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Solar Power is a sustainable renewable energy source which does not produce environmental pollution like conventional sources. The solar PV power can be transferred to grid using single stage Voltage Source Inverter (VSI) topology. Maximum Power Point Tracker (MPPT) will force the PV system to operate at the maximum power condition. Here MPPT will generate a power angle with which the VSC output voltage leads the grid voltage. The nonlinear nature of VSI is removed by an Input-Output Feedbck Linearization Controller (IOFL). The IOFL controller development includes the complete linearization of the VSI and linearized system is controlled with a linear controller. So, in this paper, Power angle control technique is incorporated along with IOFL controller so that active power flow can guided from solar panel to grid. The proposed method is more meaningful when the synchronization of grid voltage with the controller is also a part of it. So a Phase Locked Loop is also discussed for connecting it in the controller side. This paper focused on a simple, convenient method of solar power control to grid with the inclusion of MPPT, IOFL, PLL and power angle control. The simulation results shows the effectiveness of the controller in power transfer capability of grid connected PV system.

The rapidly increasing energy demand is compelling the humankind for an alternative source of electrical energy generation and that leads to one thought, which is nothing but employing renewable energy generation. The incorporation of renewable energy generation into the existing grid system overlooks at some of the technical challenges and difficulties. The modern wind power plants use the methodology of Doubly Fed Induction Generator (DFIG) based Wind Turbine Generator (WTG). This framework focuses on the performance of a new control mechanism incorporated with grid fused DFIG based WTG. The fuzzy-based Rotor Side Converter (RSC) is developed to achieve maximum power delivery from DFIG using slip frequency control mechanism. To assist the slip frequency control, the PI-based Grid Side Converter (GSC) of DFIG is also proposed to maintain constant DC link voltage under grid voltage variations. The efficacy of the controller is validated using MATLAB/Simulink for the different operating conditions such as varying wind speed, grid voltage variations, etc. A unique feature of the controller is that it adapts to variations in wind velocities for achieving Maximum power output. The laboratory prototype model of RSC and GSC converter controller is developed and the hardware setup along with the results are examined.

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.

This paper presents the study and analysis of linear, adaptive and predictive controllers for pitch control of Vertical Take-off and Landing System (VTOL). Since VTOL aircraft system is a highly nonlinear system with varying aerodynamic parameters. Adaptive controllers are capable of achieving good performance in the presence of significant parametric uncertainties without the exact knowledge of the plant model. Fixed gain Linear Quadratic Regulator (LQR) controllers are optimal in nature and constrained optimization problems can be easily solved by Model Predictive Controller (MPC). This paper mainly focuses on the modeling of VTOL system and performance analysis of the system with linear, adaptive and predictive controllers.

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 magnetic null is of greatest significance for plasma formation in any Fusion Reactor device. In Ideal case, the radial and vertical component of the magnetic field produced by the Ohmic transformer coil should be approximately zero at some specific location inside the vacuum vessel. Non-zero radial & vertical component of the magnetic field within the plasma region acts as error field and causes difficulties in the gas breakdown. The error field effect can be compensated by placing the transformer coils in series with the solenoid coil. These coil positions must be estimated precisely for designed plasma current inception. This paper proposes a method to optimize the coil positions in order to obtain the null position at the described location inside the vacuum vessel. After optimal positioning of the coils, the magnetic field and plasma formation are analyzed using ANSYS, EFFI, and Poisson codes. The analysis is conducted at Plasma Research Lab. The results obtained with ANSYS simulation is validated with Analytical calculations.

The energy consumption in lighting is increasing day by day. Lot of efforts have been made in order to minimize the energy consumption in lighting. As a part of it, new energy efficient lights, improved lighting design and advanced lighting controls are evolved. Photovoltaic (PV) is the best solution for the energy requirements in the future. This paper proposes a method to maximize the utilization of available solar energy for the efficient street lighting design. This paper presents the design and implementation of a grid-solar hybrid power supply scheme for LED street lighting. The existing street lighting scheme in a part of the University is studied, simulated on DIALux, a lighting analysis software and the problems are analyzed in detail. In order to overcome the problems, a more efficient lighting scheme is proposed. A prototype scaled down model of the proposed lighting scheme is designed and implemented. This scheme utilizes the solar energy in a more efficient way. A control strategy is developed for switching the lamps between solar and grid supply. The control principles and illumination design of the hardware and software are presented.

