Conventional Power System Stabilizer Research Articles

Bidirectional long‐short‐term memory‐based fractional power system stabilizer: Design, simulation, and real‐time validation

AbstractPower oscillations in modern power grids are inherent phenomena that may threaten system reliability. Therefore, to ensure acceptable system reliability, effective damping of power oscillations is inevitably required. In this context, this article introduces a novel approach to designing fractional power system stabilizer (FPSS) for effective damping of power oscillations. Bidirectional long‐short‐term memory (Bi‐LSTM) approach is adopted to predict the parameters of FPSS. The conventional phase compensation technique is used to train Bi‐LSTM network. To validate the efficacy of FPSS, different test scenarios of contingent operating conditions are simulated for the system. Comparative analysis is carried out with conventional power system stabilizers (PSSs) and optimization‐based PSS techniques. Additionally, a test scenario is performed against existing deep neural network‐based PSS methods to ascertain the robustness of the proposed PSS. Furthermore, the performance of the proposed Bi‐LSTM‐based FPSS is validated in real‐time simulation using an interfaced OPAL‐RT OP5700 hardware device.

Power system stability enhancement through optimal PSS design

Low-frequency oscillations (LFO) are generated in interconnected electric networks because of the weak tie lines between the parts of the networks. Such oscillations have been a significant challenge for engineers that may lead to system instability if appropriate measures are not taken. This article proposes two new metaheuristic algorithms, the jellyfish search algorithm (JSA) and the tunicate swarm algorithm (TSA), to design the power system stabilizers (PSS) for single machine infinite bus (SMIB) and multimachine power system (MPS) networks. The proposed method uses the JSA and TSA to dampen out the LFOs by modifying the vital parameters of lead-lag type conventional PSS (CPSS). A damping ratio-based objective function improves both models' system damping. These methods are tested on an SMIB system and two distinct MPS networks exposed to the three-phase fault under various loading conditions. The effectiveness of the suggested approach has been studied by comparing the system eigenvalues and minimum damping ratio (MDR) produced from JSA and TSA-tuned PSS and the CPSS. In addition, time domain simulation results are compared, demonstrating that the new approach outperforms the standard techniques, such as particle swarm optimization (PSO) and backtracking search algorithm (BSA). In the SMIB system, MDR produced by JSA and TSA-based PSS is 2.55 times higher than that of CPSS. Similarly, in comparison to PSO and BSA-based PSS, JSA, and TSA-tuned PSS offer >1.4 times greater MDR in the Two Area Four Machine network and up to 8.4 times larger MDR for the IEEE-39 Bus network. Furthermore, the efficacy of the suggested JSA and TSA approaches' prediction capacity is validated by satisfying the values of statistical performance metrics.

Improvement of an AC microgrid system’s stability by using a fuzzy logic-based PSS controller

This research article presents the low-frequency oscillation damping control of an AC Microgrid. It is integrated with four distributed generation units in which two DGs are renewable energy source based solar PV and wind energy using DFIG and the other two DGs are conventional synchronous generator-based hydro and diesel generators. There is insufficient generation through renewable-based DG then a diesel generator is employed as an emergency unit to fulfil the requirements and maintain and control the deviation of the frequency of the system. The use of renewable-based DG affected the system's dynamic stability and the characteristics of an integrated microgrid differ from conventional sources of generation. This investigation explores the impression of the deployment of multiple forms of the power oscillation damping (POD) controllers to distributed generation sources of grid forming AC Microgrid. The main various types of POD controllers are conventional lead-lag PSSs, MBPSS-4B, and proposed robust fuzzy logic PSS (FLPSS) controllers are implemented on distributed generation units of AC Microgrid for the elimination of low-frequency oscillation. Low oscillation frequencies between 0.1 and 2 Hz are the focus of this work. The system's damping ratios and stability margins because of MG integration are observed using eigenvalues analysis. The results of the simulation test demonstrate the accomplishment of the robust fuzzy logic PSS controller regarding conventional lead-lag PSSs and the MBPSS-4B controller during circumstances of fault.

