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In this paper, application of Posicast control method to generator excitation system is presented. The method is one of the simplest possible control design methods that can be applied to damp the oscillations caused by changing the excitation reference signal. Stability and robustness of the designed controller are shown using extensive time domain simulations. All the detailed simulations are carried out in MATLAB/Simulink environment.

The 6th and 7th generation drilling rigs are increasingly using more automated and integrated control systems to reduce the number of operators needed on the drill floor, enhance safety, increase operational efficiency and predictability and reduce wear and tear on the equipment. A comprehensive multi machine, sensor and camera control system has been installed on several rigs currently in operations in the Gulf of Mexico. This system allows one to two operators to control and monitor all the tools in the tripping or stand building sequence with the ease of using one joystick. This follow-up case study collects experiences of a rig using multi-machine control (MMC) by interviewing the rig crew, studying the drilling contractors KPIs and analysing logged data Findings and lessons learnd have led to improved machine design and rig floor layout on the next generation drilling rigs. This paper also summarizes how the use of multi-machine controls and assembly line focused rig design together improves the effects automation has on staffing and efficiency of pipe logistics.

The factors affecting the performance of multi-person and multi-machine operation under low-temperature conditions are very perplexing, and various factors are not independent, but interrelated and interactive, also the influence degree of each factor is not identical. Combining the experiment, the model of multi-person and multi-machine operation is introduced. SPSS 19.0 data processing software and gray relational analysis method are used to carry on scientific statistic analysis to the experiment data, analyze the influences of low temperature on the operation performance, quantify the operation process, and put forward the measures which could exalt the performance. It provides a basis for making training standards, realizing the military training management timely, standardized and scientific.

The due-date setting and operations scheduling problem is addressed in an unbalanced, multi-machine random job shop. The focus of the study is to demonstrate the feasibility of setting reliable static due-dates through operation flow time analysis. Response-surface mapping methodology via regression analysis is employed to model operation flow time characteristics, which are shown to be non-linear and dispatching rule dependent. Discussion points out the advantages and practicality of using static job information as opposed to dynamic shop information in setting due-dates. Simulation results and statistical analyses show the viability of setting due-dates that are tight, reliable, and consistent, using this methodology. A unique characteristic of the proposed method is that it shows simultaneous reductions in variability of manufacturing lead times, tardiness, proportion of tardy jobs, and maximum tardiness without resorting to looser due-dates.

This paper presents a global tuning procedure for conventional PSSs in a multi-machine power system using a non-linear optimization algorithm implemented in a simulation program. The main objective of this procedure is to simultaneously optimize pre-selected parameters of those PSSs having fixed parameters in coping with the complex non-linear natures of the power system. By minimizing a non-explicit target function in which the oscillatory rotor modes of the generators involved and swing characteristics between areas are included, overall power oscillations at transient conditions in the multi-machine system are improved. A four-machine power system is applied to demonstrate the efficiency and robustness of the presented tuning procedure. The results obtained from simulations validate the improvement in damping of overall power oscillations in the system. The simulation also shows that the optimized PSSs are robust in providing adequate damping for a range of conditions on the system.

In this paper the multi-machine Heffron-Phillips model is generalized to handle multi-machine power systems with frequency and voltage-dependent loads. A systematic method for extracting state equations is proposed which preserves structure and is able to account for infinite bus directly. The generalized model's block diagram is similar to that of Heffron-Phillips and is suitable for generalizing dynamic studies of networks with impedance loads to networks with frequency- and voltage-dependent loads. Two applications of this model are presented: (1) studying effects of load model parameters on dynamic stability of a five-bus network, and (2) designing a PSS for a one-machine infinite bus with frequency- and voltage-dependent local load and comparing it with a PSS designed based on impedance load.

The design and construction of advanced divertors has been one of the main topics of tokamak research during the last decade. The design of such divertors has been carried out by using 2-D plasma edge modelling codes. Many of the predictions from the modelling, which guided the optimisation procedure, have been demonstrated experimentally such as: larger operating density range for partially detached plasmas in vertical divertors compared to horizontal ones, improvement of the divertor pumping capability with more closed divertors and corresponding changes in recycling impurity exhaust following predictions. New phenomena that were hinted at by modelling but not clearly quantified, such as the increase in radiative capability of the divertor induced by the geometry, have been measured and understood by 2-D modelling. Divertor flows determined by divertor sources, which are in turn determined by the geometry, show the expected qualitative trends but detailed modelling which includes plasma drifts, not yet carried out, is required to sort out the effects of drifts and particle sources.

