Indirect adaptive fuzzy finite time synergetic control for power systems

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults. Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems. Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller.Вступ. Бюджетні обмеження у світі, жадібному до електроенергії, змушують комунальні підприємства експлуатувати станції, що генерують, на повну потужність, а іноді і на межі стабільності. У таких різких умовах виникнення будь-якої позаштатної ситуації або збурення може призвести до виникнення критичної ситуації, що починається з погано згасаючих коливань з подальшою втратою синхронізму та нестійкістю енергосистеми. В останні десятиліття велика увага приділялася використанню додаткових сигналів, керуючих збудження, для підвищення стійкості енергосистеми. Стабілізатори енергосистеми (СЕС) служать для вироблення додаткових сигналів керування системою збудження з метою гасіння низькочастотних коливань, спричинених збуреннями навантаження або короткими замиканнями. Проблема. Адаптивні стабілізатори енергосистем були запропоновані для того, щоб адекватно справлятися з широким діапазоном робочих умов, але вони страждають від основного недоліку, що полягає в необхідності ідентифікації моделі параметрів, спостереження за станом та обчислення коефіцієнта посилення зворотного зв'язку в режимі реального часу. Енергетичні системи є нелінійними системами з конфігураціями та параметрами, які змінюються з часом, що потребує повністю нелінійної моделі та схеми адаптивного управління для практичного операційного середовища. Новий нелінійний адаптивно-нечіткий підхід, заснований на синергетичній теорії управління, розроблений для нелінійних стабілізаторів енергосистем для подолання вищезазначених проблем. Мета. Теорія синергетичного управління успішно застосовувалася під час проєктування стабілізаторів енергосистем. Це найбільш перспективний надійний метод управління, заснований на тому ж принципі інваріантності, що і в ковзному режимі управління, але без його недоліку, пов'язаного з вібрацією. У більшості своїх програм синергетичний закон управління був розроблений на основі аналізу асимптотичної стійкості, і траєкторії системи еволюціонують до заданого атрактора, що досягає рівноваги за нескінченний час. У статті подано непрямий адаптивний нечіткий синергетичний стабілізатор енергосистеми з кінцевим часом для гасіння локальних та міжзонових мод коливань енергосистем. Методологія. Пропонована конструкція регулятора заснована на адаптивному нечіткому управлінні, що поєднує синергетичну теорію управління з атрактором кінцевого часу та синтезом Ляпунова. Удосконалюючи існуючий стабілізатор адаптивної нечіткої синергетичної енергосистеми, де нечіткі системи використовуються для апроксимації динаміки невідомої системи та надійного синергетичного управління тільки для забезпечення асимптотичної стійкості замкнутої системи, запропонований метод забезпечує властивість збіжності за кінцевий час при виведенні безперервного синергетичного закону керування. Наведено аналітичні докази збіжності за кінцевий час, що підтверджують, що запропонована адаптивна схема може гарантувати обмеженість сигналів системи та отримання стійкості за кінцевий час. Результати. Працездатність пропонованого стабілізатора оцінюється для одномашинної системи з нескінченними шинами і багатомашинної енергосистеми при різних типах збурень. Результати моделювання порівнюються з результатами, отриманими за допомогою звичайного нечіткого адаптивного синергетичного регулятора

Coordination of Adaptive Neuro Fuzzy Inference System (ANFIS) and Type-2 Fuzzy Logic System-Power System Stabilizer (T2FLS-PSS) to Improve a Large-scale Power System Stability

Intelligent control included ANFIS and type-2 fuzzy (T2FLS) controllers grown-up rapidly and these controllers are applied successfully in power system control. Meanwhile, small signal stability problem appear in a large-scale power system (LSPS) due to load fluctuation. If this problem persists, and can not be solved, it will develop blackout on the LSPS. How to improve the LSPS stability due to load fluctuation is done in this research by coordinating of PSS based on ANFIS and T2FLS. The ANFIS parameters are obtained automatically by training process. Meanwhile, the T2FLS parameters are determined based on the knowledge that obtained from the ANFIS parameters. Input membership function (MF) of the ANFIS is 5 Gaussian MFs. On the other hand, input MF of the T2FLS is 3 Gaussian MFs. Results show that the T2FLS-PSS is able to maintain the stability by decreasing peak overshoot for rotor speed and angle. The T2FLS-PSS makes the settling time is shorter for rotor speed and angle on local mode oscillation as well as on inter-area oscillation than conventional/ ANFIS-PSS. Also, the T2FLS-PSS gives better performance than the other PSS when tested on single disturbance and multiple disturbances

