Nonlinear Time-domain Simulation Research Articles

Dynamic response of steel catenary riser using a seabed interaction under random loads

It is important to develop better understanding of the Steel Catenary Riser (SCR)–soil interaction mechanism to provide a realistic technique to predict the dynamic response and structural behaviour of the SCR in the Touchdown Zone (TDZ).This paper discusses the significance of SCR–seabed interaction in the design of SCR for deepwater applications and reports the results of an analysis of an SCR on soft clay in 910 m depth of water using the commercial code OrcaFlex for non-linear time domain simulation with a robust meshing technique. In the study reported in this paper, the vertical embedment and large lateral movements of the SCR in the TDZ were investigated. During the simulations the seabed has been modelled using a hysteretic non-linear model in vertical seabed direction, and bilinear and trilinear models in the lateral seabed direction. It has been found that the TDZ responses result in the degradation of the seabed soil stiffness due to cyclic loading. Furthermore, an improved SCR–soil interaction model, with accurate prediction of soil stiffness and riser penetration enables us to more accurately predict global riser dynamic performance in the TDZ.

Comparison of Honey Bee Mating Optimization and Genetic Algorithm for Coordinated Design of Pss and Statcom Based on Damping of Power System Oscillation

Recently, honey bee mating optimization (HBMO) technique and genetic algorithms (GA) have attracted considerable attention among various modern heuristic optimization techniques. This paper presents the application and performance comparison of HBMO and GA optimization techniques, for coordinated design of STATCOM and PSS. The design objective is to enhance damping of the low frequency oscillations. The design problem of the controller is formulated as an optimization problem and both HBMO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques for damping low frequency oscillations are tested and demonstrated through nonlinear time-domain simulation and some performance indices studies to different disturbances over a wide range of loading conditions. The results show that the designed controller by HBMO performs better than GA in finding the solution. Moreover, the system performance analysis under different operating conditions show that the φ based controller is superior to the C based controller.

Damping of Power System Oscillations via Quantum Particle Swarm Optimization Based Distributed Static Series Compensator

The distributed static series compensator is a series distributed flexible AC transmission system device that can control the power flow in the transmission lines. In this article, a linear Heffron–Philips model for a distributed static series compensator is presented and considered to design a supplementary damping controller for low-frequency oscillations in a single- and multi-machine power system. A quantum particle swarm optimization based damping controller is designed for the distributed static series compensator to damp the power system oscillations. To compare the results, a particle swarm optimization based damping controller is also designed and granted to the distributed static series compensator to damp the oscillations. Simulation results are performed in two separate cases. In the first case, the quantum particle swarm optimization based damping controller is examined in a single-machine infinite bus based on the linearized model of the system in three different operating points; in the second case, non-linear time-domain simulations have been performed in a six-machine three-area power system. Moreover, performance index analysis is also carried out to verify the effectiveness of the proposed quantum particle swarm optimization based damping controller.

Subsynchronous resonance mitigation using variable‐speed wind energy conversion systems

This work proposes a strategy to mitigate subsynchronous resonance (SSR) in synchronous generators using variable-speed wind energy conversion systems (WECSs) based on full converter wind turbines. A supplementary active and reactive power to be delivered by WECSs located near synchronous generators is designed to reduce the SSR phenomenon. These supplementary signals are calculated using an observer-based controller tuned through an optimal quadratic technique which allows to minimise the WECS control effort, whereas a good torsional oscillation damping is accomplished. The power ratio between the WECS and the synchronous generator, impact on the power quality and communication time-delay requirements are also discussed. The authors compare two control approaches: the first one uses mechanical measurements of the synchronous generator (measures which have high observability of torsional modes), whereas the second one uses voltage measurements at the wind farm connection point. In this way, two control schemes using remote and local measurements are proposed, and advantages and disadvantages of both schemes are presented. The proposed scheme can provide satisfactory torsional damping under a wide range of operating points, avoiding to include dedicated SSR damping equipment, and using the new wind farms installed in the network. Eigenvalue analysis and non-linear time-domain simulations confirm the good performance of the WECS-based SSR damping controller.

