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

Synchronous Generator Excitation Chatter-Free Sliding Mode Controller

A chatter-free sliding mode controller (SMC) for synchronous generator excitation is presented in this paper. A linearized model of a single machine connected to an infinite bus is employed to design a variable-structure controller which not only stabilizes the system, but also ensures that this is maintained in the face of system parameter variations. Validating the robustness feature of an SMC, simulation results that show the dynamic performance of the system under both constant excitation and SMC-controlled excitation are presented

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

Artificial Intelligence-Based Power System Stabilizers for Frequency Stability Enhancement in Multi-machine Power Systems

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently constructed in tandem to improve the dampening efficiency of the system. In this study, an Interline Power Flow Controller (IPFC) FACTS device will be added to the PSSs controller to improve the power system’s oscillatory stability. PSSs optimal design and supplemental controller of power fluctuations for IPFC were conducted out on WSCC multi-machine test systems using a linear system model. Using time-domain simulations and quantitative analysis, the proposed IPFC model was compared to the FFA-PSSs controller in terms of performance and efficiency. The main disadvantage of this technique is the difficulty in designing a dynamic IPFC model in test systems, as well as the burden of IPFC coordinated PSSs optimization. In both PSSs design using FFA method and FFA-optimized PSS with IPFC cases, rise in the computational and simulation costs was found unavoidable. To compensate for these flaws and obtain the research contribution, this paper proposes a Neuro-Fuzzy Controller (NFC) developed as a damping controller that can take the place of the two controllers (research objectives three). The application of the NFC substitutes the computational and simulation cost involved in designing multi-machine PSS and IPFC-FACTS systems simultaneously. With the availability of NFC in SIMULINK, a dynamic model of the WSCC three-machine system was developed under a variety of operating situations. Quantitative analysis results from the WSCC test system simulation show that when comparing the proposed NFC model to the IPFC model for the WSCC test system, the proposed NFC model was found to be 149 percent and 0 percent efficient in terms of the time to settle of rotor angle respond for G2 and G3, respectively, but 394 percent efficient when compared to the uncontrolled model. The decreased settling time values ensured the proposed NFC model’s efficacy in damping down the LFO and achieving superior stability over the two controllers. The proposed NFC model was shown significant performance improvement in both the transient and steady-state areas than when the system was designed with the two damping controllers

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

Aplikasi Fuzzy Type-2 PSS untuk Perbaikan Stabilitas Dinamik Pembangkit Listrik Tenaga Mikro Hidro dan Diesel: Application of Fuzzy Type-2 PSS to Improve Dynamic Stability of Micro Hydro and Diesel Power Plants

Teknologi fuzzy tipe 2 (FT2) berkembang sangat pesat dan memasuki bidang stabilitas sistem tenaga listrik. Pembangkit listrik tenaga mikro hidro (PLTMH) dan diesel (PLTD) riskan terhadap gangguan perubahan beban. Studi stabilitas penting dikerjakan untuk memastikan bahwa operasi PLTMH-PLTD tetap stabil ketika dan setelah beban berubah. Maka power system stabilizer (PSS) berbasis FT2 diusulkan untuk perbaikan stabilitas sistem tersebut. FT2PSS didesain dengan input kecepatan rotor dan derivatifnya. Outputnya adalah sinyal stabilitas yang diumpankan pada sistem eksitasi. Hasilnya, FT2PSS mampu mereduksi overshoot -0,035 deg. Sedangkan overshoot untuk CPSS adalah -0,051 deg. FT2PSS juga dapat mempersingkat settling time dan mempercepat steady state. Stabilitas PLTMH-PLTD yang dilengkapi dengan FT2PSS diperbaiki secara significan

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

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

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

Power system stabilizer (PSS) is applied to dampen system oscillations so that the frequency does not deviate beyond tolerance. PSS parameter tuning is increasingly difficult when dealing with complex and nonlinear systems. This paper presents a novel hybrid algorithm developed from incorporating chaotic maps into the sea-horse optimizer. The algorithm developed is called the chaotic sea-horse optimizer (CSHO). The proposed method is adopted from the metaheuristic method, namely the sea-horse optimizer (SHO). The SHO is a method that duplicates the life of a sea-horse in the ocean when it moves, looks for prey and breeds.  In This paper, The CSHO method is used to tune the power system stabilizer parameters on a single machine system. The proposed method validates the benchmark function and performance on a single machine system against transient response. Several metaheuristic methods are used as a comparison to determine the effectiveness and efficiency of the proposed method. From the research, it was found that the application of the logistics Tent map from the chaotic map showed optimal performance. In addition, the application of the PSS shows effective and efficient performance in reducing overshoot in transient conditions