15 research outputs found

    Systems Structure and Control

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    The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc

    Reliable Control of Power Electronic based Power Systems

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    Toward Fault Adaptive Power Systems in Electric Ships

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    Shipboard Power Systems (SPS) play a significant role in next-generation Navy fleets. With the increasing power demand from propulsion loads, ship service loads, weaponry systems and mission systems, a stable and reliable SPS is critical to support different aspects of ship operation. It also becomes the technology-enabler to improve ship economy, efficiency, reliability, and survivability. Moreover, it is important to improve the reliability and robustness of the SPS while working under different operating conditions to ensure safe and satisfactory operation of the system. This dissertation aims to introduce novel and effective approaches to respond to different types of possible faults in the SPS. According to the type and duration, the possible faults in the Medium Voltage DC (MVDC) SPS have been divided into two main categories: transient and permanent faults. First, in order to manage permanent faults in MVDC SPS, a novel real-time reconfiguration strategy has been proposed. Onboard postault reconfiguration aims to ensure the maximum power/service delivery to the system loads following a fault. This study aims to implement an intelligent real-time reconfiguration algorithm in the RTDS platform through an optimization technique implemented inside the Real-Time Digital Simulator (RTDS). The simulation results demonstrate the effectiveness of the proposed real-time approach to reconfigure the system under different fault situations. Second, a novel approach to mitigate the effect of the unsymmetrical transient AC faults in the MVDC SPS has been proposed. In this dissertation, the application of combined Static Synchronous Compensator (STATCOM)-Super Conducting Fault Current Limiter (SFCL) to improve the stability of the MVDC SPS during transient faults has been investigated. A Fluid Genetic Algorithm (FGA) optimization algorithm is introduced to design the STATCOM\u27s controller. Moreover, a multi-objective optimization problem has been formulated to find the optimal size of SFCL\u27s impedance. In the proposed scheme, STATCOM can assist the SFCL to keep the vital load terminal voltage close to the normal state in an economic sense. The proposed technique provides an acceptable post-disturbance and postault performance to recover the system to its normal situation over the other alternatives

    Computational approaches for voltage stability monitoring and control in power systems

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    The electric power grid is a complex, non-linear, non-stationary system comprising of thousands of components such as generators, transformers, transmission lines and advanced power electronics based control devices, and customer loads. The complexity of the grid has been further increased by the introduction of smart grid technologies. Smart grid technology adds to the traditional power grids advanced methods of communication, computation and control as well as increased use of renewable energy sources such as wind and solar farms and a higher penetration of plug-in electric vehicles among others. The smart grid has resulted in much more distributed generation, bi-directional powerflows between customers and the grid, and the semi-autonomous control of subsystems. Due to this added complexity of the grid and the need to maintain reliable, quality, efficient, economical, and environmentally friendly power supply, advanced monitoring and control technologies are needed for real-time operation of various systems that integrate into the transmission and distribution network. In this dissertation, the development of computational intelligence methods for on-line monitoring of voltage stability in a power system is presented. In order to carry out on-line assessment of voltage stability, data from Phasor Measurement Units (PMUs) is utilized. An intelligent algorithm for optimal location of PMUs for voltage stability monitoring is developed. PMU information is used for estimation of voltage stability load index in a power system with plug-in electric vehicle and wind farm included. The estimated voltage stability index is applied in the development of an adaptive dynamic programming based optimal secondary voltage controller to coordinate the reactive power capability of two FACTS devices --Abstract, page iii

    Model referans kayan kipli kontrolör tabanlı güç sistem kararlayıcı tasarımı

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    06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Güç sistemlerinin doğası gereği sıklıkla ve rastgele meydana gelen yük değişimleri sistemde küçük genlikli ve düşük frekanslı, 0.2-3 Hz, salınımların oluşmasına neden olur. Güç sistemlerinin kararlı çalışmayı sürdürebilmesi için bu salınımların uygun bir şekilde sönümlenmesi gerekmektedir. Güç sistemlerinde görülen salınımların sönümlenmesi amacı ile senkron generatörlerin uyarma sistemine destekleyici kontrol işareti sağlayan yardımcı kontrol sistemleri literatürde güç sistem kararlayıcısı (GSK) olarak adlandırılır.Bu tez çalışmasında GSK tasarımına yeni bir yaklaşım olarak ayrık-zaman model-referans kayan kipli kontrolör tabanlı (MR-KKK) bir yapı sunulmuştur. Farklı çalışma noktaları ve sistem parametreleri için yapılan benzetim çalışmalarında sunulan MR-KKK tabanlı GSK yapısının literatürde mevcut olan klasik GSK, LQR tabanlı GSK, KKK tabanlı GSK yapılarına oranla güç sistemlerinde görülen salınımları daha az aşımlı ve daha hızlı bir şekilde sönümlediği, sistem parametrelerindeki değişimlere daha az duyarlı olduğu dolayısıyla daha dayanıklı (robust) bir yapıda olduğu gösterilmiştir.Due to nature of power systems, random load changes seen frequently have resulted in small magnitude and low frequency oscillations. These oscillations shall be damped appropriately to sustain stability of power systems. Power System Stabilizers (PSSs) added to excitation systems to enhance the damping of electric power system during low frequency oscillations.In this thesis, as a new approach to design of PSS, a discrete time model reference sliding mode controller (MR-SMC) based structure have been represented. In simulation studies for different operating points and system parameters, it has been seen that the proposed MR-SMC has better performance in terms of over-shoot and setting time compared to existed PSS structures such as, classical, LQR and SMC. In addition, it has been shown that the proposed approach is less insensitive to changes in system parameters and therefore it has robust property

    Fully Evolvable Optimal Neurofuzzy Controller Using Adaptive Critic Designs

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    A near-optimal neurofuzzy external controller is designed in this paper for a static compensator (STATCOM) in a multimachine power system. The controller provides an auxiliary reference signal for the STATCOM in such a way that it improves the damping of the rotor speed deviations of its neighboring generators. A zero-order Takagi-Sugeno fuzzy rule base constitutes the core of the controller. A heuristic dynamic programming (HDP) based approach is used to further train the controller and enable it to provide nonlinear near-optimal control at different operating conditions of the power system. Based on the connectionist systems theory, the parameters of the neurofuzzy controller, including the membership functions, undergo training. Simulation results are provided that compare the performance of the neurofuzzy controller with and without updating the fuzzy set parameters. Simulation results indicate that updating the membership functions can noticeably improve the performance of the controller and reduce the size of the STATCOM, which leads to lower capital investment

    A Proportional-Integrator Type Adaptive Critic Design-Based Neurocontroller for a Static Compensator in a Multimachine Power System

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    A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system, using artificial neural networks, is presented in this paper. The action dependent heuristic dynamic programming, a member of the adaptive critic designs family is used for the design of the STATCOM neurocontroller. This neurocontroller provides optimal control based on reinforcement learning and approximate dynamic programming. Using a proportional-integrator approach, the proposed neurocontroller is capable of dealing with actual rather than deviation signals. Simulation results are provided to show that the proposed controller outperforms a conventional PI controller for a STATCOM in a small and large multimachine power system during large-scale faults, as well as small disturbances
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