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This paper proposes to optimally coordinate multiple Energy Storage System (ESS) based stabilizers and Power System Stabilizers (PSS) to increase damping in a multi-machine power system using an improved particle swarm optimization (IPSO). The IPSO has the strong and global searching ability and high efficiency by applying chaos initialization and simulated annealing (SA) algorithm in iteration. All eigenvalues, including both electromechanical and non-electromechanical modes, that meet the stability requirements in a wide range of operating conditions have been included in the objective function. In the 4-machine power system, the power system oscillations are effectively suppressed at different operating conditions by multiple ESS-based stabilizers and PSSs coordinated by IPSO, where the damping effect is better with the stabilizers designed by the IPSO than with the stabilizers tuned individually by the conventional compensation method. The results show the validity, robustness and superiority of the IPSO design.

Many agricultural operations involve the coordination of multiple tasks executed by several different machines. Additionally, an envisioned paradigm shift away from using a few large machines that are operated by one person, to multiple small automated machines, will result in coordination becoming even more important. Using scheduling and optimisation algorithms to create a work plan for multiple machines can reduce the resources used, such as time, costs and fuel, and increase the work capacity. In this paper, a scheduling and optimisation algorithm is presented aimed at the inter field scheduling of multiple tasks at multiple locations for multiple vehicles.

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.

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.

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.

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 modeling and analysis of the impact of Solar Photovoltaic (PV) on the small signal stability of power system are explored. The analysis provides explanations of the impact of the closed-loop control on the power system stability. Two system models, Single Solar Infinite Bus (SSIB) system and solar connected multi- machine system are considered. In model of PV, module variable are algebraic that is, they change instantaneously and the modeled dynamics are those of the power converter controller. The discussion considers maximum power point tracking, dc link voltage and current controller. In case of SSIB sensitivity to different weather conditions such as irradiance, temperature is studied. Also sensitivity to different power system conditions such as voltage variation, reactive power support from solar is studied. In multi-machine case impact of different active and reactive power injection levels is analyzed. The observations and conclusions obtained from eigenvalue, participation factor analysis suggest that even though the PV generation system dynamic do not participate into low frequency oscillation modes, its control can influence small signal damping depending based on its location in the system.

The main purpose of this paper is to design a non-linear second order sliding mode control for transient stability of two generator system (TGS). Second order sliding mode algorithms such as Twisting Algorithm (TA) and Super Twisting Algorithm (STA) have been applied and their simulation results are compared. The equilibrium point of TGS is maintained after the clearance of fault and the system is in post fault condition. Simulation results verify the proposed controller. The advantage with this type of control is that it does not require linearized model for its implementation and reduced chattering effect.

The design of excitation controllers to improve transient stabilization of power systems is a topic of renewed interest in the control community. Existence of a state– feedback stabilizing law for multi–machine aggregated reduced network models has recently been established. In this paper we extend this result in two directions: first, in contrast with aggregated models, we consider the more natural and widely popular structure–preserving models (SPM) that preserve the identity of the network components and allow for a more realistic treatment of the loads. Second, we explicitly compute a control law that, under a detectability assumption, ensures that all trajectories converge to the desired equilibrium point, provided that they start and remain in the region where the model makes physical sense.

An application of gain scheduling theory to multi machine stabilization control is proposed in this paper. And, a design method of a generator control system based on the gain scheduling theory for multi-machine power systems is proposed. Subsequently a decentralized control is carried out which considers interaction between the generators directly, that is to say, we regard the non-diagonal blocks of the whole system matrix as a disturbance matrix. Moreover, we confirm that the multi input generator control system is effective in using the control system based on the H infinity control theory.

Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

The researches on decentralised and/or adaptive control of power systems have received a great interest in recent years. In particular, the emphasis of most adaptive approaches towards improved stability has been placed on the utilisation of controller based on single-input/single-output models of single machine systems. Unfortunately, this approach does not guarantee an adequate performance in multi-machine system due to the strong interaction among machines. For this reason, in the paper, a decentralised model reference adaptive control (DMRAC) technique has been used to design a controller for a multi-machine system. In fact, considering as subsystem reference model for each machine the dynamic system determined by an appropriate optimal control law, the proposed DMRAC allows to adjust on line regulator gains in order to compensate the fluctuations in the interconnection. In order to show the performance of the proposed control law, some numerical experiments have been made on a four machines test system.

Electric network is now confronted with market deregulation or overload. Power System Stabilizer (PSS) is used to enhance capacity limits and improve transient stability, and it also make important role in the renewed system. This paper proposes design of excitation control with Fletcher-Powell method, which is non-linear mathematical optimization technique to realize output feedback control. The design procedure and the effectiveness are discussed through 5-machine system models. Scheme of decomposing control matrices for the large network is also discussed for successful application of the method.

The fuzzy control of the super-conducting magnetic energy storage (SMES) is proposed to improve the transient stability and damping requirements of multi-machine power systems. The effects of the SMES control on the line power transfer are considered to design a fuzzy controller. The theoretical realization of the proposed control scheme is presented. The simulation study of the New-England test system is carried out. The practical implementation based on the local measurements is explained. The improvement of the system's critical clearing time and also the system damping requirements are clearly demonstrated Finally a conclusion is provided.

The paper presents an intelligent adaptive turbine control scheme intended to improve the overall control performance of a multi-machine power system. Supplementary rule-based control is applied to the turbine governor, taking account of generator acceleration/deceleration as a measure of the imbalance between mechanical and electrical power. It is shown that this approach is capable of achieving more effective control of frequency transients on multi-machine power systems.