Coordination of Controllers to Development of Wide-Area Control System for Damping Low-Frequency Oscillations Incorporating Large Renewable and Communication Delay

The modern power systems incorporate high penetration of renewable is a large, composite, interconnected network with dynamic behavior. The small disturbances occurring in the system may induce low-frequency oscillations (LFOs) in the system. If the (LFOs) are not suppressed within a stipulated time, it may cause system islanding or even blackouts. Hence, it is essential to investigate the behavior of the system under various levels of disturbances and control action must be taken to damp these oscillations. The established approach to damping the LFOs is by installing power system stabilizers (PSS). PSS uses the local signals from generators to control the oscillations. The dominant source of inter-area oscillations in power systems is due to overloaded weak interconnected lines, converter-interfaced generation, and the action of the high gain exciter present in the system. Consequently, wide area control is needed to control the inter-area oscillations existent in the system. This paper developed a coordinated design of conventional PSS, static compensator, renewable converters, and wide area controller for damping the local and inter-area oscillations in renewable incorporated power systems. The performance of the developed controller is evaluated through the time domain analysis and eigenvalue analysis. A comparison of the introduced controller has been done with other standard conventional methods. The choice of input signals for the wide area controller from the wide-area measurement system is done based on the controllability index. Additionally, the location of the controller must be identified to dampen the inter-area oscillations in the system. In this paper, the controllability index is calculated to find out the highly affected wide area signals for considering it as the feedback signal to a developed controller. The location of the controller is recognized by computing the participation factor. The developed controller has experimented on renewable incorporated large study power systems when time delay and noise are present in wide area signals.

STABILISATEUR DE SYSTÈME D'ALIMENTATION ROBUSTE BASÉ SUR UN CONTRÔLE H∞ STRUCTURÉ POUR LA STABILITÉ D'UN SYSTÈME MULTI-MACHINE

A robust design of power system stabilizers (PSSs) using H∞ output feedback control has been introduced in this work. To facilitate the implementation of the designed PSSs, the proposed technique employs the H∞ to tune the fixed-structure conventional lead-lag PSS parameters of the multi-machine system. These PSSs are used to improve the damping of the local and inter-area low-frequency oscillations in power systems under different operating conditions. The proposed control is tested on a multi-machine system, which is a three-machine nine-bus system. A comparative simulation study shows a significant enhancement and good performance of the proposed design compared to an IEEE conventional power system stabilizer.

Two dimensional parallel sequence spread spectrum for wireless communications

A novel two-dimensional parallel sequence spread spectrum (2D-PSSS) structure for the physical layer of wireless communication systems is introduced. The proposed 2D-PSSS system partitions a data block into two groups of bits, representing the two dimensions. The first dimension represents the selected code from a predefined set of Gold codes. While the second dimension determines a shift value applied to the chosen code. The shifted Gold code will represent the data block. By design, the 2D-PSSS system overcomes the challenge of inter-code interference encountered in conventional PSSS systems without introducing additional computational complexity. Moreover, the 2D-PSSS system offers reduced encoder computational complexity compared to PSSS systems, enhancing its suitability for a wide range of wireless communication applications. The performance of the 2D-PSSS system in terms of bit error rate has been evaluated in additive white Gaussian noise (AWGN) channel and under different fading channel conditions.

Low-frequency oscillations damping with doubly-fed induction generators embodying grid-forming control with hardware-in-the-loop simulation

The integration of wind power generation into modern power systems necessitates the development of advanced control strategies to enhance grid stability and reliability. Among these strategies, grid-forming control has emerged as a promising solution, enabling converter-interfaced generation technologies to provide services traditionally supplied by conventional generation. This paper specifically addresses the challenge of low-frequency oscillations damping in power systems incorporating Doubly-Fed Induction Generators embodying grid-forming control. In this paper, two low-frequency oscillations damping strategies are proposed and tested, designed to complement a doubly-fed induction generator grid-forming control strategy. The first, called POD-Q, uses reactive power; while the second, POD-P, acts on the active power injection. Both strategies are analyzed through small-signal stability analysis and experimental testing. For the small-signal stability analysis, a dynamic model of a conventional system with a certain penetration of doubly-fed induction generation has been employed. Experimental results are obtained within a real-time simulation environment, using the hardware-in-the-loop technique to communicate a real controller board with the real-time simulator. The results indicate that the POD-P strategy is more efficient in low-frequency oscillations damping compared to a synchronous generator with a conventional power system stabilizer and also in comparison to the POD-Q strategy. However, both proposed strategies have demonstrated improvements in low-frequency oscillations damping.

