<span lang="EN-IN">Unit commitment state’s the strategic choice to be prepared in order to define which of the accessible power plants should be taken into account to supply power. It permits utilities to reduce generation price of power. In this paper, the unit commitment problem is elucidated by taking N-1-1 contingency as a foremost constraint. The standard N-1-1 contingency takes the loss of sequential two components in the network having intervening interval for network modifications in the middle of two losses. The crucial objective to carry out contingency constrictions is to make certain that the operations of power system are adequately strong to unexpected losses of the components of the network. The optimal scheduling/allocation of the generating units is resolved by taking into account the N-1-1 criterion of contingency. By considering the N-1-1 criterion of contingency, the problem results to give an optimised model which is a linear model of mixed integer form. The linear program of mixed integer is a technique of an operational assessment in which restriction is imposed on few variables to be integers. Primarily benders decomposition was considered but for the improvement of results, the algorithm of branch and cut is presented. IEEE 30 bus system is taken into consideration and widespread analysis is accomplished to associate performance of the system under N-1-1 criterion contingency. The computational outcomes determine the value for taking into concern the intervening interval for the adjustments of the system with respect to the cost and robustness of the system. Later to the above model reliability assessment is proposed to calculate the Loss Of Load Expected (LOLE). This model is solved using MATLAB/MATPOWER software.</span>

This research article describes a novel optimization technique called simulink design optimization (SDO) to compute the optimal PID coefficients for an automatic voltage regulator (AVR). The time-domain performance of the proposed controller was analyzed using MATLAB/Simulation, and its performance was compared with that of water cycle algorithm, genetic algorithm, and local unimodal sampling algorithm-based PID controllers. The robustness of the proposed controller was verified by applying the disturbances to the generator field voltage and the amplifier parameter uncertainty. The studies presented in literature were discussed the AVR loop stability using the Bode plot which will not give the minimum stability margins. This study proposes a novel stability analysis called disk-based stability analysis to authenticate the stability of the AVR loop which is obtained by the classical analysis. This stability was compared with the proposed stability analysis. The MATLAB results reveal that the SDO-PID controller regulates the terminal voltage of the generator precisely, is more robust to parameter uncertainty, and is more stable than the other controllers. The maximum allowable parameter uncertainty of the amplifier model was identified as 102% of its nominal parameters. The stability margins are recognized as DGM = 10.40 dB and DPM = 56.50° for the AVR stability.

This paper presents a new multiobjective optimization method that can be used for generation rescheduling in power systems. Generation rescheduling in restructured power systems is performed by the system operator for different operations like congestion management, day-ahead scheduling, and preventive maintenance. The nonlinear nature of the equations involved and the constraints on decision variables pose a challenge to find the global optimum. In order to find the global optimum using a genetic algorithm, a bilevel optimization method is proposed. In the proposed multiobjective optimization method, the objectives are classified as primary and secondary based on their relative importance. The best solution is found using the secondary objective from the acceptable solutions of the Pareto-optimal front in the primary objective plane. As the financial feasibility and adherence to emission limits are of higher importance, the primary objectives considered are minimization of generation cost and emission. The secondary objective considered is reliability, to find the most reliable solution from the set satisfying the primary objectives. The proposed technique is validated on the IEEE 30-bus system and the results are presented.

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This article presents a study on the performance characteristics of a Francis turbine operating with various guide vane openings to determine the best operating point based on unit quantities. The guide vane openings were specified based on the width between the vanes at their exit, i.e., 10 mm, 13 mm, 16 mm, and 19 mm. The performance characteristic curves of the Francis turbine—head versus speed, torque versus speed, discharge versus speed, and efficiency versus speed—were obtained at various input power and guide vane openings. From these data, unit curves were plotted and the corresponding best efficiency points were obtained. The highest efficiency of 50.25% was obtained at a guide vane opening of 19 mm. The values of head, discharge, speed, and output power at BEP were 7.84 m, 13.55 lps, 1250 rpm, and 524 W, respectively.

This paper presents the design and implementation of Inverter system for driving three phase Induction motor using DSPACE DS1104 controller with the controlling objective space vector pulse width modulation (SVPWM) technique. AC motor drives are commonly used over DC motor drives because of their more advantages. Induction motor is the most commonly used AC motor drive for various industrial and domestic applications. The project will be commenced by a basic understanding of SVPWM inverter, components used in the design and study the mathematical equations of the Induction motor. The performance of SVPWM based Induction motor (IM) in open loop is presented with simulation. Here the hardware implementation of the three phase inverter which is fed to a three phase induction motor driven by DSPACE CP1104 is been implemented.

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