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This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

A number of techniques have been proposed to dampen the power system oscillations in the electric power systems. Flexible alternating current transmission system (FACTS) devices are becoming one of them. Among the FACTS family, the static synchronous compensator (STATCOM), a shunt connected FACTS device, has been widely used to provide smooth and rapid steady state, limit transient voltage, and improve the power system stability and performance by absorbing or injecting reactive power. However, the influence ability depends on its placement, control signal, and place of receiving-signal in the network. In order to satisfy these issues, this paper proposes a method for optimal setting and signal position of the STATCOM into the multi-machine power systems with the aim for damping the electromechanical oscillations. This method is developed from the energy approach based on Gramian matrices considering multiple tasks on the Lyapunov equation, in which the observability Gramian matrix is used to seek an optimal location for STATCOM placement. The another is the controllability one used to determine the best local input signal placement that is chosen as a feedback signal for the power oscillation damping (POD) of STATCOM. In addition, the Krylov-based model reduction method is introduced to shorten the calculation time. The proposed method has been verified on the IEEE 24-bus system by analyzing the small-signal stability to search several feasible placements, and then the transient stability is analyzed to compare and determine an optimal placement through testing various cases. The obtained result is also compared with other optimal method.

This paper is predicated on a unique coherency identification technique, which is evident and decisive. This coherency testimony technique has the capability to spot the coherent teams accurately, that the essence of the machines within the reduced order system is sort of almost like those of the complete system. The technique involves the alpha index, delta index and a power variation index for each pre-fault and at the moment of initiating fault condition to pick out the coherent cluster of generators. These indices have the capability to see the optimum coherent teams of generators with reference to dynamic response. The Dynamic equivalent construction method is being used to replace each coherent group of generators with a single machine. Thus less computer storage and time are needed in finding the swing equations. The projected coherency identification methodology has been applied on IEEE 39 bus test power system considering three different cases and therefore the obtained results well-tried that the proposed technique is very effective in deciding the coherent teams of generators with high accuracy.

Accurate damping of inter-area and intra area oscillations are very much critical in the stability of electric power system. Power system stabilizer (PSS) is mainly used as auxiliary controllers to damp out the low frequency oscillations in the area of electric power system. The tuning of Conventional Power System Stabilizer (CPSS) for a nonlinear power system should be robust such that overall system stability can be improved under several operating points. Today's scenario, various populations based heuristic algorithms are available to minimize the effect of stability problem by properly tuning the parameters of CPSS. In this paper presents a new heuristic population based optimization technique named as Group Search Optimization (GSO) algorithm to tune the PSS parameters for a multi-machine system for different operating conditions. The importance of the GSO algorithm is evaluated and compared for damping the system oscillations during small and large disturbances, and their robustness is illustrated using the transient signal analysis.

International audience; A solution to the problem of transient stabilisation for multi-machine power systems, with transfer conductances different from zero, is given. The 3n-dimensional (aggregated) model of the n-generator system, with lossy transmission lines, non-linear loads and excitation control, is considered. A non-linear dynamic state-feedback control law that ensures, under some conditions on the physical parameters, global asymptotic stability of the operating point is constructed. To the best of the authors' knowledge only existence results - with the restrictive assumption of uniform inertia generators - are available to date for this problem. Simulation results on the New England benchmark system illustrate the performance of the proposed controller.

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.

Automation is widely used in various industries to increase the speed, accuracy and effectiveness of production and reduce the risk of hazards. In general, the manufacturing industry has a product packaging and sorting process based on size, weight, shape, height and color. Currently, the sorting process in the industry is still mostly done manually which causes human error problems, so the development of industrial automation that is low cost, easy to maintain, efficient, user friendly and more accurate needs to be done. Programmable Logic Controller (PLC) is one of the most widely used for automation equipment in the industry and can be programmed to control machine operations. In this paper, the Mitsubishi Melsec PLC with ladder diagram programming using GX work2 has been developed to control multi-machine operation by product sorting and packaging based on product color. Multi-machine operation consists of three DC motors used for conveyors, two single solenoids, proximity sensors, inductive sensors and limit switches. The proximity sensors are used to detect the products based on color. The system is equipped with an emergency button and alarm system to facilitate the implementation of troubleshooting. To facilitate communication with operators and user-friendly systems, the human machine interface (HMI) is used as an interface for system monitoring and controlling. HMI uses Pro-face from Schneider which is programmed using GP-Pro EX4.0. The ladder diagram has been implemented in the PLC and tested on hardware to simulate the system. Based on test results, MELSEC PLC can communicate with HMI and control multi-operation machines with product sorting and packaging. The machine can separate and package metal products by colour and the packaging system can be monitored and controlled remotely automatically with HMI.