Supramolecular phthalocyanine assemblies‐enhanced synergistic photodynamic and photothermal therapy guided by photoacoustic imaging

AbstractPhototherapeutic nanoplatforms that combine photodynamic therapy (PDT) and photothermal therapy (PTT) with the guidance of photoacoustic (PA) imaging are an effective strategy for the treatment of tumors, but establishing a universal method for this strategy has been challenging. In this study, we present a supramolecular assembly strategy based on Förster resonance energy transfer to construct a supramolecular nanostructured phototherapeutic agent (PcDA) via the anion and cation supramolecular interaction between two water‐soluble phthalocyanine ramifications, PcD and PcA. This approach promotes the absorption of energy, thus enhancing the generation of reactive oxygen species (ROS) and heat by PcDA, improving its therapeutic efficacy, and overcoming the low photon utilization efficiency of conventional PSs. Notably, after the intravenous injection of PcDA, neoplastic sites could be clearly visualized using PA imaging, with a PA signal‐to‐liver ratio as high as 11.9. Due to these unique features, PcDA exhibits excellent antitumor efficacy in a preclinical model at a low dose of light irradiation. This study thus offers a general approach for the development of efficient phototherapeutic agents based on the simultaneous effect of PDT and PTT against tumors with the assistance of PA imaging.

Design of Fuzzy Logic based Adaptive Active Power Controller to Enhance Power sharing among DGs in an Autonomous Microgrid

This paper presents the design of an adaptive active power controller to enhance the power-sharing capabilities of distributed generators (DGs) in an autonomous microgrid. Each DG in an autonomous microgrid consists of a droop-controlled inverter to control active and reactive power by regulating frequency and voltage correspondingly. The high droop gain can be used in the power controller to encourage faster power sharing among the DGs. However, high droop gain can cause undamped growing oscillations during load fluctuations or generation losses. During such events, attaining faster power-sharing between DGs using high droop gains is difficult. So, the problem with an autonomous microgrid is the conflict between faster power sharing and stability. Stability needs to be compromised to attain quicker power sharing and vice versa. Hence, to achieve power-sharing swiftly with high droop gain and to diminish the growing oscillations caused, this paper proposes a fuzzy logic-based adaptive active power controller (FLAPC). The proposed FLAPC is adaptive and easy to implement. It offers faster power sharing for different values of droop gains and step change in load. The FLAPC is developed in MATLAB 2018a/Simulink environment, and time domain simulations are performed to see the efficacy of the proposed controller. The results of time domain simulations are compared with a droop controller without any additional controller, conventional lead-lag power system stabilizer, and proposed controller for step change in load at different droop gains. The results show that the proposed controller enhances the power-sharing performance and also ameliorates the system’s stability by reducing the settling time and overshoot in active power responses of DGs.

Stabilizing multimachine power systems with fuzzy logic using artificial bee colonies

Over the past few years, fuzzy logic systems have gained popularity due to their superiority over classical controllers when it comes to enhancing the transient stability of power systems. In this paper, a Fuzzy Logic Power System Stabilizer (FLPSS) is designed to damp local and inter-area oscillations following disturbances through the use of an Artificial Bee Colony Optimization Algorithm (ABC). The designed FLPSS is expected to significantly increase the robustness of power systems and ultimately improve the quality of power supply to end-users. This test system consists of two areas with four machines and eleven buses, with the purpose of evaluating the performance of the ABC-FLPSS under a variety of disturbances and loads. In order to optimize the scaling factors of FLPSSs, the Integral Squared Error (ISE) of rotor speed deviation is formulated as an objective function. Evaluation of the proposed controller involves simulating the test system under different conditions. These conditions range from small perturbations, such as changes in one of the system parameters, to large changes, such as removing a main transmission line, to determine its effectiveness. A comparison of ABC-FLPSS with FLPSS and Conventional Power System Stabilizer (CPSS) shows that the ABC-FLPSS controller is superior to FLPSS and CPSS.

Fuzzy adaptive tuning control of power system based on moth-flame optimization algorithm

Since low-frequency oscillation seriously threatens the safe operation of the power system, the power system stabilizer (PSS) can effectively suppress the oscillation. In this paper, a hybrid parameter optimization method combining the moth-flame optimization (MFO) algorithm and fuzzy logic controller (FLC) is proposed to address the problem of poor adaptability of the parameter tuning method in the conventional power system stabilizer (CPSS). This method can optimize the parameters of PSS in different processes. Initially, the optimal parameters of PSS under the current perturbation are given by the MFO algorithm. During the online operation of the system, as perturbation changes, the parameters of the PSS will also be adaptively tuned by the FLC in real-time when the system operating conditions change. According to this method, a fuzzy adaptive proportional–integral–differential (FPID) controller is designed based on the moth-flame optimization algorithm (MFO-FPID), and it is used as PSS to improve dynamic stability performance during oscillation. Moreover, its parameters can be adaptively adjusted in different perturbation scenarios. The designed MFO-FPID controller is applied to the single machine infinite bus (SMIB) power system to compare the dynamic performance with other controllers, that is, proportional–integral–differential (PID) and CPSS. The result shows that the MFO-FPID controller can suppress the oscillation very well, and the control effect is the best.