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.

The power transmission network and its effective utilization are the recent topic of interest. Flexible AC Transmission Systems (FACTS) devices are equipped in the transmission lines for control of real and reactive power flow. The reactive power compensation can be done with STATic COMpensator (STATCOM). The appropriate amount of reactive power generated by the STATCOM will improve voltage stability in the buses. The Non Linear Controller namely Feedback Linearization Controller (FBLC) is used for controlling the Voltage Source Converter of STATCOM. The closed loop control of STATCOM with FBLC using MATLAB/SIMULINK is described in this paper. The results shows that with the proposed controller, DC link capacitor voltage and AC coupling voltage of STATCOM are attained its desired value. The load flow analysis with STATCOM in IEEE 5 bus system shows that losses in the network are reduced and thus transmission efficiency is improved.

Grid integrated wind energy conversion system is highly known among all renewable energy sources. Grid integrated wind farm undergoes many technical challenges. Wind farms need long transmission line for the grid integration. As long transmission line exhibits high inductive reactance, capacitive series compensation is required to improve the transmission capacity. Insertion of capacitive compensation in a line causes Sub Synchronous Resonance (SSR) Oscillations in the system. These oscillations may lead to a permanent damage in the turbine-shaft system. This paper proposes a novel fuzzy based adaptive controller for Rotor Side Converter (RSC) and Grid Side Converter (GSC) for damping SSR oscillations in a grid connected DFIG based wind farm. The paper describes the development of a mathematical model of the proposed system in detail and small signal stability for SSR oscillations is analyzed using Eigen value approach. Oscillation. Performance of the proposed controller is tested under varying operating conditions and it has been observed that the fuzzy based controller adopts the changes in the system operating conditions and gives satisfactory performance compared with conventional PI controller.

PWM converters are usually controlled using linear control techniques. As the linear control techniques have a disadvantage of requiring tuning from time-to-time, non-linear control techniques were employed for the control. One such non-linear control technique is feedback linearization control (FBLC). A control strategy for controlling the output voltage of three phase PWM converters through a linearization technique is discussed in this paper. Feedback linearization technique allows a few advantages like the decoupled control of the state variables, wide operating region. The performance analysis of the converter control using FBLC is done for varied conditions of load. The results from simulation of the controller and the analysis made on the thus linearised system shows the effectiveness of the Feedback linearization technique on different operating conditions.

As the penetration of wind energy to the grid is increasing drastically, the transmission line must be capable of handling large power which demands the series capacitor compensation for the lines. This can result in Sub-synchronous oscillations in the system. This paper explains the detailed mathematical modeling of a Squirrel Cage Induction Generator (SCIG) based wind farm, which is interconnected to the grid through a series, compensated transmission line. The detailed Sub-synchronous Resonance (SSR) analysis has been conducted under various operating conditions such as varying wind penetration levels, varying series compensation levels and varying grid impedance levels. Damping of different modes of SSR oscillations are analysed using the eigen value method. A Linear Quadratic Regulator has been designed for damping of these oscillations. The performance of the system with the proposed controller is analyzed for different operating conditions and the performance was satisfactory.

The interconnected systems are equipped with Flexible AC transmission Systems (FACTS) for better control on power transfer capability and stability improvement. The operation of these devices can be explained with different modeling techniques. Unified Power Flow Controller (UPFC) is one of the FACTS device with multivariable control capability. Different load flow models have been investigated to study the impact of UPFC in load flow solution. Power injection model and voltage source based model of UPFC are used for study the effect of UPFC in an interconnected system. So this paper focuses on the performance analysis and comparison of these UPFC models in a standard IEEE 5 bus system.

