Hari Om Gupta

ANN-based estimator for distillation using Levenberg-Marquardt approach

In modern chemical industries the purity of the distillate is the main objective and time to estimate the distillate composition is also the constraint. In the present paper, the Levenberg-Marquardt (LM) approach is proposed for predictive inferential control of distillation process. The developed estimator using LM approach predicts the composition of distillate using column pressure, reboiler duty, and reflux flow along with the temperature profile of the distillation column as inputs. In complex chemical industries where the output depends on many parameters, Steepest Descent Back Propagation (SDBP) algorithm does not work properly for estimating the composition of distillate, which results in saturated outputs and differs from the desired results. To overcome such type of situation, LM approach is used in developed estimator. The estimated results are compared with the simulation results and it is observed that the results obtained from LM approach are significantly improved than the results obtained from SDBP algorithm. To enhance the accuracy of the estimated results, the pressure, reflux flow and heat input with temperature profile of the column are used as input to train the neural network.

A control algorithm for compensation of customer-generated harmonics and reactive power

This paper presents a new control algorithm for a shunt active power filter to compensate harmonics and reactive power required by nonlinear loads. If the utility voltage is distorted, active power filter (APF) allows similar level of distortion in the compensated source current. Therefore, the resultant source currents have the same waveform as that of the supply voltage, thereby attributing the responsibility of utility and customer at the point of common coupling (PCC). Due to similar shape of the source voltage and currents, reactive power is compensated completely. The proposed scheme provides an additional feature of compensation of either only harmonics, or both harmonics and reactive power simultaneously, based on the desired capacity of the APF. Various simulation results are presented with ideal and distorted mains voltage and compared with other algorithms. Proposed algorithm is implemented as a prototype to verify the simulation results.

Optimal control of nonlinear inverted pendulum dynamical system with disturbance input using PID controller & LQR

Optimal response of the controlled dynamical systems is desired hence for that is the optimal control. Linear quadratic regulator (LQR), an optimal control method, and PID control which are generally used for control of the linear dynamical systems have been used in this paper to control the nonlinear dynamical system. The inverted pendulum, a highly nonlinear unstable system is used as a benchmark for implementing the control methods. In this paper the modeling and control design of nonlinear inverted pendulum-cart dynamic system with disturbance input using PID control & LQR have been presented. The nonlinear system states are fed to LQR which is designed using linear state-space model. Here PID & LQR control methods have been implemented to control the cart position and stabilize the inverted pendulum in vertically upright position. The MATLAB-SIMULINK models have been developed for simulation of the control schemes. The simulation results justify the comparative advantages of LQR control methods.

Study of composition dependent structural, optical, and magnetic properties of Cu-doped Zn1−xCdxS nanoparticles

Cu-doped Zn1-xCdxS nanoparticles were synthesized by coprecipitation technique in ice bath at 280 K. The band gap energy of Zn1-xCdxS:Cu nanoparticles can be tuned to a lower energy by increasing t ...

Utility Oriented Demand Side Management Using Smart AC and Micro DC Grid Cooperative

DC microgrid provides a viable and more efficient option to cater for DC loads in the building space and, in particular, data centers. This paper investigates the opportunities associated for utilities to optimize industrial demand response for smart AC and DC microgrid environment thus facilitating distribution utility to reduce peak energy on the existing AC distribution system. A load shifting demand side management (DSM) technique is used to shift AC industrial loads in response to time of day (TOD) tariff. Hence, an attempt has been made to study the impact of DSM strategies with optimal shifting of AC devices in the presence of DC microgrid. Simulations are carried out on a practical distribution system having large industrial loads but it has been assumed that the AC distribution system has DC microgrid with renewables and battery storage systems (BSSs). DSM results for AC distribution grid are compared and analyzed with differing DC microgrid set ups, for example with and without battery storage. It has been observed that the DSM strategy with DC microgrid in the presence of solar renewables and battery storage can substantially reduce average energy cost for demand to response and peak load burden on AC distribution utilities.