Controllability analysis of renewable embedded AC microgrid with multi-band stabilizers

The depletion of conventional energy sources and the increasing demand for electricity due to industrialization and rising global living standards has led to the need for a transformation of the traditional power grid. The microgrid concept has emerged as a solution that integrates renewable energy sources into the main grid. This paper examines an AC microgrid consisting of solar, wind, hydro, and diesel power stations, and investigates the effect of various power system stabilisers (PSSs) on the silent-pole synchronous generator of the diesel and hydro power plant. The effectiveness of different PSSs, including - PSS, ΔPa-PSS, and Multi-band PSS, is compared using a grid-connected AC microgrid. The simulation results show that Multiband PSS performs better than conventional PSSs in eliminating electromechanical oscillation, even in the presence of Gaussian and colored noise. PSSs are useful in managing the power flow of various DERs and improving power system stability. The simulation is conducted using the MATLAB/SIMULINK software.

Designing a power system stabilizer using a hybrid algorithm by genetics and bacteria for the multi-machine power system

This research creates an optimal power grid stabilizer for four machines. Rotor speed signals are system inputs in the proposed design. To improve response, this system uses a conventional power system stabilizer (CPSS) and an optimal CPSS (OCPSS). The genetic optimization hybrid has a new structure, and the network generators use the bacterial foraging algorithm (BFA) with stabilizer system. The system set is tested by MATLAB software under various conditions to evaluate the designs. The experiment starts with a three-phase fault in line 3 that is fixed by breaking the line after 0.2 seconds. The simulation results show that after a short circuit in line 3, the proposed OCPSS design reaches damping after about a cycle of oscillation in 4 seconds. However, the conventional CPSS design achieves damping after four oscillations in six seconds. Simulations show that the proposed method is better than genetic algorithm (GA) and BFA. Power system oscillations are dampened faster and with lower amplitude when power system stabilizer (PSS) coordinate with the proposed optimization method. It also improves power system dynamics. We demonstrate with the proposed OCPSS stabilizer that advanced optimization systems can maximize system control capacity by utilizing conventional CPSS system advantages.

Model-Predictive Control Design for Power System Oscillation Damping via Excitation – A Data-Driven Approach

This paper presents a novel power system oscillation damping controller design based on a data-driven model-predictive control (MPC) approach. The system dynamics are extracted from the measurements and applied to the synthesis of control actions in an equation-free manner, without requiring explicit knowledge of the underlying system model. Dynamic mode decomposition with control (DMDc), originating from the Koopman operator theory, connects the collected data with the nonlinear dynamical system modeling. The discrepancy between the model identified by DMDc and the real plant is labeled as a total disturbance. It is estimated in real time by an extended state observer (ESO) and mitigated via a linear MPC, assuming the estimate to be constant over the prediction horizon. The overall control framework is referred to as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ESO-Koopman-MPC (EKM)</i> . Two <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EKM</i> -based oscillation damping controllers are proposed - a standalone PSS and an integrated AVR+PSS. The controller operation is illustrated on the single machine infinite bus system (SMIB), Kundur two-area system and IEEE 39-bus system, and the performance is compared with conventional power system stabilizers (CPSSs) under various test scenarios.

Laboratory Implementation of a Wide-area Damping Controller using a Dynamic Hardware Emulator

The ongoing decarbonisation of the electric power system brings new challenges in terms of system dynamics and stability, as the substitution of generation units with rotating masses towards generation units based on power electronics entails a substantial loss of inertia. To meet the new challenges and maintain the reliability of the electrical grid, innovative solutions are required. Therefore, this paper presents a two-step approach to test and validate controller structures for damping inter-area oscillations. First, the controller was developed and tested in a control hardware in the loop environment. Then, the controller was transferred to a dynamic hardware emulator (scaled version of the Kundur's two area transmission network in the laboratory consisting of physical hardware) for final performance validation. It is shown that with a conventional power system stabilizer (PSS) and a proportional wide-area damping controller (WADC), the damping of inter-area oscillations is improved in an emulated power system. In addition, with the setup created, different types of controllers and other challenges related to wide-area damping control can be investigated in the future.