This paper presents a single stage grid connected three phase micro inverter for transfer of power from a solar array to grid controlled by a two level fuzzy logic controller. The system utilizes a line commutated inverter, thus the need for synchronization modules are eliminated. A fuzzy logic controller is designed and developed to track the maximum power from the PV panel and generate an appropriate control variable which is compatible for the switching of thyristorised converter. A two level logic is chosen for faster convergence with variable correction steps for the fuzzy logic controller. The maximum power point voltage window is identified from the PV array characteristics and the rule base for the two levels is developed. The system is tested for two array ratings of 5.8 kW and 8.7 kW to bring out the generic nature of the proposed fuzzy controller for power tracking. The micro inverter system is executed in MATLAB/Simulink for varying ambient conditions of the PV panel and the power balance is verified as proof of theory.

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 day by day increase in electricity demand and depletion of fossil fuels has made the world to think about the renewable energy sources such as solar, wind etc., This paper focuses on the configuration of large Doubly Fed Induction Generator (DFIG) based wind farm connected into the grid. Nowadays DFIGs are more focused in the wind energy conversion systems due to its own advantages. This paper explains the development of a mathematical model of DFIG driven by wind turbine. The turbine generator set is considered as a two mass model and development of the same is discussed. Mathematical modelling of wind turbine, two mass drive train and grid connected DFIG machines are developed by using the dynamic equations. Dynamics of DFIG Rotor Side Converter (RSC) and Grid Side Converter (GSC) are analyzed for further studies with control. The MATLAB simulation results for a 3730W wind farm is explained in this paper, and analyses of various unbalanced conditions on wind farm has been discussed such as rotor short circuit, grid voltage dip and sudden drop in wind speed. Similarly, different rated DFIG machines can be modeled using different machine specifications with the help of developed model.

Technological advancements has made production of electrical energy more efficient and minimized the consumption of non-renewable sources of energy. Wind energy has been harvested for more than a decade and has been considered to be one of the cleaner methods of producing electricity. This paper focuses on wind electric system connected to the grid. There are different types of wind electric generators such as fixed speed generators (synchronous generators) and variable speed generators which are squirrel cage and slip ring induction generators. Variable speed induction generators are widely chosen in wind electric system. In variable speed induction generators, doubly fed induction generators are mostly used because its rotor transfers the slip power when there is high wind speed velocity, and voltage is injected if the wind velocity is less. This paper proposes a method for controlling the stator power output of DFIG at speeds below synchronous speed using a novel fuzzy logic controller for Rotor Side Converter(RSC). The fuzzy logic rule base is formulated based on wind turbine speed and it controls the amount of rotor/slip power to be injected at appropriate slip frequency by varying the reference signal of the PWM generator, hence maintains the constant power flow from stator to grid. The fuzzy based RSC controller is designed and implemented in the laboratory.

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.

The paper presents a new design of adaptive and dynamic neural network-based controller architecture with feedback connection for non-linear multivariable systems. The network is trained online at each sampling interval using the desired output trajectory and the training method used is the Real Time Recurrent Learning Algorithm (RTRL). The recurrent network is a fully connected one, with feedback from output layer to the input layer through a delay element. Since the synaptic weights to the neurons are adjusted on-line, this controller has potential applications in real time control also. Moreover, it can be used for both continuous and discrete systems. The simulation results obtained by applying the algorithm to a non-linear multivariable system demonstrate the effectiveness of the proposed method.

Electrical energy generation from solar and wind is increasing day by day and the extraction of good quality electrical energy effectively as well as efficiently is really challenging. This paper focuses on the extraction of electrical energy from solar cells and interconnecting it to the single phase grid through a Quadratic Buck-Boost Converter (QBBC) and Multi Level Inverter (MLI). MLI uses three DC sources, one of which is derived from the solar array through QBBC with Maximum Power Point Tracking (MPPT) controller. In this paper, a new converter topology which accepts wide variations in input voltage has been designed to produce minimum distortion in MLI output with reduced number of switches. The proposed system is designed and implemented in the laboratory and the output is analyzed in different operating conditions

