promising results. In addition to deciding optimal transfer limits, it is also investigated how the transfer capacity can be enhanced by controlling components in the power system to increase stability. / QC 20111010

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

Over the past decades, the concepts and methods for reliability assessment have evolved from analysing the ability of individual components to operate without faults and as intended during their lifetime, into the comprehensive approaches for evaluating various engineering strategies for system planning, operation and maintenance studies. The conventional reliability assessment procedures now receive different perspectives in different engineering applications and this thesis aims to improve existing approaches by incorporating in the analysis: a) a more detailed and accurate models of LV and MV networks and their reliability equivalents, which are important for the analysis of transmission and sub-transmission networks, b) the variations in characteristics and parameters of LV and MV networks in different areas, specified as “generic” UK/Scottish highly-urban, urban, sub-urban and rural network models, c) the relevant requirements for network reliability performance imposed by Regulators on network operators, d) the actual aggregate load profiles of supplied customers and their correlation with typical daily variations of fault probabilities and repair times of considered network components, and e) some of the expected “smart grid” functionalities, e.g., increased use of network automation and reconfiguration schemes, as well as the higher penetration levels of distributed generation/storage resources. The conventional reliability assessment procedures typically do not include, or only partially include the abovementioned important factors and aspects in the analysis. In order to demonstrate their importance, the analysis presented in the thesis implements both analytical and probabilistic reliability assessment methods in a number of scenarios and study cases with improved and more detailed “generic” LV and MV network models and their reliability equivalents. Their impact on network reliability performance is analysed and quantified in terms of the frequency and duration of long and short supply interruptions (SAIFI and SAIDI), as well as energy not supplied (ENS). This thesis addresses another important aspect of conventional approaches, which often, if not always, provide separate indicators for the assessment of system-based reliability performance and for the assessment of customer-based reliability performance. The presented analysis attempts to more closely relate system reliability performance indicators, which generally correspond to a fictitious “average customer”, to the actual “best-served” and “worst-served” customers in the considered networks. Here, it is shown that a more complex metric than individual reliability indicators should be used for the analysis, as there are different best-served and worst-served customers in terms of the frequency and duration of supply interruptions, as well as amounts of not supplied energy. Finally, the analysis in the thesis considers some aspects of the anticipated transformation of existing networks into the future smart grids, which effectively require to re-evaluate the ways in which network reliability is approached at both planning and operational stages. Smart grids will feature significantly higher penetration levels of variable renewable-based distributed generation technologies (with or without energy storage), as well as the increased operational flexibility, automation and remote control facilities. In this context, the thesis evaluates some of the considered smart grid capabilities and functionalities, showing that improved system reliability performance might result in a deterioration of power quality performance. This is illustrated through the analysis of applied automation, reconfiguration and automatic reclosing/remote switching schemes, which are shown to reduce frequency and duration of long supply interruptions, but will ultimately result in more frequent and/or longer voltage sags and short interruptions. Similarly, distributed generation/storage resources might have strong positive impact on system reliability performance through the reduced power flows in local networks and provision of alternative supply points, even allowing for a fully independent off-grid operation in microgrids, but this may also result in the reduced power quality levels within the microgrids, or elsewhere in the network, e.g. due to a higher number of switching transfers and transients.

abstract: Electric power system security assessment is one of the most important requirements for operational and resource planning of the bulk power system ensuring safe operation of the power system for all credible contingencies. This deterministic approach usually provides a conservative criterion and can result in expensive bulk system expansion plans or conservative operating limits. Furthermore, with increased penetration of converter-based renewable generation in the electric grid, the dynamics of the grid are changing. In addition, the variability and intermittency associated with the renewable energy sources introduce uncertainty in the electricity grid. Since security margins have direct economic impact on the utilities; more clarity is required regarding the basis on which security decisions are made. The main objective of this work is to provide an approach for risk-based security assessment (RBSA) to define dynamic reliability standards in future electricity grids. RBSA provides a measure of the security of the power system that combines both the likelihood and the consequence of an event. A novel approach to estimate the impact of transient stability is presented by modeling several important protection systems within the transient stability analysis. A robust operational metric to quantify the impact of transient instability event is proposed that incorporates the effort required to stabilize any transiently unstable event. The effect of converter-interfaced renewable energy injection on system reliability is investigated us-ing RBSA. A robust RBSA diagnostics tool is developed which provides an interactive user interface where the RBSA results and contingency ranking reports can be explored and compared based on specific user inputs without executing time domain simulations or risk calculations, hence providing a fast and robust approach for handling large time domain simulation and risk assessment data. The results show that RBSA can be used effectively in system planning to select security limits. Comparison of RBSA with deterministic methods show that RBSA not only provides less conservative results, it also illustrates the bases on which such security decisions are made. RBSA helps in identifying critical aspects of system reliability that is not possible using the deterministic reliability techniques. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