A fast adaptive power system stabilizer which uses an optimal singul- adaptive observer (OSA) is proposed and investigated. The identical direct (non iteratIve) model identification approach have been used which applied to multimachme power system. In this paper, the implementation ofan adaptive PSS on the base of OSA observer m multtmachine power systems is investigated. The simulation results are corroborated the. correctness, applicableness and effectiveness of the proposed adaptive stabilizer for multimachine power systems.

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.

In recent times, renewable energy resource based bulk power plants are being implemented in power system and wind energy based farms are one amongst them. The induction machines employed in the wind farms possess different characteristics compared to conventional synchronous generator plants. The behaviour of these induction generators, can affect the stability of power system when they operate in synchronism with synchronous generators. Also, the frequency response of the power system has been deteriorated with integration of converter based wind turbine generators because of their inability to provide natural inertial response. One of the remedies for this can be to operate the doubly fed induction generators (DFIG) as a synchronous generator to provide inertial response during frequency event. In the literature, small signal stability has been analyzed for the SMIB system integrated with the wind farm. This paper offers small signal stability analysis of multi-machine power system integrating DFIG based wind farm. It further analyzes the changes in small signal response and frequency improvement while the DFIGs are operated in order to emulate the synthetic inertia. Detailed modeling of the wind generators and their integration with the multi-machine system is presented in this paper. Eigenvalue analysis has been performed for it and the effect of DFIG based wind farm on the frequency oscillations and damping of the system is 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.

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 stabilizers (PSSs) are generally used to solve the low-frequency oscillation problem. To overcome this type of oscillation, this paper presented a new method by using the genetic algorithm (GA) to identify PSS settings. The tuning of PSS parameters was formulated relying on an eigenvalue-based objective function aiming at maximizing the stability margin. This was achieved by increasing the sum of the squares of negative real parts of the system eigenvalues. The small disruptions in the form of load change take place routinely; the controller parameters should be adjusted to the changing conditions. To remedy this defect, an adjustment of parameters as a function of the load was required. Thus, a neuronal model by using a historical database determined by the GA solutions for various load levels can approximate the simulation studies, since it could estimate the stabilizer parameters in real time after the learning phase. The validity of the proposed technique was checked through the evolution simulation of the regulator parameters for a load forecast curve. These concepts were discussed in details on a multi-machine network Western System Coordinating Council (WSCC) comprising three generators and nine nodes. The eigenvalue analysis and time domain simulation results were presented at different operating conditions and under various disturbances in order to show the effectiveness of this study.

A Unified Power Flow Controller (UPFC) in Multi machine system is proposed. The UPFC model is having a voltage source. The magnitude and angle of this voltage source depends on the UPFC control parameters. For the analysis of Eigen value, power system with linearized model was developed. Poorly damped electromechanical mode is controlled by stabilizing signal. The superior stabilizing signal is selected by approach based singular value decomposition. The UPFC with voltage source model incorporated into the generator output power equation simplifies the dynamic analysis of the system and this incorporation into the generators output power equation can be easily done. This proposed model will be used to compare and determine a simple system’s dynamic behavior, equipped with an adaptive UPFC.