As compared to conventional inverter topologies like diode clamped and capacitor clamped inverters, the cascaded multilevel inverter has lesser harmonics as well as lower switching stress. The cascaded topology has more number of power switches leading to greater heat losses, larger size, higher cost and more gate drive circuitry. The proposed configuration contains less number of switches and produces lesser harmonics in the output voltage than the cascaded topology. A comparison between four different types of pulse width modulation (PWM) techniques, namely, In-phase disposition (IPD), Anti-phase disposition (APD), Carrier Overlap (CO) and Variable Frequency (VF) PWM methods, has been done. The results have been verified through simulation study in MATLAB/Simulink in order to select the best PWM method that provides minimum THD in the output voltage. An LC filter has been designed to improve the harmonic profile.

This paper presents a novel design of a co-ordinated controller for series connected FACTS devices like Thyristor Controlled Series Capacitor(TCSC) and Thyristor controlled Power Angle Regulator (TCPAR). The scheme can be used for non-linear system control, in which the exact linearized mathematical model of the system is not required, can be used to control many FACTS devices with a single controller. The basis of the proposed design is the Real Time Recurrent Learning (RTRL) algorithm in which the Neural Network (NN) is trained in real time. This requires two sets of neural networks. The first set is a fully connected Recurrent Neural Network (RNN) which acts as a neuro-identifier that provides the dynamic model of the system. The second set of neural network is the neuro-controller, used to generate the required control signals for the thyristors. Simulations results of the system using MATLAB/SIMULINK show that the performance of the system with the proposed controller is better than the conventional PI controllers and GA-based PI controllers.

The paper presents the design of a discrete Linear Quadratic Gaussian (DLQG) compensator for SSR damping which includes a full order Kalman filter to estimate all the states of the system and a full state feedback regulator. The controller is tested on IEEE First Benchmark model for SSR studies. A Discrete Linear-Time Invariant (LTI) model of a Thyristor-Controlled Series Capacitor (TCSC) in the synchronously rotating DQ reference frame is used in this system in which, the sample invariance is achieved by a simple transformation of the zero sequence variables in the discrete domain. This model of Discrete TCSC is then integrated with discretised LTI model of the rest of the system under study. Thyristor firing is based on current synchronised phase-locked loop and the sampling frequency is six times the synchronous frequency. The eigen value analysis is done for this integrated system for different angles of conduction of the thyristor. The modeled system is having 27 state variables including the PLL states. The TCSC model and DLQG compensator design is validated using time domain simulation of the system.

The paper presents artificial neural network (ANN) based adaptive controller for nonlinear systems. A state feedback adaptive control algorithm using fully connected recurrent neural network is employed. The desired trajectory for the on-line training of the neural network is obtained from a reference model. The synaptic weights adaptation of the network is based on real time recurrent learning algorithm (RTRL). Since the synaptic weights are adjusted in real time, this novel method of controller design has potential applications in non-linear systems. Simulation results of the controller applied to a simple non-linear dynamic system demonstrate the effectiveness of the controller.

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.

Electrical energy generation from renewable energy sources such as sun, wind etc., are widely adopted due to the increase in electricity consumption. The integration of renewable energy sources with the grid plays an important role in energy utilization. It is difficult to utilize electricity from renewable energy sources directly for the injection of power into the grid. Hence the system needs power electronic converters as an interface between renewable energy sources and grid/load. This paper discusses about the integration of three phase six level voltage source inverter into the grid. Three phase 2000 VA inverter is designed by using three , single phase eight switch six level inverters (in quarter cycle) and each single phase inverter uses three DC voltage sources which can be derived from renewable energy sources such as solar, wind and fuel cell. The pure sinusoidal 415 V three phase voltage is obtained from inverter to inject the power into grid and to the three phase resistive load. The proposed three phase Multi Level Inverter (MLI) is compared with the conventional three phase inverter and the observed THD of the conventional MLI is 31%. THD of the proposed MLI output voltage is analyzed which is 0.13% and found to be very less compared to six and 12 pulse conventional converter topologies. The simulation on the proposed inverter topology is done in MATLAB/Simulink and the results are verified.