We developed a mixed integer programming formulation for minimizing job earliness and tardiness (ET) in a multi-machine scheduling problem. Our formulation allows setup times to depend on the job-to-job sequence, processing times to depend on the job–machine combination, due dates and cost penalties to vary for each job, and machine characteristics to be non-uniform. The model can easily provide the optimal solution to problems involving about nine jobs and three machines. Thus, the formulation shown here can provide the optimal solutions necessary for the development and validation of industrial-scale, multi-machine ET heuristics, which to date, have only been tested against other heuristics.

Summary form only given as follows. A new method has been proposed based on the method of inequalities for the coordinated synthesis of power system stabilizer (PSS) parameters in multi-machine power systems in order to enhance overall system small signal stability. Since the coordination and control of PSSs is a Pareto-optimization problem, a comprehensive list of design objectives has been presented in terms of a set of inequalities. To solve these inequalities, genetic algorithms have been applied to determine the PSS parameters.

Minimising makespan aims to achieve high utilisation of equipment and resources by getting all jobs out quickly. This is an important scheduling criterion, especially for automated systems, because of the high investment cost. The problem, however, becomes complex when many parts and machines are involved. This is because different parts may require different numbers of operations, and there are many possible schedules. For small problems, a mathematical programming model for minimising makespan is formulated. For large problems, a sequencing algorithm based on decomposition and pairwise comparison is proposed. The idea of “total overlapping time” in the sequencing algorithm is introduced to determine the solution of each sub‐schedule. It maximises the number of jobs working at different machines at the same time, while satisfying the parts’ operation precedence and machine constraints. The differences between this method and the traditional graphical method are discussed. The sequencing algorithm significantly reduces the number of schedules for consideration and hence, the computational power required.

So far the control of power systems are mostly designed for locally optimized operations and has not been considering information from remotely-located generators. This paper presents a new and novel approach to control power oscillations of generators which are located remotely. First we propose to utilize the GPS (Global Positioning Systems) signals to obtain synchronized measurements of the generators. Under the condition, we propose to design the control of the local generator using a robust decentralized control theory so as to take into account uncertainties arising from unexpected sources. The proposed method is demonstrated using a nine bus system with three generators.

This paper is concerned with the application of an adaptive fuzzy logic controller to both single and multi-machine power system simulations. Significant reductions in the amount of required calculations have been made which allow for a very computationally efficient design. A novel on-line training algorithm has been developed to reduce the error between the plant output and a reference model output. The controller is shown to provide excellent regulation for various disturbances over a wide range of operating conditions. Multi-machine analysis shows the ability of the fuzzy logic controller to damp multi-modal oscillations much more effectively than conventional algorithms.

Application of a neural adaptive power system stabilizer (NAPSS) to a five-machine power system is described in this paper. The proposed NAPSS comprises two subnetworks. The adaptive neuro-identifier (ANI) to dynamically identify the nonlinear plant, and the adaptive neuro-controller (ANC) to damp output oscillations. The backpropagation training method is used online to train these subnetworks. The effectiveness of the proposed NAPSS in damping both local and inter-area modes of oscillations and its self-coordination ability are demonstrated.

This paper presents a design procedure for a fuzzy logic based power system stabilizer (FPSS) and investigates the robustness of the FPSS for a multi-machine power system. Speed deviation of synchronous generator and its derivative are chosen as the input signals to the FPSS. A two area, five generator power system is used to illustrate the robustness of the FPSS. A normalized sum-squared deviation (NSSD) index is used for designing the FPSS and demonstrating its robustness. Nonlinear simulation tests for different disturbances and their results are discussed.

The paper presents an approach based on integral of squared error (ISE) technique for tuning of the parameters of power system stabilizers (PSS) in a multi-machine power system. The PSS are tuned sequentially, depending on which machine needs stabilization most. However, later it has been establishes that if the tuning algorithm is iterated twice or more, no particular tuning sequence is necessary. Dynamic performance with PSS tuned by the proposed method is compared with a previously reported approach in which all the stabilizers are tuned simultaneously. The proposed approach provides satisfactory system dynamic performance and the method is computationally much simpler.