This paper proposes two switching controllers working in a coordinated manner to enhance the transient stability of multi-machine power systems. One is switching excitation controller (SEC) and the other is switching governor (SG). The SEC switches between a bang-bang excitation controller (BEC) and a conventional excitation controller (CEC) and the SG switches between a bang-bang governor (BG) and a conventional governor (CG), via a state-dependent switching strategy. The BEC and the BG are designed as bang-bang constant funnel controllers (BCFC), which are able to provide fast switching of excitation voltage and valve position between their upper and lower limits. A detailed steam turbine model including boiler pressure effect is considered in the controller design process. Simulation studies are undertaken in the IEEE 16-generator 68-bus power system to evaluate the control performance of the switching controllers, which include the cases that three-phase-to-ground fault and transmission line outage occur in the system, respectively. Coordination between the excitation loop and speed governing loop is studied. Two system resilience indexes are introduced, and the short-term resilience is investigated for the power systems with and without switching controllers installed, respectively.

In this study, power system stabiliser (PSS), static VAR compensator (SVC), and thyristor controlled series capacitor (TCSC) controllers are simultaneously used to increase the stability and damping of the oscillations of a multi-machine power system. By SVC, the transferrable power in the steady state can be increased and the voltage profile can be controlled along the line. TCSC can regulate line impedance and therefore, increase the transferred power of the system. PSS is added to excitation system to enhance the damping of electric power system during low frequency oscillations. SVC, TCSC, and PSS can combine with each other for further damping and stability; therefore, their coordination is very important. Then, adaptive velocity update relaxation particle swarm optimisation algorithm is used to optimise the parameters of PSS, SVC, and TCSC simultaneous controllers. The robustness of the proposed algorithm has been tested on 16-machine 68-bus power system.

In this paper, a decentralized nonlinear coordinated excitation and steam valve adaptive control combined with a modified high-order sliding mode differentiator is designed for multi-machine power system stability enhancement. The proposed control scheme is based on Lyapunov’s direct method and requires only local information on the physically available measurements of relative angular speed, active electric power and terminal voltage with the assumption that the power angle and mechanical power input are not available for measurement. Each synchronous generator is considered as a classical fifth order model that includes turbine dynamics. The simplicity of the proposed scheme and its robustness with respect to large perturbations, change in operating point and parameter uncertainties constitute the main positive features. Simulation results in the case of the Kundur 4-machines 2-area power system show the effectiveness, robustness and superiority of the proposed scheme over the classical AVR/PSS.

Accurate measurement of the rotor angle and speed of synchronous generators is instrumental in developing powerful local or wide-area control and monitoring systems to enhance power grid stability and reliability. Exogenous input signals such as field voltage and mechanical torque are critical information in this context, but obtaining them raises significant logistical challenges, which in turn complicates the estimation of the generator dynamic states from easily available terminal phasor measurement unit (PMU) signals only. To overcome these issues, the authors of this paper employ the extended Kalman filter with unknown inputs, referred to as the EKF-UI technique, for decentralized dynamic state estimation of a synchronous machine states using terminal active and reactive powers, voltage phasor and frequency measurements. The formulation is fully decentralized without single-machine infinite bus (SMIB) or excitation model assumption so that only local information is required. It is demonstrated that using the decentralized EKF-UI scheme, synchronous machine states can be estimated accurately enough to enable wide-area power system stabilizers (WA-PSS) and system integrity protection schemes (SIPS). Simulation results on New-England test system, Hydro-Quebec simplified system, and Kundur network highlight the efficiency of the proposed method under fault conditions with electromagnetic transients and full-order generator models in realistic multi-machine setups.

This paper presents a novel decentralized control scheme for a multi-machine power system with nonlinear interconnections. We adopt a recursive backstepping method and develop a novel LMI-based algorithm to construct decentralized feedback control laws that improve the disturbance attenuation ability of the closed-loop interconnected system and do not require the online optimization. Simulation results show the effectiveness of our proposed control strategy.

