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Relentless demand for electricity concomitant with worldwide preferences to sustainable development have accelerated the need for renewable energy sources for the generation of electricity. In recent years among the diverse sources of renewable energy, wind energy has been increasingly deployed by the power industry. Normally, wind farms are far away from the load centers and hence long transmission lines are required to transmit power. High inductance of long transmission lines increases the reactive power requirement of the system which can be compensated by adding capacitors in series with the system. This can cause dynamic stability issues in Power Systems such as Sub-Synchronous Resonance (SSR) Oscillations. In most of the reported work, a separate SSR damping controller is designed to damp this oscillations. This paper proposes a novel Model Reference Adaptive Controller (MRAC) for Thyristor Controlled Series Compensator(TCSC) whose parameters can be tuned in real time under fast dynamic conditions. Parameter uncertainties and system uncertainties can be incorporated in the controller design. The adaptive tuning of controller is Lyapunov based MIT rule. A complete mathematical modeling, eigenvalue analysis of stability of SSR oscillations and the design of MRAC-based TCSC controller were accomplished using MATLB/SIMULINK. A diligent analysis of the proposed controller for SSR oscillations under varying wind speeds and for various levels of transmission line series compensations revealed that the proposed controller performed well under fast dynamic conditions.

Electric power transmission systems can be effectively controlled with FACTS devices. Unified Power Flow Controller (UPFC) is a multi-functional FACTS device that can control different parameters of the power system under dynamic conditions. UPFC consists of two Voltage Source Converters (VSCs), which are connected back to back to a common DC link. In this paper, a non linear state-space model of UPFC is developed by including VSC output voltage functions, the effect of source impedance and energy variation in the passive elements. The non linear model of the UPFC is controlled with a non linear controller. The paper also proposes a non linear controller Partial Feedback Linearization (PFBLC) for UPFC. PFBLC modifies the control input such that UPFC is able to behave linearly under all non linear dynamics occurs in the system. The proposed system is designed, analyzed and tested in an interconnected power system network. The hardware implementation is also carried out in a five bus test bench. It was observed that the UPFC shows satisfactory performance in all operating conditions.

Fast growing power system network requires highly precise control on system parameters. Nowadays, Flexible AC Transmission Systems (FACTS) has got vital importance for attaining this goal. The series FACTS controllers can improve power flow and effectively damp out the oscillations in an interconnected system. Static Synchronous Series Compensators (SSSC) consists of a three phase Voltage Source Converter (VSC) coupled to a DC link capacitor. The SSSC is maintaining overall transmission line impedance by injecting a voltage phase shifted by 90° with the line current. The dynamic equations governing VSC operation is nonlinear in nature. So nonlinear control techniques are best suited for wider operating conditions. Input-Output Feedback Linearizaton (IOFL) technique is a proficient nonlinear controller can feasibly work with a nonlinear model of SSSC. The IEEE 5 bus system is selected as the test system for proving the relevancy of the control algorithm under steady state and dynamic conditions. The power flow improvement has been observed in IEEE 5 bus system with SSSC. The results also imply that the unique robust nature of IOFL control when compared with PI controller for procuring the desired performance indices.

Stator interturn fault diagnosis of electrical machines has been a very intensely researched area. The synchronous generator (SG) is a very important component of a power system and there are only a few works that deal with the model based approach to fault diagnosis of a wound rotor synchronous generator. This work deals with the application of augmented Extended Kalman Filter (EKF) to obtain the residual signal for an SG. This signal contains the signature of the fault and can distinguish an interturn fault from a load imbalance of similar magnitude.

The power system is overwhelmed with the load demand during peak hours. The Flexible AC Transmission Systems (FACTS) have better control on the power flow in an interconnected system. Unified Power Flow Controller (UPFC) is a FACTS device can improve the control of power flow in a transmission system. The IEEE 5 bus network is a benchmark system taken in this paper in order to check the response of UPFC on the power flow enhancement. UPFC is modeled in different ways to analyze power flow and voltage improvement at each bus. In this paper UPFC is modeled as a Voltage Source Model (VSM) and that will generate reference bus voltage and phase angle at different load conditions on the receiving end of UPFC. The variation between the voltage generated by VSM and actual voltage profile in the bus is injected in the line through an injection transformer. The entire system simulation shows that voltage stability of the system is getting improved and power flow through the system with UPFC is enhanced.

As the global energy consumption is rising dramatically, wind energy is a prominent one among the renewable energy sources. The penetration of wind energy into grid is increasing day by day. In order to carry huge amount of wind power during the grid integration of large scale wind farms, high transmission line capability is demanded. In order to improve the power carrying capability of the transmission line and to improve the stability of the system, series compensation is the best practical solution. Series compensation can result in Sub-Synchronous Resonance (SSR) oscillations in the electrical system which will lead to damages in the system such as shaft failure. In this paper, a novel idea of using the Real Time Recurrent Learning (RTRL) based adaptive neuro controller is proposed for damping SSR oscillations in grid connected windfarms. The controller is trained in real time without a reference model. The effectiveness of the proposed controller is tested under varying series compensation, wind speeds and grid impedance conditions and it has been proved that the proposed controller performs far better than any other linear controllers.