Optimal design of damping controllers using a new hybrid artificial bee colony algorithm

This paper integrates the artificial bee colony (ABC) algorithm with the sequential quadratic programming (SQP) to create the new hybrid optimization algorithm, ABC–SQP, for solving global optimization problems and damping of low frequency oscillations in power system stability analyses. The new algorithm combines the global exploration ability of ABC to converge rapidly to a near optimum solution and the accurate local exploitation ability of SQP to accelerate the search process and find an accurate solution. A set of well-known benchmark optimization problems is used to validate the performance of the ABC–SQP as a global optimization algorithm and to facilitate a comparison with the classical ABC. Numerical experiments demonstrate that the hybrid algorithm converges faster to a significantly more accurate final solution for a variety of benchmark test functions. Power system stabilizers and supplementary static VAR compensator controllers are designed for two-area–four-machine and five-area–sixteen-machine systems to illustrate the feasibility and effectiveness of the new method in power systems. The performance of the proposed ABC–SQP algorithm is compared with the classic ABC and the genetic algorithm (GA) through eigenvalue analysis and nonlinear time-domain simulation. The simulation results indicate that the controllers designed by the ABC–SQP perform better than those designed by ABC and GA.

Course stability of a ship towing system in wind

This paper proposes a numerical model for analyzing the course stability of a towed ship in uniform and constant wind. The effects of an unstable towed ship and a stable towed ship were recorded using numerical analysis at various angles and velocities of wind. The stability investigation of the ship towing system was discussed using the linear analysis, where a tug's motion was assumed to be given. When the tug and the towed ship's motions were coupled through a towline as a proper model of the ship towing system, their dynamic interactions during towing was then captured using towing trajectories and analyzed using nonlinear time-domain simulation. With increasing wind velocity, the simulation results revealed that the towing instability of the unstable towed ship was recovered in the range of beam to quartering winds; however, the towing stability of the stable towed ship in head and following winds gradually degraded. It should be noted that this towing instability might have resulted in the impulsive towline tension and could led to serious towing accident e.g. towline breakage or collisions.

Optimal Power Sharing of an Inverter-Based Autonomous Microgrid

Stability of the autonomous microgrids while sharing the power between multiple distributed generation (DG) units is an important task. Conventional droop control is usually used for power sharing between DGs. Power sharing coefficients and controller parameters affect the stability of the microgrid. In this paper, to improve the transient dynamic response of the microgrid, a power derivative-integral term is added to the conventional droop control. The design problem is formulated as an optimization problem. The power sharing coefficients and controller parameters are obtained using the particle swarm optimization (PSO) to achieve the microgrid stability based on power error minimization. Nonlinear time domain simulation is executed to investigate the proposed controller effectiveness for different disturbances. Finally the results show satisfactory performance with efficient transient damping characteristics of the autonomous microgrid.

Controller Design of STATCOM for Power System Stability Improvement Using Honey Bee Mating Optimization

Damping of low frequency electromechanical oscillations is very important for a safe system operation. The fast acting, of a static synchronous compensator (STATCOM) which is capable of improving both steady state and dynamic performance permits newer approaches to system stabilization. This paper presents a novel methodology for tuning STATCOM based damping controller in order to enhance the damping of system low frequency oscillations. The design of STATCOM parameters are considered an optimization problem according to the time domain-based objective function solved by a Honey Bee Mating Optimization (HBMO) algorithm that has a strong ability to find the most optimistic results. To validate the results accuracy, a comparison with Genetic Algorithm (GA) has been made. The effectiveness of the proposed controller is demonstrated through nonlinear time-domain simulation and some performance indices studies over a wide range of loading conditions. The simulation study shows that the designed controller by HBMO performs better than GA in finding the solution. Moreover, the system performance analysis under different operating conditions shows that the φ based controller is superior to the C based controller.