This paper addresses the problem of scheduling n jobs on m identical parallel machines so as to minimize the completion time variance. Properties of optimal solutions are derived first. Then, complexity results are obtained, which show that the problem is NP-complete in the strong sense when m is arbitrary, and NP-complete in the ordinary sense when m is fixed. Two algorithms are proposed. The first algorithm can generate an optimal solution in time O ( n 2m P m (P − P m ) m−1 [m m (m − 1)!] 2 ) , where P is the sum of all the processing times and Pm is the sum of the first m largest processing times. The second algorithm can find a near-optimal solution in time O ( nP m (P − P m ) m−1 m m (m − 1)! ) . It is further shown that the relative error of the near-optimal solution is guaranteed to approach zero at a rate O(n−2) as n increases.

The phase compensation method based on the concept of damping torque has been successfully applied for the design of Power System Stabilizers (PSS) in single-machine infinitebus power systems for decades. In this paper, the application of the phase compensation method to the design of multiple FACTS-based stabilizers and PSSs in multi-machine power systems is presented. An example three-machine power system is demonstrated, where a TCSC-based stabilizer and a PSS are successfully designed by the phase compensation method to damp power system oscillations.

The existence of a Lurie-type Lypunov function for multi-machine power systems with transfer conductances is considered. New criteria are presented for the existence of this function which are very convenient to be used in practical applications. An example studied in the previous literature for four-dimensional multi-machine power systems is discussed again.

A hierarchical production planning (HPP) and scheduling model is developed to solve a real-world problem in fibre manufacturing scheduling. The problem under study requires determining production sequences in the presence of variable setup costs in a multi-machine and multi-product environment. The concept of expected setup cost is developed to reduce the difficulty of addressing sequence-dependent setup costs at the aggregate level. A mixed integer linear programming model (MILP) incorporates the logic of expert systems to minimize the number and costs of machine setups and other associated costs. At the daily operational level, a set of heuristics is developed to manage contingencies, such as machine breakdowns and changes in demand. The heuristics effectively utilize idle capacity and inventories to smooth production and avoid unnecessary extra setups, therefore maintaining system stability. Data provided by the fibre plant is used to validate the model. Compared to the actual schedule, results from th...

The application of the H∞ optimisation method to power system stabiliser design is studied in this paper. The weighting function selection and the application to multi-machine power systems are investigated in two separate parts. In this second part, it is shown that PSS design for multi-machine power systems can be translated into a problem of a series of sequential stabiliser designs. Each of them is for a very high order Single—Input Single—Output (SISO) ‘plant’ and can be formulated as an H∞ mixed-sensitivity optimisation problem. The method developed in the first part for the selection of weighting functions is also used in this second part. Applying these to a model of a 10 machine 39 bus-bar power system shows a satisfactory performance.

Power system stability is a great concern in today's interconnected power system especially when the system is subjected to a fault. These faults occasionally lead to Low Frequency Oscillation (LFO). Therefore, Shunt Flexible AC Transmission System (FACTS) devices for example, SVC are employed to provide damping to attain system stability. The performance of SVC is totally dependent on proper tuning of its controller and usually heuristic optimization techniques are used to search the best controller parameters. In this paper, a popular metaheuristic optimization technique known as Firefly Algorithm (FA) is presented for optimal design of SVC controller in multi machine power system. In the simulation, the linearized model of power system and conventional lead-lag controller as SVC damping controller are used. The performance of obtained results using Firefly Algorithm (FA) is compared with the results obtained from Particle Swarm Optimization (PSO) Algorithm. The comparison of attained results show that FA can find more optimal parameter values of SVC damping controller and subsequently enhance power system stability.

Pole placement based power system stabilizer designs are well-known for their superior control capabilities compared with the conventional lead-lag power system stabilizers. They require feedback of all the state variables. As power system state variables are generally not measurable they have not seen much of practical realization. In multi machine systems pole placement designs require feedback of other machine states as well. This paper proposes a new approach for the pole placement based PSS. In this paper, recently proposed modified Heffron Phillip’s model is used for the PSS design. Modified Heffron Phillip’s model is derived by taking the secondary bus voltage of the step-up transformer as reference instead of infinite bus. State variables of this model are locally measurable, which makes the pole placement design decentralized and independent of the external system information. The performance of the proposed controller is evaluated on 10 generator 39 bus multi - machine system over a wide range of operating conditions. The proposed PSS performance is found to be better than the conventional PSS. Keywords: Engineering, Power System Stabilizer, Small-Signal Stability, State Feedback, Linear Quadratic Regulator, Andhra Pradesh, India