Modelling and Simulation for Optimal Control of Nonlinear Inverted Pendulum Dynamical System Using PID Controller and LQR

This paper presents the modelling and simulation for optimal control design of nonlinear inverted pendulum-cart dynamic system using Proportional-Integral-Derivative (PID) controller and Linear Quadratic Regulator (LQR). LQR, an optimal control technique, and PID control method, both of which are generally used for control of the linear dynamical systems have been used in this paper to control the nonlinear dynamical system. The nonlinear system states are fed to LQR which is designed using linear state-space model. Inverted pendulum, a highly nonlinear unstable system is used as a benchmark for implementing the control methods. Here the control objective is to control the system such that the cart reaches at a desired position and the inverted pendulum stabilizes in upright position. The MATLAB-SIMULINK models have been developed for simulation of control schemes. The simulation results justify the comparative advantages of LQR control methods.

Influence of Cobalt Doping on the Physical Properties of Zn0.9Cd0.1S Nanoparticles

Zn0.9Cd0.1S nanoparticles doped with 0.005–0.24 M cobalt have been prepared by co-precipitation technique in ice bath at 280 K. For the cobalt concentration >0.18 M, XRD pattern shows unidentified phases along with Zn0.9Cd0.1S sphalerite phase. For low cobalt concentration (≤0.05 M) particle size, dXRDis ~3.5 nm, while for high cobalt concentration (>0.05 M) particle size decreases abruptly (~2 nm) as detected by XRD. However, TEM analysis shows the similar particle size (~3.5 nm) irrespective of the cobalt concentration. Local strain in the alloyed nanoparticles with cobalt concentration of 0.18 M increases ~46% in comparison to that of 0.05 M. Direct to indirect energy band-gap transition is obtained when cobalt concentration goes beyond 0.05 M. A red shift in energy band gap is also observed for both the cases. Nanoparticles with low cobalt concentrations were found to have paramagnetic nature with no antiferromagnetic coupling. A negative Curie–Weiss temperature of −75 K with antiferromagnetic coupling was obtained for the high cobalt concentration.

Evolutionary programming based algorithm for selection of wheeling options

This paper describes how to select a particular wheeling option among the various feasible transaction options available under the deregulated environment of modern power systems. An efficient hybrid optimal power flow (HOPF) algorithm has been proposed to determine the optimal selection based on wheeling cost. In this proposed HOPF, the Newton-Raphson method and evolutionary programming (EP) algorithm have been used for power flow and economic dispatch respectively. Based on the power transfer capability and minimum generation cost, an optimal wheeling option will be suggested to both the owners of private nonutility generator (i.e. independent power producers or co-generators) and the utility. The proposed algorithm is independent of the cost characteristics of nonutility generators (NUGs). The proposed model has been tested on the IEEE-30 bus test system with synthetic imposition of wheeling transactions. The solutions obtained are quite encouraging and useful in the present deregulated environment.

Artificial neural network based automatic generation control scheme for deregulated electricity market

This paper presents an artificial neural network (ANN) based frequency controller design for multi-area Automatic Generation Control (AGC) scheme in a deregulated electricity market. The effect of Superconducting Magnetic Energy Storage (SMES) unit has also been considered to develop the model. SMES units have been used to the power systems to inject or absorb active power. The effect of generator rate constraint (GRC) has also been considered in developing the multi area AGC model. A three layer feed forward neural network (NN) is proposed for controller design and trained with Back propagation algorithm (BPA). The poolco based transaction can be implemented by optimizing the bids (price & capacity) submitted by the generating companies (Gencos) and distribution companies (Discos). The functioning of the proposed ANN based controller has been demonstrated on a four-area System, and the results have been compared with those obtained by using a Genetic Algorithm based control scheme.

Advance Compensated Mho Relay Algorithm for a Transmission System with Shunt Flexible AC Transmission System Device

Abstract—The presence of shunt flexible AC transmission system devices adversely affect the performance of distance relay and create security and reliability issues. This article introduces a noble compensated Mho relay algorithm for the protection of transmission line employing shunt flexible AC transmission system devices, such as a static VAR compensator and static synchronous compensator. A detailed model of transmission system employing a shunt flexible AC transmission system device is explained. Then compensated impedance inserted by a shunt device in the transmission line is calculated, and finally, a compensated Mho relay algorithm is proposed to protect zone one of the transmission line. Simulation work is carried out in PSCAD/EMTP software. Results show that the proposed relay is secure, accurate, and reliable under the wide variation in power system parameters, such as load angle, fault resistance, fault location, and compensation level.