A Novel Objective Function and Algorithm for Optimal PSS Parameter Design in a Multi-Machine Power System

This paper proposes a novel objective function and algorithm to obtain a set of optimal power system stabilizer (PSS) parameters that include a feedback signal of a remote machine and local and remote input signal ratios for each machine in a multi-machine power system under various operating conditions. A novel function called the damping scale is proposed and formulated as an objective function to increase system damping after the system undergoes a disturbance. Three existing objective functions of the damping factor, damping ratio, and a combination of the damping factor and damping ratio were analyzed and compared with the proposed objective function. A novel algorithm called gradual self-tuning hybrid differential evolution (GSTHDE) was developed for rapid and efficient searching of an optimal set of PSS parameters. GSTHDE uses the gradual search concept on STHDE to enhance the probability of searching for an optimal solution. Eigenvalue analysis and nonlinear time domain simulation results demonstrated the effectiveness of the proposed objective function and algorithm.

A New Robust Multi-machine Power System Stabilizer Design Using Quantitative Feedback Theory

Small-signal oscillations is one of the important problems in power system operation that caused by insufficient natural damping in the system. This paper uses the Quantitative Feedback Theory (QFT) to design a new robust PSS for multi-machine power systems able to provide acceptable damping over a wide range of operating points. In the design procedure the main purpose is to reject the load fluctuations and, therefore, a particular transfer function is used as the nominal plant. The parametric uncertainty in power system is readily handled using QFT. The decentralized design with a simple structure is easily applied to multi-machine power systems. The nonlinear time-domain simulations are carried out to validate the effectiveness of the proposed controller. Results clearly show the benefits of the proposed controller for stability enhancement of power systems.

Rough water performance of lightweight high-speed craft

Previous studies have shown how the use of composite materials and application of sophisticated design methods can give significantly lighter high-speed craft structures than what is normally achieved for traditional aluminium designs. A reduction in structural mass and a corresponding reduction in displacement improve the craft calm water performance but can be unfavourable regarding the rough water performance. Here, the rough water performance of two versions of a fast patrol vessel, one in aluminium and the other in carbon fibre sandwich, is studied with simplified semi-empirical methods and more advanced non-linear time domain simulations. In speeds up to 30 knots, the rough water performance of the two craft versions is found to be practically equal. At higher speeds, the lighter composite craft experiences higher vertical accelerations than the heavier aluminium craft, which implies less operational availability. Using trim ballast tanks, the rough water performance of the lighter craft is improved, and it is shown that the acceleration levels can be reduced and even lowered relative to the heavier aluminium craft. This means that the calm water advantages of a lighter composite vessel can be utilized with the same ride comfort and operational availability as for a heavier aluminium vessel.

Development of a non-reflecting boundary condition for multidimensional nonlinear duct acoustic computation

The quality of any time-domain nonlinear CFD simulation of silencers is determined by the modeling procedure used for the anechoic termination at the boundary end of the computational domain. In this study, a novel anechoic boundary condition based on the characteristic theory combined with the linear relaxation method has been developed in an open source CFD code. Wave propagation in ducts and mufflers has been analyzed and the effect of the damping properties of the boundary condition has been studied. The study shows that the explicit damping of the solution vector produces good performance at all the frequencies with acoustic waves having varying incidence to the boundary. Also, results indicate that numerical reflection of acoustic waves with high incident angles is reduced if the damping is applied at the boundary within the semi-implicit solution of the governing equations. Finally, the boundary condition has been applied together with a nonlinear solver to evaluate the acoustic attenuation performance of circular flow-reversing chambers and single-plug perforated mufflers with and without mean flow velocity of the gas. Code validation has been carried out against experimental data.