This paper investigates the use of Discrete Linear Quadratic Gaussian (DLQG) Compensator to damp sub synchronous oscillations in a Thyrisor Controlled Series Capacitor (TCSC) compensated power system. The study is conducted on IEEE First Benchmark Model (FBM) in which, TCSC is modelled as a discrete linear time-invariant modular unit in the synchronously rotating DQ reference frame. This modular TCSC is then integrated with the Linear Time Invariant (LTI) model of the rest of the system. The design of DLQG includes the design of a Kalman filter for full state estimation and a full state feedback for control. Since the order of the controller is as large as the order of the system considered here(27 states), the practical implementation of the controller is difficult. Hence by using Hankels norm approximation technique, the order of the controller is reduced from 27 to 15 without losing the significant system dynamics. The eigen analysis of the system shows that the use of DLQG can damp torsional oscillations as well as the swing mode oscillations simultaneously, which is practically difficult for a conventional sub-synchronous damping controller. The performance of the system with DLQG is appreciable for all operating conditions and it shows the robustness of the controller.

The power system complexity is increasing day by day and the requirement of stable, secure and high quality electrical power is mandatory in present scenario. Flexible AC Transmission System (FACTS) devices such as Thyristor Controlled Series Capacitor (TCSC) are commonly used nowadays to improve the power system performance. This paper presents the design and Implementation of non-linear, Adaptive Real Time Recurrent Learning Algorithm (RTRL) based controller for TCSC to damp power system oscillations and enhance the stability of the system. This control scheme requires two sets of neural networks. The first set is a neuro-identifier and the second set is a neuro-controller which generate the required control signals for the thyristors.

The rapidly growing level of wind energy injection into the grid is insisting the modifications in power system. In order to improve power transfer capability, series capacitive compensation in the transmission line is adopted which leads to Sub Synchronous Resonance (SSR) oscillations. The main objective of this paper is to develop a dynamic model of Doubly Fed Induction Generator (DFIG) based wind farm connected into grid through series compensated transmission line for SSR studies. The small signal stability studies are carried out through Eigen value approach. State space representation of the whole system is developed. Different modes of the systems are identified for different wind speeds and for various series compensation levels.

Background/Objectives: To analyze the SSR phenomenon in a Squirrel Cage Induction Generator based Wind farm connected to series compensated transmission line at varying operating conditions. Methods/Statistical Analysis: There is a remarkable rise in the renewable energy sector in the current energy demand scenario, but their grid integration leads to various power system stability issues. In the case of wind power, wind farms being located far away from the grid, the integration of large scale wind farms to the utility grid requires high transmission line capacity to transport huge amount of wind power. In order to provide the power transfer capability and to improve the system stability, series compensation is the effective solution. But the series compensation may cause SSR oscillations in the system. Eigen value analysis is the method chosen to perform the Small Signal Stability analysis which examines the potential of SSR in the study system. Findings: The study investigates on the application of series capacitor for series compensation which is required during the grid integration. Series compensation of transmission line causes electro-mechanical oscillations at a sub-synchronous frequency which may finally result in serious damages in the system such as shaft failure. In order to perform the Eigen value analysis, detailed mathematical modeling of the system is developed. The pitch angle control is not taken into account while developing the system, whereas the strength of the transmission line is considered. The interconnection of three sub systems provides the complete model of the study system. The identification of system modes and damping of torsional and network modes are analyzed for various wind speed levels, various series compensation levels and various grid impedance levels. It has been observed that different grid impedance levels have a significant effect on the torsional mode oscillations of the system. Application/Improvements: As the overall system model is linearised, optimal control techniques can be developed as an application to mitigate the SSR oscillations and thereby improve the system stability.

Modern interconnected electrical power systems are complex and require perfect planning, design and operation. Hence the recent trends towards restructuring and deregulation of electric power supply has put great emphasis on the system operation and control. Flexible AC transmission system (FACTS) devices such as thyristor controlled series capacitor (TCSC) are capable of controlling power flow, improving transient stability and mitigating subsynchronous resonance (SSR). In this paper an adaptive neurocontroller is designed for controlling the firing angle of TCSC to damp subsynchronous oscillations. This control scheme is suitable for non-linear system control, where the exact linearised mathematical model of the system is not required. The proposed controller design is based on real time recurrent learning (RTRL) algorithm in which the neural network (NN) is trained in real time. This control scheme requires two sets of neural networks. The first set is a recurrent neural network (RNN) which is a fully connected dynamic neural network with all the system outputs fed back to the input through a delay. This neural network acts as a neuroidentifier to provide a dynamic model of the system to evaluate and update the weights connected to the neurons. The second set of neural network is the neurocontroller which is used to generate the required control signals to the thyristors in TCSC. This is a single layer neural network. Performance of the system with proposed neurocontroller is compared with two linearised controllers, a conventional controller and with a discrete linear quadratic Gaussian (DLQG) compensator which is an optimal controller. The linear controllers are designed based on a linearised model of the IEEE first benchmark system for SSR studies in which a modular high bandwidth (six-samples per cycle) linear time-invariant discrete model of TCSC is interfaced with the rest of the system. In the proposed controller, since the response time is highly dependent on the number of states of the system, it is often desirable to approximate the system by its reduced model. By using standard Hankels norm approximation technique, the system order is reduced from 27 to 11th order by retaining the dominant dynamic characteristics of the system. To validate the proposed controller, computer simulation using MATLAB is performed and the simulation studies show that this controller can provide simultaneous damping of swing mode as well as torsional mode oscillations, which is difficult with a conventional controller. Moreover the fast response of the system can be used for real-time applications. The performance of the controller is tested for different operating conditions.

Unified Power Flow Controller can control the power system parameters like voltage, line reactance and phase angle to control power flow in the transmission line. The control of power flow in the transmission line done by injecting a suitable voltage with a phase angle. In this paper design a decoupled control scheme for shunt and series converter to track the reference power inputs by using conventional PI controller. Modeling is done by using MATLAB/SIMULINK software. The analysis is done on the system with different power factors and load conditions. The results show that UPFC is able to track the power changes and inject a suitable voltage into the power system so that power flow can be maintained.