Our study concentrates on all aspects of co-operation among machines in performing assigned tasks. The algorithm for real-time multiobjective co-operation control presented in this paper covers issues on both task planning and task execution. From the Decision Theory point of view, the topic is viewed as a vector optimisation problem, with the goal of finding a Pareto-optimal solution for real-time task planning and task execution.

The multi-mode oscillation problem occurs in multi-machine power systems when the rotors of machines, behaving as rigid bodies, oscillate with rcspcct to one another using the electrical transmission path between them to exchange energy [1]. The ability of an adaptive self-tuning stabilizer to damp out the multi-mode power system oscillations is investigated in this paper. The studies show that such a stabilizer is very effective as it damps out the multi-mode oscillations one by one according to their dominance.

A digital voltage controller is presented, based on the optimal-aim control method, and able to enhance the dynamic and transient stability of single-and multi-machine power networks. The single-and multi-machine controllers are, thus, built upon the same theory, the multi-machine case being a generalization of the single-machine case. The theoretical basis are presented, as well as simulations results on some typical networks. The possibilities to minimize the amount of data transmission between the power plants are also studied and validated.

A systematic computer-aided procedure for the design of the power system excitation and governor controller, considering the parameter uncertainties, rapid and large load variations the network contingencies and the nonlinearities of the synchronous machine model is presented The design procedure consists in using three layer controllers with the first layer controller guaranteeing the maintenance of the nominal voltage, the nominal frequency and the scheduled powers even in the face of the disturbances, the second layer controller ensuring the desirable damping of the local and inter-tie mode oscillations and the third layer controller improving further the dynamic performance. The controller structure consists in the inclusion of an error driven filter to reject the said disturbances followed by the regulation of the augmented system consisting of the process and the filter using stabilizing compensators. The theoritical justification of the proposed multi-layer control strategy is given using input-output stability and Lyapunov reasoning.

Summary The design and operation of an on-line computer controlled multimachine drive is described. The drive consists of ten fractional horsepower synchronous motors with compliant coupling between adjacent machines. The stators are supplied at 50 Hz and the rotors are excited by individual two-phase computer-fired thyristor amplifiers. The load angles are measured digitally and the computer can thus provide a closed loop multivariable control of the load angles and thus the drive tension. Computer-fired thyristor amplifiers have the advantage that digital-analogue convertors are not required and that very simple firing circuits can be used but in previous work little time was left for other calculations by the computer. In this present work this is overcome by introducing a moderate amount of external logic. Results are given for an optimal control of the drive which is shown to be straightforward to design and implement.

In this paper we apply the decentralized H∞ control theory to interconnected multi-machine power systems. The idea is to design a local controller for each generator model so as to globally stability and optimal performance with consideration to interactions among multi-machine systems. The proposed excitation controller enables a power system to remain stable over a wide range of operating conditions. We also propose the design method of the advanced type of multi-input PSS(Power System Stabilizer) on the basis of H∞ theory.

Multiple Traveling Salesman Problem (MTSP) is an important combinatorial optimization problem. However, it is applicable to only the cases in which multiple executing individuals (traveling salesman) share the common workspace (city set). It cannot be used to handle many multi-machine engineering systems where multiple machines' workspaces are not the same and partially overlap with each other This paper proposes and formulates a new MTSP called colored traveling salesman problem (CTSP). Each of its salesmen is assigned a private city set and all salesmen share a public city set. Every set of cities is colored differently. To solve CTSP, we present two improved genetic algorithms (GA) by combining the classic one with a greedy algorithm and hill-climbing one to achieve better performance Finally, the algorithms are applied and compared through a case study. The result shows that the hill-climbing GA enjoys the best performance among the investigated ones.

Stabiliser faults in multi-machine power systems are examined in this paper where fault-masking and system reconfiguration of the nonlinear system are obtained using a virtual actuator approach. Phasor Measurement Units, which can be integrated in wide-area transmission grids to improve the performance of power system stabilisers, are utilised when reconfiguring remaining stabilisers after a local failure has made one inoperable. A stability-preserving reconfiguration is designed using absolute stability results for Lure type systems. The calculation of a virtual actuator that relies on the solution of a linear matrix inequality (LMI) is detailed in the paper. Simulation results of a benchmark transmission system show the ability of the fault-tolerant reconfiguration strategy to maintain wide-area stability of a power system despite failure in one of the stabilisers.

This paper considers the application of the supervisory discrete-time LQG control as a wide-area multi-machine power system controller subjected to unknown communication time-delays. These unknown time-delays are estimated using the Extended Kalman Filter algorithm and their estimates are then used to re-design LQG controller. The resulting LQG controller is then compared with the conventional LQG controller which ignores the presence of time-delays. The comparison is carried out on a non-linear simulation of a 2-area, 4-machine, 8-bus power system with a control objective of damping the electromechanical oscillations in the presence of unknown time-delays.

Power systems are highly n onlinear systems th at ex hibit undesirable oscillatio ns following disturbances. Power system stabilizers (PSS) are usually incorporated to provide auxiliary excitation signals to dam p these oscillations. Our objective is to im prove the PSS performance via the use of fuzzy logic and LMI techniques. A power system is viewed as a polytopic model that can be adequately represented by a Takagi-Sugeno fuzzy system. A power system stabilizer based on the parallel distributed c ontrol principle i s suggested. Ty pically, speed measurements are used as feedback signals. Consequently, a fuzzy observer is included to estimate the unmeasured states. LMI conditions that guarantee the stability and robust pole clustering of the closed loop system are derived. Simulation results of both single-machine an d multi-machine m odels co nfirm the effectiv eness of the propo sed algorithm. �