Indirect adaptive fuzzy finite time synergetic control for power systems

Introduction. Budget constraints in a world ravenous for electrical power have led utility companies to operate generating stations with full power and sometimes at the limit of stability. In such drastic conditions the occurrence of any contingency or disturbance may lead to a critical situation starting with poorly damped oscillations followed by loss of synchronism and power system instability. In the past decades, the utilization of supplementary excitation control signals for improving power system stability has received much attention. Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp low-frequency oscillations caused by load disturbances or short-circuit faults. Problem. Adaptive power system stabilizers have been proposed to adequately deal with a wide range of operating conditions, but they suffer from the major drawback of requiring parameter model identification, state observation and on-line feedback gain computation. Power systems are nonlinear systems, with configurations and parameters that fluctuate with time that which require a fully nonlinear model and an adaptive control scheme for a practical operating environment. A new nonlinear adaptive fuzzy approach based on synergetic control theory which has been developed for nonlinear power system stabilizers to overcome above mentioned problems. Aim. Synergetic control theory has been successfully applied in the design of power system stabilizers is a most promising robust control technique relying on the same principle of invariance found in sliding mode control, but without its chattering drawback. In most of its applications, synergetic control law was designed based on an asymptotic stability analysis and the system trajectories evolve to a specified attractor reaching the equilibrium in an infinite time. In this paper an indirect finite time adaptive fuzzy synergetic power system stabilizer for damping local and inter-area modes of oscillations for power systems is presented. Methodology. The proposed controller design is based on an adaptive fuzzy control combining a synergetic control theory with a finite-time attractor and Lyapunov synthesis. Enhancing existing adaptive fuzzy synergetic power system stabilizer, where fuzzy systems are used to approximate unknown system dynamics and robust synergetic control for only providing asymptotic stability of the closed-loop system, the proposed technique procures finite time convergence property in the derivation of the continuous synergetic control law. Analytical proofs for finite time convergence are presented confirming that the proposed adaptive scheme can guarantee that system signals are bounded and finite time stability obtained. Results. The performance of the proposed stabilizer is evaluated for a single machine infinite bus system and for a multi machine power system under different type of disturbances. Simulation results are compared to those obtained with a conventional adaptive fuzzy synergetic controller

Output power levelling for DFIG wind turbine system using intelligent pitch angle control

Blade pitch angle control, as an indispensable part of wind turbine, plays a part in getting the desired power. In this regard, several pitch angle control methods have been proposed in order to limit aerodynamic power gained from the wind turbine system (WTS) in the high-windspeed regions. In this paper, intelligent control methods are applied to control the blade pitch angle of doubly-fed induction generator (DFIG) WTS. Conventional fuzzy logic and neuro-fuzzyparticle swarm optimization controllers are used to get the appropriate wind power, where fuzzy inference system is based on fuzzy c-means clustering algorithm. It reduces the extra repetitive rules in fuzzy structure which in turn would reduce the complexity in neuro-fuzzy network with maximizing efficiently. In comparing the controllers at any given wind speed, adaptive neuro-fuzzy inference systems controller involving both mechanical power and rotor speed revealed better performance to maintain the aerodynamic power and rotor speed at the rated value. The effectiveness of the proposed method is verified by simulation results for a 9 MW DFIG WTS

Design of Power System Stabilizer

A power system stabilizer (PSS) installed in the excitation system of the synchronous generator improves the small-signal power system stability by damping out low frequency oscillations in the power system. It does that by providing supplementary perturbation signals in a feedback path to the alternator excitation system. In our project we review different conventional PSS design (CPSS) techniques along with modern adaptive neuro-fuzzy design techniques. We adapt a linearized single-machine infinite bus model for design and simulation of the CPSS and the voltage regulator (AVR). We use 3 different input signals in the feedback (PSS) path namely, speed variation(w), Electrical Power (Pe), and integral of accelerating power (Pe*w), and review the results in each case. For simulations, we use three different linear design techniques, namely, root-locus design, frequency-response design, and pole placement design; and the preferred non-linear design technique is the adaptive neuro-fuzzy based controller design. The MATLAB package with Control System Toolbox and SIMULINK is used for the design and simulations

Automatic Control and Routing of Marine Vessels

Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

Adaptive Fuzzy Synergetic PSS Design to Damp Power System Oscillations

This paper presents a novel indirect adaptive Power System Stabilizer (PSS) via a developed synergetic control methodology and fuzzy systems. Fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. The synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law. Additionally, the parameters of the controller are optimized by Imperialist Competitive Algorithm (ICA). The effectiveness of the proposed scheme is confirmed on a single machine power system while the stability is guaranteed through Lyapunov synthesis

H∞ based control of a DC/DC buck converter feeding a constant power load in uncertain DC microgrid system

DC microgrids are gaining more and more popularity and are becoming a more viable alternative to AC microgrids (MGs) due to their advantages in terms of simpler power converter stages, flexible control algorithms and the absence of synchronization and reactive power. However, DC-MGs are prone to instability issues associated with the presence of nonlinear loads such as constant power loads (CPL) known by their incremental negative impedance (INI), which may lead to voltage collapse of the main DC Bus. In this paper, -based controller of a source side buck converter is designed to avoid the instability issues caused by the load-side converter acting as a CPL. Besides, the proposed controller allows a perfect rejection of all perturbations that may arise from parameter variations, input voltage and CPL current fluctuations. The design process of H-based controller is based on the Golver Doyle Optimization Algorithm (GDOA), which requires an augmented system extracted from the small-signal model of the DC/DC converter including the mathematical model of parameter variations and overall external perturbations. The​ based controller involves the use of weight functions in order to get the desired performances. The proposed controller is easy to implement and lead to reducing the implementation cost and avoid the use of current measurement that may have some disadvantages. The derived controller is validated by simulation performed in Psim software and experimental setup