abstract: Photovoltaic (PV) power generation has the potential to cause a significant impact on power system reliability since its total installed capacity is projected to increase at a significant rate. PV generation can be described as an intermittent and variable resource because its production is influenced by ever-changing environmental conditions. The study in this dissertation focuses on the influence of PV generation on trans-mission system reliability. This is a concern because PV generation output is integrated into present power systems at various voltage levels and may significantly affect the power flow patterns. This dissertation applies a probabilistic power flow (PPF) algorithm to evaluate the influence of PV generation uncertainty on transmission system perfor-mance. A cumulant-based PPF algorithm suitable for large systems is used. Correlation among adjacent PV resources is considered. Three types of approximation expansions based on cumulants namely Gram-Charlier expansion, Edgeworth expansion and Cor-nish-Fisher expansion are compared, and their properties, advantages and deficiencies are discussed. Additionally, a novel probabilistic model of PV generation is developed to obtain the probability density function (PDF) of the PV generation production based on environmental conditions. Besides, this dissertation proposes a novel PPF algorithm considering the conven-tional generation dispatching operation to balance PV generation uncertainties. It is pru-dent to include generation dispatch in the PPF algorithm since the dispatching strategy compensates for PV generation injections and influences the uncertainty results. Fur-thermore, this dissertation also proposes a probabilistic optimal power dispatching strat-egy which considers uncertainty problems in the economic dispatch and optimizes the expected value of the total cost with the overload probability as a constraint. The proposed PPF algorithm with the three expansions is compared with Monte Carlo simulations (MCS) with results for a 2497-bus representation of the Arizona area of the Western Electricity Coordinating Council (WECC) system. The PDFs of the bus voltages, line flows and slack bus production are computed, and are used to identify the confidence interval, the over limit probability and the expected over limit time of the ob-jective variables. The proposed algorithm is of significant relevance to the operating and planning studies of the transmission systems with PV generation installed. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

Orientador: Madson Cortes de Almeida / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-24T01:13:38Z (GMT). No. of bitstreams: 1 Dardengo_VictorPellanda_M.pdf: 2575363 bytes, checksum: 30d6d4f10eba96b3baa38c14dae17316 (MD5) Previous issue date: 2013 / Resumo: No planejamento de sistemas de medição para estimação de estado de sistemas de energia elétrica são definidos os tipos, a localização e a quantidade de medidores. Um plano de medição adequado deve garantir a observabilidade da rede, viabilizando a estimação do estado de toda a rede, e permitir a filtragem de erros grosseiros. Para que os erros grosseiros possam ser filtrados é necessário que no plano de medição não estejam presentes medidas e conjuntos críticos. Neste contexto, esta dissertação propõe uma nova metodologia de análise de observabilidade baseada no estimador linearizado regularizado e apresentam duas técnicas de classificação de medidas capazes de identificar medidas críticas, medidas pertencentes a conjuntos críticos e medidas redundantes. A primeira técnica é baseada na fatoração da matriz Gram das medidas e a segunda é baseada na fatoração da matriz Jacobiana das medidas. Além disso, são estudadas e aplicadas técnicas de fatoração com números inteiros que conferem maior robustez 'as metodologias de classificação de medidas. São apresentados testes realizados em redes de pequeno e médio porte que apontam o bom funcionamento dos métodos desenvolvidos e estudados / Abstract: In planning of power systems state estimation are defined the type, the location and the number of meters. An adequate measurement plan have to ensure the observability of the network, enabling the state estimation of the entire network, and allow filtering of gross errors. In order to filter gross errors is necessary in the measurement plan is not present critical measurements and critical sets. In this context, this work proposes a new observability analysis methodology based on the regularized weighted least squares DC state estimator and presents two measurements classification techniques capable of identifying critical measurements, measurements belonging to critical sets and redundant measurements. The first technique is based on the factorization of the measurement Gram matrix and second is based on the factorization of the measurement Jacobian matrix. Furthermore, are studied and applied factorization techniques with integers numbers which give greater robustness to measurements classification methodologies. Tests are presented in small and medium networks size showing the proper functioning of developed and studied methods / Mestrado / Energia Eletrica / Mestre em Engenharia Elétrica