In this paper, the nonlinear control problem of permanent magnet wind generators is investigated based on Hamiltonian energy method. A nonlinear design method is proposed for the multi-machine system, such that the closed-loop system is stable simultaneously. Moreover, in the presence of disturbances, the closed-loop is finite–gain L 2 stable under the action of the Hamiltonian controller. In order to illustrate the effectiveness of the proposed method, the simulations are performed which show that the gotten controller can improve the transient property and robustness of the system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2824

International audience; We deal here with a multi-machine scheduling problem with non idling constraints, i.e constraints which forbids the interruption of the use of the processors. We reformulate the problem, while using specific pyramidal profile functions, next get a min-max feasibility criterion and finally derive exact polynomial algorithms for both the feasibility problem and the makespan optimization problem.

This study presents coordinated control tuning of power system stabilizer (PSS) with thyristor controlled series capacitor (TCSC). The design of proposed coordinated damping controller is formulated as an optimization problem and the controller gains are optimized instantaneously using advanced adaptive particle swarm optimization (AAPSO). Here the multi-machine power system employed with PSS and TCSC is considered. The coordinated tuning among the damping controllers is performed on the non-linear power system dynamic model. Finally, the proposed coordinated controller performance is discussed with time domain simulations. Different loading conditions are employed on the test system to test the robustness of proposed coordinate controller and the simulation results are compared with four different control schemes.

This paper presents the application of decomposed analysis of damping contribution from a PSS installed in a real large scale Chinese power system. With the decomposition of damping function from the PSS into damping torque contribution and its connections with the power system oscillation mode of interests, a deep understanding on the PSS function is obtained in the complex large scale multi-machine power system. In the paper, the mathematical description of decomposed analysis of damping contribution from the PSS is firstly given. Then the result of application in real large-scale Chinese power system is presented.

This paper presents damping torque analysis of an automatic voltage regulator (AVR) in a multi-machine power system. Firstly in this paper, mathematic model of a multi-machine power system with AVR considered is described. Damping torque analysis of AVR is established. Then an example three-machine power system is presented to demonstrate how the damping torque analysis for the AVR is carried out. Finally, application of damping torque analysis for the AVR in a large-scale Chinese power system is presented to identify the most influential AVR on the system oscillation modes of interests.

Effectiveness of the fuzzy logic based power system stabilizer in a multi-machine power system environment is investigated in this paper. The power system used to study the performance of the stabilizer exhibits multi-mode oscillation phenomena. Machine speed deviation and accelerating power as the plant's output are used as the inputs to the stabilizer. Results of simulation studies for different operating conditions and disturbances are given in the paper.

The authors proposed a nonlinear adaptive generator control system with neutral networks for improving damping of power systems, and showed its effectiveness in a one-machine infinite bus test power system in a previous paper. The proposed neurocontrol system adaptively generates appropriate supplementary control signals to the conventional controllers such as the automatic voltage regulator and speed governor so as to enhance transient stability and damping of the power system. In this paper, the applicability of the proposed neurocontrol system to multimachine power systems is discussed. Digital time simulations are carried out for a 4-machine test power system, where one or several synchronous generators is equipped with the neurocontrol system. As a result, also in the multimachine power system, the proposed adaptive neurocontrol systems improve the system damping effectively and they work adaptively against the wide changes of the operating conditions and the network configuration.

Procedures to reduce set‐up times at individual machines have been well documented; however, very little research has been conducted on developing an effective strategy to prioritize set‐up reduction procedures in a multi‐machine facility. Describes a new and innovative way – a throughput approach – to prioritize set‐up reduction procedures in a multi‐machine production system.

Certain maintenance procedures fail to perform prior to a pre-specified deadline and need extra time for successful accomplishment. Processing times under this specific deterioriation are represented by a step function. We study the problem of makespan minimization of step-wise deteriorating jobs. We introduce compact integer programming formulations. We then focus on heuristic methods, since even the case of single machine single-step deterioration is NP-complete. These methods are extended to settings of multi-machine and multi-step deterioration. Our numerical tests indicate that the proposed algorithms are highly accurate and efficient in the context of a numerical study discussed in this paper.