In this paper coordination of fuzzy power system stabilizer (FPSS) and flexible ac transmission systems (FACTS) have been considered in a multi-machine power system. The proposed model, has been applied for a wide-area power system. The proposed FPSS presented with local, nonlinear feedbacks, and the corresponding control synthesis conditions are given in terms of solutions to a set of linear matrix inequalities (LMIs). For this model, in fuzzy control synthesis, the new proposed control design method is based on fewer fuzzy rules and less computational burden. Also, the parameters of FACTS controller have been evaluated by improved honey bee mating optimization (IHBMO). The effectiveness of the proposed method has been applied over two case studies of single-machine infinite-bus (SMIB) and two areas four ma chine (TAFM) Kundur’s power system. The obtained results demonstrate the superiority of proposed strategy.

This papers concern the replacement of Static Frequency Converters (SFC) by Rotary Frequency Converters (RFC) in Railway Power Supply Systems (RPSS) operating at 16⅔ Hz. There is a need to investig ...

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, 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.

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.

This paper presents a new parameter optimization technique in order to parameter optimization of Linear Optimal Control (LOC) and Power System Stabilizer (PSS) in multi-machine power system. The optimized LOC consists of the advantages of conventional stabilizers. Also, the proposed LOC demonstrates excellent performance with fast response in multi-machine power systems. These features are developed by extended simulations and different conditions. Also, the method employs transient parameters of Q-axis for PSS and LOC in order to better damping oscillations. Simulations are performed by MATLAB software and the results proved that the proposed optimized LOC and PSS significantly improve the dynamic response of the power system in various conditions and different disturbances. After coefficient calculation for multi-machine systems, regard to transient parameters of Q-axis, multi-machine LOC and PSS parameters are optimized and the results are extracted.

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 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.

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.

This paper describes a simple and didactic procedure which illustrates the benefits of the visual aspects of MATLAB/SIMULINK for educational purposes. The novel didactic procedure is specially developed for transient stability simulation of a multi-machine power system given with full details. Structural details of various sub-models for a multi-machine power system are provided and their implementation in SIMULINK environment is outlined. Simulation results show that the developed transient simulation model is a powerful and promising tool for transient stability studies, and very helpful to understand transient stability phenomena for students and researchers. The most salient features of the developed MATLAB/SIMULINK-based model are simplicity of use, transparency, flexibility and expandability. These special characteristics are easy to understand and can be easily modified. Hence, these features make the proposed model suitable for both educational and research purposes. In addition, classroom experience has shown that the didactic procedure helps in consolidating a better understanding of power system transient stability.

This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter’s related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

A new approach for power system transient stability preventive control is proposed by performing trajectory sensitivity analysis on the one-machine-infinite-bus (OMIB) equivalence of multi-machine systems. Exact instability time/angle are determined from the equivalent OMIB power-angle curve; the trajectory sensitivity is calculated at the instability time and the transient stability of the multi-machine system is controlled by constraining the OMIB's angle excursion at the instability time to that of the critical OMIB which corresponds to the marginally stable condition of the system. The required preventive control action (generation rescheduling) can be efficiently solved via a linear programming model with the OMIB trajectory sensitivities-based constraints. Simulation results on the New England 10-machine 39-bus system and a 285-machine and 1648-bus system validate its effectiveness and superiority over previous trajectory sensitivity applications to this problem.

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.

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 proposes a new method to improve the transient stability of a multi-machine power system integrated with hybrid renewable sources. The study aims at investigating and understanding the transient stability of the system with constant and varying power injection by doubly fed induction generator (DFIG) based wind farm and solar photovoltaic (PV) farm. The controllers of the converters in DFIG and Solar PV system are modified in such a way that during fault period both the renewable sources allow maximum reactive power injection unlike during normal period. This coordinated reactive power support during fault causes improvement in the bus voltage magnitude and thereby enhance the overall system transient stability. Faults are considered in different load buses and stability is compared for the cases with and without the proposed controller. The study is carried out in WSCC 3-machine 9-bus system and the platform used for simulation is PSCAD/EMTDC.

Due to the increased deployment of new technologies such as renewable sources and smart meters, complex and unexpected interactions are occurring in power systems. The dynamic instability in power systems are caused by the existing imbalance between mechanical input and output power. For damping these oscillations, power system stabilizer (PSS), and static synchronous compensator (STATCOM) can be used. In this paper, a unique fuzzy controller for dynamic stability of PSS and STATCOM in multi-machine power system is designed. Particle swarm optimization (PSO) combined with genetic algorithm (GA) is used for fuzzy controller optimization. Proposed method is tested on IEEE 39-bus system under disturbance. The simulation results verify the efficiency of the proposed method for dynamic stability of power system.

