Lead-lag Type Research Articles

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.

Recommendations of Optimal Sampling Rates for Periodic Output Feedback Based Discrete Mode PSS

In this paper, an attempt is made to recommend the optimal sampling time period for Periodic Output Feedback (POF) based discrete mode power system stabilizer (DPSS). Various collection of input and output sampling time interval has been used in the designing of POF based DPSS. The Particle Swarm Optimization (PSO) technique is used to obtain the optimal gain matrix of the POF controller as well as the optimal sampling time intervals. The effectiveness of POF based DPSS over continuous mode lead-lag PSS is certified using small-signal stability studies. The parameters of lead-lag type continuous mode PSS is also tuned using the PSO technique. The PSS is designed using POF technique for single machine infinite bus (SMIB) system, considering a variety of sampling time intervals at input-output port. Finally, a trial is made to propose an optimum input and output sampling time period for SMIB test power system, through simulation studies.

An optimization methodology of susceptance variation using lead-lag controller for grid connected FSIG based wind generator system

In wind power system, low frequency oscillations are observed due to imbalance between mechanical input and electrical output. Hence, variable susceptance controllers are being adopted to mitigate these oscillations. However, improper modulation of control parameters also leads to system instability. Therefore, we propose an optimization methodology for mitigating low frequency oscillations in wind power generation system. To visualize our methodology, we use a lead-lag type variable susceptance controller for fixed speed induction generator (FSIG) based wind generation system. Then, we optimize gain and time constants of lead-lag controller using three optimization algorithms: particle swarm optimization (PSO), genetic algorithm (GA), and flower pollination algorithm (FPA). Later, we perform non-linear time domain simulation and quantitative analysis to find average fitness, standard deviation, run time, and iteration number for these optimization algorithms. Moreover, non-parametric statistical analysis, such as Kolmogorov–Smirnov and Wilcoxon signed-rank tests are employed for identifying statistically significant differences among these algorithms.

The causal nexus between oil prices and equity market in the U.S.: A regime switching model

The aim of this paper is to analyse the causal link between monthly oil futures price changes and a sub-grouping of S&P 500 stock index changes. The causal linkage between oil and stock markets is modelled using a vector autoregressive model with time-varying parameters so as to reflect changes in Granger causality over time. A Markov switching vector autoregressive (MS-VAR) model, in which causal link between the series is stochastic and governed by an unobservable Markov chain, is used for inferring time-varying causality. Although we do not find any lead–lag type Granger causality, the results based on the MS-VAR model clearly show that oil futures price has strong regime prediction power for a sub-grouping of S&P 500 stock index during various sub-periods in the sample, while there is a weak evidence for the regime prediction power of a sub-grouping of S&P 500 stock indexes. The regime-prediction non-causality tests on the MS-VAR model show that both variables are useful for making inference about the regime process and that the evidence on regime-prediction causality is primarily found in the equation describing a sub-grouping of S&P 500 stock market returns. The evidence from the conditional non-causality tests shows that past information on the other series fails to improve the one step ahead prediction for both oil futures and stock returns.

An approach to optimum combustion control using parallel type and cross-limiting type technique

In the paper, a new approach to the combustion control by introducing the parallel type air–fuel combustion control and cross-limiting type (or lead-lag type) combustion control technique designed in one control system in a boiler is presented. This new approached combustion control system is designed in such way that controlled the air–fuel ratio in furnace in parallel way for small steam demand variation and in cross-limiting way for high steam demand variation. This approach does not require any extra field instrumentation or modified process parameter. All original instruments are used to measure the process parameters for combustion control and final control elements controlled the process. It is shown that air and fuel flow can be successfully optimized for the required steam demand by new designed combustion control. The accurate air–fuel ratio obtained in the proposed technique also minimizes some problems of the conventional system like incomplete combustion during sudden load change, boiler stuck-up problem and bump problem. The complete derivation of the required mathematical models is reported in the paper. Performance of three boilers incorporated with the proposed system is observed for a long period and the performance report is presented. A very efficient performance in three boilers has been observed.

IMP를 이용한 근접장 기록 장치의 디스크 진동 및 편심 보상

Information storage devices using disks have a disk vibration at the frequency which is equivalent to the disk rotational speed. They also have a track vibration due to the disk eccentricity at the same frequency. In near field recording systems, the former affects the air-gap servo and the latter affects the tracking servo. In this paper, we introduce a novel control algorithm based on the internal model principle to both servos. A controller block designed by the principle is connected to the base lead-lag type compensator in parallel in order to cancel the repeatable run-out due to the disk vibration or eccentricity. Simulation and practical application of the algorithm on a near field recording system show good servo performance.

A DAMPING CONSTANT LIMITATION DESIGN OF POWER SYSTEM STABILIZER USING HYBRID DIFFERENTIAL EVOLUTION

This paper is used to investigate a novel design of lead-lag type power system stabilizers for a multi-machine power system. In the design procedures, the minimum damping constants requirements of all of electromechanical modes can be designated and several typical operating conditions can be considered at the same time. The hybrid differential evolution (HDE) method is used to tune the parameters of power system stabilizers. In the design procedures, a region in the left half complex plane bounded by a line with a given negative real value is given. Thus, at the final step of the HDE, all of electromechanical modes should be moved to or near this region to have a smaller objective function value. In this paper, the objective function is chosen to let the design results have small real parts of electromechanical modes. Since the speed deviations are used as the feedback signals of the power system stabilizers, the stabilizers could be implemented easily. Because several operating conditions are considered in the design of stabilizer parameter values, the damping forces are ensured effective in those operating conditions simultaneously. Nonlinear system time domain simulations are used to demonstrate the design results.

Active vibration isolation of a large stroke scanning probe microscope by using discrete sliding mode control

Active vibration isolation is gaining increased attention in the ultra high precision applications to effectively treat the unavoidable ground vibration. The use of active vibration isolation is now being explored for the Molecular Measuring Machine (M 3) at the National Institute of Standards and Technology to improve its imaging resolution. The M 3 system uses a Mallock suspension to establish a non-rotation constraint to the stage motion. The vibration isolation system has to work within the Mallock geometry. The system is also a six-input–six-output system; therefore, a clever design is needed to maximize the controller performance while limiting it to within the stability range. The control algorithm adopted uses discrete sliding mode control, taking advantage of its easy computer implementation and its robust high performance properties. The experimental results show that the controller is effective over the operating frequency band and is superior to the conventional lead–lag type controller.

Application of H∞ Control to Improve the Current and Speed Loops of Switched Reluctance Motor Drives

In this paper the H∞ robust control technique is applied to design a switched reluctance motor drive where the rotor position sensor provides just six pulses per revolution. A control system analyzer is used to obtain the frequency responses at each design step. To reduce the effect of the inherent phase inductance variations, an H∞ two-degree-of-freedom control scheme is designed in the current-loop of the drive to achieve the demanding time-response specifications. In order to have a good load torque disturbance rejection ability, the H∞ loop shaping procedure is employed to construct a lead-lag type controller in the speed-loop of the drive. The designed H∞ controllers are evaluated in real-time experiments with a digital signal processor (DSP). The results demonstrate the effectiveness of the proposed strategy in comparison with that of a conventional design.