In this paper, a power system stabilizer design method for single machine systems1 is extended to multi-machine systems. This is based on: (1) pseudo global system models introduced in this paper; (2) frequency response based model order reduction technique; and (3) the pole assignment algorithm for single-input multi-output control systems presented in Reference 1. The new design method is also applied to a practical ten-machine power system.

A novel procedure for computer-aided design of feasible non-linear controls for remote, supervisory, optimum control of fully automated low-power, multi-machine hydroelectric plant has been developed. It is based on systems engineering considerations and the use of classical equipment typically installed in low-power, multi-machine plants, such built on irrigation and water-supply systems or mountane streams. The engineering robustness in operation is of major concern in such plants, as demonstrated by the application of this procedure to twe real-world plants. The actual development stems from the attempt to derive a kind of practical yet not purely heuristic time-optimal controls with constrained magnitude, which are easily embodied in a C++ programmed command control suited for small hydro-plants where classical relay-type actuator and alike implement control actions.

List scheduling algorithms are commonly used for multi-machine scheduling problems, especially for those with precedence relationships among operations. In most list scheduling algorithms, operations are scheduled forward. In this paper, we suggest a backward approach in which the operations are scheduled backward. We discuss some details that must be considered when applying the backward approach to problems with due dates and suggest several methods of defining parameters needed in the backward approach. Performance of this approach is tested on job shop problems and identical machine problems with several types of precedence constaints.

The effectiveness of an artificial neural network (ANN), functioning as a power system stabilizer (PSS), in damping multi-mode oscillations in a five-machine power system environment is investigated in this paper. Accelerating power of the generating unit is used as the input to the ANN PSS. The proposed ANN PSS using a multilayer neural network with error-backpropagation training method was trained over the full working range of the generating unit with a large variety of disturbances. The ANN was trained to memorize the reverse input/output mapping of the synchronous machine. Results show that the proposed ANN PSS can provide good damping for both local and inter-area modes of oscillations. >

Interconnected power grid becomes more complex and tends to be vulnerable to unwanted disturbances; thus, transient stability of the power system becomes an important research topic. In this paper, we propose a control law that not only enhances the transient stability but also makes the system to satisfy output synchronization. The key idea of this paper is that the power system can be realized as Port-Controlled Hamiltonian(PCH) model and the model automatically satisfies the passivity with respect to input and output relationship. Using the property, we can analyze the output synchronization by employing consensus algorithm. Through simulation results, we evaluate the synchronization analysis.

The introduction of wide area measurements has brought a need for real time assessment methods of power systems, which are accurate and fast. The time varying coefficients in synchronous machine equations make it difficult to find solutions to obtain machine voltages, currents and flux linkages when expressed in phase quantities under transient conditions. The paper presents an approach to design power system transient stability assessment using direct methods for a multi-machine network based on multiple synchronized phasors, measured from Phasor Measurement Units (PMUs) and generator parameters. The generator rotor angle was derived from phasor measurements of voltage and current, and generator parameters using direct algorithm . The method assumes that a temporary fault is applied to the system therefore the pre-fault and post-fault conditions are similar. The multi-machine system was reduced to groups denoted Single Machine to Equivalent Bus (SMEB) models and another groups denoted Load Equivalent Bus (LEB) using Parallel Algorithms (PAs) [1]. The use of these PAs eliminates the SPMUs at each bus in the system, and it is required number of SPMUs only equals the number of generator buses. So that, the Equal Area Criterion in both rotor angle domain and time domain can be applicable for the SMEBs groups to assess the system stability in real-time through the Synchro-Phasors Measurements Units (SPMUs). A temporary three phase fault was simulated at test system comprises 2-machine, 8-bus network for validating the novel algorithm.

Power system stabilizers (PSSs) are used to generate supplementary control signals for the excitation system to damp electromechanical oscillations. This paper presents an Artificial Bee Colony (ABC) optimization based approach for tuning the parameters of PSSs in multi-machine power systems. The stabilizers are tuned to simultaneously shift the undamped and lightly damped electromechanical modes of all plants to a prescribed zone in the s-plane. A multi-objective problem is formulated to optimize a composite set of objective functions comprising the damping factor and the damping ratio of lightly damped electromechanical modes. The performance and robustness of optimized PSS using ABC algorithm is then, tested on New England New York 16-machine, 68-bus system under different operating conditions. Eigenvalue analysis and nonlinear time domain simulation results shows the effectiveness and robustness of the proposed ABCPSS over CPSS under different operating conditions and system configurations.