Design and performance analysis of opposition-based whale optimization algorithm tuned power system stabilizer for multimachine stability

A novel Opposition-based Whale Optimization Algorithm (OWOA) is utilized to build a power stabilizer and increase multimachine stability. A Conventional Power System Stabilizer (CPSS) with a lead-lag compensator is employed, and OWOA fine-tunes its settings using an objective function that minimizes the integral absolute error of speed deviations of generator rotors. Various time-domain simulations were performed to validate the superior performance of the proposed Power System Stabilizers (PSS). Furthermore, the performance of the proposed PSS is compared to a Whale Optimization Algorithm (WOA)-based PSS and a conventional PSS. The obtained results demonstrate the effective performance of the proposed OWOA-based PSS for power oscillation damping.

A review of opposition-based whale optimization algorithm and whale optimization algorithm tuned power system stabilizer for multimachine stability

This research aims to improve the stability of power systems using a power stabilizer. Various methods were used to finetune the conventional Power System Stabilizer (PSS) with a lead-lag compensator by minimizing the integral absolute error of speed deviations of generator rotors. To evaluate the performance of the various methods, different timedomain simulation test cases were conducted and the results were compared with the performance of the Oppositional Whale Optimization Algorithm-based Power System Stabilizer (OWOA-based PSS), Whale Optimization Algorithm-based Power System Stabilizer (WOA-based PSS), and the conventional PSS. The obtained results show that the OWOA-based PSS is more efficient in power oscillation damping than the other methods, including the WOA-based PSS. Overall, the OWOA-based PSS can be considered as a potential solution to enhance the stability of power systems by mitigating power oscillations in generator rotors. However, further studies and experiments may be required to validate all methods and compare them to ensure their effectiveness and efficiency.

Low frequency oscillations damping by design of power system stabilizer using intelligent controllers

The intention and justification of a Fuzzy and PID Controller based PSS for a multi area classification is to examine its analysis to dank out the squat frequency oscillation. The design employs a conservative input pairs like speed deviation (Δω) and rotor angle deviation (Δδ) to the Fuzzy PSS and speed deviation (Δω) for Integer Order PID (IOPID) controller. The advantage of this Fuzzy based PSS is that, it can be fed to each of machines in the each areas of the Power System which eases cost, scanning time and thus shortens the arrangement. It is observed that Fuzzy based PSS yields a more satisfactory role in damping low frequency oscillations and to increase stability rather than conventional and IOPID PSS. The analysis of the system is done using MATLAB 2014b.

Power System Stabilizers Layout via Flower Pollination Algorithm

In this article, the optimum layout of Power System Stabilizers (PSSs) using Flower Pollination Algorithm (FPA) is developed in a multimachine environment. The PSSs values tuning problem is turned into an optimization task which is treated by FPA. FPA is used to check for optimum controller parameters by reducing an eigenvalues based objective function involving the damping factor, and the damping ratio of the lightly damped modes. The implementation of the developed FPA based PSSs (FPAPSS) is compared with Particle Swarm Optimization (PSO) based PSSs (PSOPSS) and the Conventional PSSs (CPSS) for various loading conditions and disturbances. The results of the developed FPAPSS are confirmed via time domain analysis, eigenvalues and some indices. Also, the results are introduced to prove the effectiveness of the developed algorithm over the PSO and conventional one.

Robust Damping Controller for Synchronous Generators under Operational Uncertainties

Power system stabilizers have been widely used to create sufficient damping against low-frequency oscillations. Due to appearing new uncertainties in operational conditions of power systems, robust design of stabilizers and damping controllers is a crucial requirement for small signal stability. In this paper, a robust local damping controller is developed considering the possible uncertainties in operational conditions. The developed damping controller is optimized based on the H-infinity method in presence of uncertainties in electrical variables of the synchronous machine including rotor angle, rotor speed, and terminal voltage magnitude. In the proposed robust damping controller, only the practically available control signals such as the deviation of the rotor speed of the synchronous generators are used. To fulfill the robust and internal stabilities of the damping controller under a given horizon of operational uncertainties, a novel design based on the combination of the developed robust damping controller and the conventional power system stabilizer is introduced. Simultaneous damping of local oscillatory modes and the internal stability of the proposed robust controller is achieved via a multi-objective function. The efficacy of the proposed local damping controller is compared with the conventional stabilizer and a damping controller that is designed using the pole placement approach.