Optimal IPFC signal selection and damping controller design using a novel current injection model in a multi-machine power system

This paper develops a novel approach to model the Interline Power Flow Controller (IPFC) with the purpose of enhancing the power system dynamic stability. The dynamic behavior of the IPFC is modeled using a new and detailed current injection model. On the basis of designing a supplementary damping controller, the effectiveness of the proposed model in robust damping of the oscillations is evaluated. Thus, the problem of attaining the damping controller parameters transmitted into an optimization process which is solved using Particle Swarm Optimization algorithm (PSO). The PSO has a strong and reliable capability to find out the optimistic solution. The optimization procedure is performed in a multi-machine power system and under various operating conditions. Assessment the derived results from the nonlinear time domain simulation and through some performance indices with considering to a severe transient disturbance clearly indicates the major performance of the proposed model and the model based designed controller in improvement the system stability margins. Moreover, to identify the most suitable IPFC control signal, a precise evaluation of the employed indices is accomplished. Numerical results verify the superior stabilization effect of the m1 (one of the IPFC control signals) in the wide range of operating conditions.

An efficient particle swarm optimization technique with chaotic sequence for optimal tuning and placement of PSS in power systems

This paper presents a novel and efficient method for the optimal tuning and placement of power system stabilizer (PSS). The proposed modified particle swarm optimization (MPSO) integrates the particle swarm optimization with passive congregation (PSOPC) and the chaotic sequence. Passive congregation helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search. In addition, the chaotic sequence concept is introduced to improve the global searching capability and prevent the premature convergence due to local minima. The proposed optimization procedure handles the problem-specific constraints, in this case it is related to low frequency oscillations in power systems and PSS, using a penalty function. Based on this, tuning and placement of PSS over a wide range of system configurations is formulated as a multi-objective function where the main objective is the aggregation of the three objectives related to the damping ratio and damping factor, and the number of PSS. The robustness of the proposed PSS tuning technique is verified on a multi-machine power system under different operating conditions. The performance of the proposed MPSO is also compared to the PSOPS and PSO, genetic algorithm through eigenvalue analysis, nonlinear time-domain simulation and statistical tests. Finally, the proposed method is applied to find out the best candidate machines to be equipped with PSSs. The obtained results showed that the new method can find the best placements and the optimum PSSs parameters simultaneously with an excellent global damping performance.

Multi-machine power system stabilizer design using improved particle swarm optimization (PSO) with time-varying acceleration coefficients

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort. Key words: Power system stabilizer (PSS) design, particle swarm optimization, power system dynamics, time-varying acceleration coefficients.

New Trends for the Nonlinear Measurement and Modeling of High-Power RF Transistors and Amplifiers With Memory Effects

Power amplifier (PA) behavior is inextricably linked to the characteristics of the transistors underlying the PA design. All transistors exhibit some degree of memory effects, which must therefore be taken into account in the modeling and design of these PAs. In this paper, we will present new trends for the characterization, device modeling, and behavioral modeling of power transistors and amplifiers with strong memory effects. First the impact of thermal and electrical memory effects upon the performance of a transistor will be revealed by comparing continuous wave and pulsed RF large-signal measurements. Pulsed-RF load-pull from the proper hot bias condition yields a more realistic representation of the peak power response of transistors excited with modulated signals with high peak-to-average power ratio. Next, an advanced device modeling method based on large-signal data from a modern nonlinear vector network analyzer instrument, coupled with modeling approaches based on advanced artificial neural network technology, will be presented. This approach enables the generation of accurate and robust time-domain nonlinear simulation models of modern transistors that exhibit significant memory effects. Finally an extension of the X-parameter (X-parameter is a trademark of Agilent Technologies Inc.) behavioral model to account for model memory effects of RF and microwave components will be presented. The approach can be used to model hard nonlinear behavior and long-term memory effects and is valid for all possible modulation formats for all possible peak-to-average ratios and for a wide range of modulation bandwidths. Both the device and behavioral models have been validated by measurements and are implemented in a commercial nonlinear circuit simulator.