This paper proposes a nonlinear control approach for a multi-machine power system with DFIG-based wind turbines. The proposed approach aims at coordinating the design of the controllers of the doubly fed induction generator and that of the Static Synchronous Compensator (STATCOM) device. Its main objectives are to improve the transient and voltage stability of the inter-connected system. The nonlinear approach is based on the zero dynamics technique. The effectiveness of the proposed approach was evaluated via eigenvalue analysis and transient simulations. Further assessments of its dynamic performance were performed by considering a three phase fault condition. The obtained results were compared to that of a traditional power oscillation damping (PRINT) approach. Significant improvements in the transient behavior and power stability of the inter-connected power system are among the main positive features of the proposed design.

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...

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.

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

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 a new dynamic model of multi-machine power system equipped with GUPFC for power system study, and using PSS and GUPFC POD controller some effective control schemes are proposed to improve power system stability. Based on UPFC configuration, an additional series boosting transformer is considered to define a GUPFC configuration and its mathematical model; Phillips-Heffron scheme is used to formulate machine model, and modification of network dealing with GUPFC parameter is carried out to develop a MIMO as well as comprehensive power system with GUPFC model. Genetics Algorithm method was proposed to lead-lag compensation design, this technique provides the parameter controller. The controller produced supplementary signals, the PSS for machine and POD for GUPFC. By applying a small disturbance, the dynamic stability power system was investigated. Simulation results show that the proposed power system with GUPFC model is valid and suitable for stability analysis. The installation of GUPFC without POD decreased the damping oscillation. But, the results show that the presence of GUPFC in power system network provided by PSS and POD controller is very potential to improve system stability. A 66% overshoot reduction could be reached, it is obtained 12 s in settling time (shorter), although the rise time become 700 ms longer. Simulation results revealed that the role of POD controller is more dominant than the PSS, however both PSS and GUPFC POD controller simultaneously present a positive interaction. Phase angle of converter C, δC is the most significant control signal POD in oscillation damping.

In this article, a new evolutionary algorithm presented in order to optimally design stabilizers of multi-machine power system. This article utilizes Hybrid Particle Swarm Optimization (HPSO) technique to search for optimized amounts of power system stabilizer (PSS). The strength of presented method to create initial amounts was proved. Efficiency and capability of HPSOPSS was tested under different turbulences and loading modes for different multi-machine systems. Data analysis and results of nonlinear simulations, delineated the usefulness of HPSOPSS in damping local and in-area frequency modes; and this coordination has a remarkable effect on execution of loading modes and arrangement of power system. Totally, potential and priority of the presented method in proportion to other common methods was proved.

This paper presents the implication of adding various FACTS controllers in multi-machine power system environment in coordinated control manner for enhancement of voltage stability requires an appropriate mathematical model of the power system and the FACTs controllers such as a Static Var Compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC). The DAE (Differential Algebraic Equation) methodology for multi-machine system has been is used in this paper. Event tough the SVC model has been incorporated in DAE model, TCSC model has not been incorporated. So the purpose of this paper is to derive a TCSC model such that it can be incorporated in DAE model of power system. Further in a large power system there may be more than one FACTS controllers, therefore it is important to develop a combination of series and shunt FACTS controllers that can be incorporated in the DAE model in Modular fashion. The models developed have been utilized for eigen-value analysis of IEEE 9-bus 3-machine power systems. There are many commercial packages available for transient simulation and analysis of power systems. The transient simulation packages (e.g. EMTDC/PSCAD) allow incorporation of FACTS controller models. This facility is however not available in the small signal stability analysis packages. The objective of this paper is to develop a methodology to incorporate FA CTS controllers in a modular fashion to facilitate eigen-value and voltage stability analysis using MATLAB toolbox.