Assessing the Dynamic Stability of an Offshore Supply Vessel

The dynamic stability of a typical offshore service vessel operating under stability critical operating conditions was investigated. Excessive roll motions and relative motions at the stern were studied for two loading conditions for ship speeds ranging from zero to the design speed. A linear frequency-domain seakeeping analysis was followed by nonlinear time-domain simulations of ship motions in waves. Based on results from these methods, critical scenarios were selected and simulated using finite-volume solvers of the Reynolds-averaged Navier-Stokes equations to understand the phenomena related to dynamically unstable ship motions and to confirm the results of the simpler analysis methods. The results revealed the possibility of excessive roll motions and water run-up on deck; countermeasures such as a ship-specific operational guidance are discussed.

Robust decentralized multi-machine power system stabilizer design using quantitative feedback theory

A new robust power system stabilizer (PSS) design using Quantitative Feedback Theory (QFT) for damping electromechanical modes of oscillations and enhancing power system stability is proposed in this paper. The design procedure is carried out on a multi-input–multi-output (MIMO), non-minimum phase and unstable plant. A multi-machine electric power system with system parametric uncertainties is considered as a case study. To show the effectiveness of the QFT technique, the proposed method is compared with a conventional PSS (CPSS) whose parameters are tuned using the classical lead-lag compensation and genetic algorithms. Several nonlinear time-domain simulation tests indicate that the suggested control scheme is robust to the changes in the system parameters and also to successfully reject the disturbances. The results also show that the performance of the QFT method given in this paper is more desirable than CPSS and genetic algorithm (GA).

RTDS Implementation of the Optimal Design of Grid-connected Microgrids Using Particle Swarm Optimization

The dynamic nature of the distribution network challenges the stability and control of the microgrid. In this paper, a simplified simulation model of an inverter-based microgrid in the grid-connected mode is implemented in real- time on a Real-Time Digital Simulator (RTDS®). The simulation is performed fast because RTDS works in continuous sustained real-time. All components such as the inverter bridge, LC filter, coupling inductor and grid are modeled using their physical representation in standard library blocks. The inverter bridge is modeled by the assumption of ideal sources. Optimal design of the LC filter, PI controllers, and damping resistance obtained using particle swarm optimization (PSO) in the optimal nonlinear model of the grid-connected microgrid is used in the simulation model. Nonlinear time domain simulation has been carried out to assess the effectiveness of the proposed controllers under disturbance. The results show satisfactory performance with efficient damping characteristics of the microgrid considered in this study. Additionally, the effectiveness of proposed approach for optimizing different parameters and its robustness have been confirmed through the nonlinear time domain simulations. The performance of this controller has been verified in simulation using a RTDS.

Performance Comparison of Invasive Weed Optimization and Particle Swarm Optimization Algorithm for the tuning of Power System Stabilizer in Multi-machine Power System

In this paper, two evolutionary algorithms- Invasive Weed Optimization (IWO) based power system stabilizer (PSS) and particle swarm optimization (PSO) based power system stabilizer is designed for multi-machine power system to compare their tuning performances. IWO is a derivative-free real parameter optimization technique that mimics the ecological behavior of colonizing weeds. PSO is also a derivative-free and flexible optimizer which is powered by the behavior of organism, such as bird flocking. Eigen-value based objective function is considered for the tuning of PSSs to enhance system damping of electromechanical mode. The performance of proposed IWO-based PSS and PSO-based PSS is tested and demonstrated under different disturbances for a four machine example power system. The Eigen value analysis and non-linear time domain simulation results shows that both IWO-based PSS and PSO-based design can successfully damp out the oscillations and thus improve the stability of the system. However, the abilities like faster convergence and greater shifting of critical modes to the left of s-plane keeps the choice of IWO based design in front of PSO based design for the system under consideration.