Power Research

Arunesh Kumar Singh ¹, Talish Naseem ², Vikas Pratap Singh ³

Affiliations
1 Assistant Professor, Department of Electrical Engineering, Jamia Millia Islamia, Jamia Nagar, New Delhi, 110025, IN
2 PG Scholar, Department of Electrical Engineering, Jamia Millia Islamia, Jamia Nagar, New Delhi, 110025, IN
3 Senior Research Fellow, Central Power Research Institute Bangalore, IN

Abstract

Now a days, power quality issues are very important for the sensitive equipments to increase the efficiency of the syatem. In the power system, disturbances are due to non linear characteristics and fast switching of the power electronics apparatus. Because of the use of the power electronic devices many distortions are introduced. Due to these harmonics the devies connected to the system suffer and their life is reduced. Our main aim is to use a shunt active filter that improves these harmonics and gives a sinusoidal current at the load side. For improving power quality fuzzy controllers are used and found to be better than traditional controllers.

Keywords

Fuzzy, controller, PWM, filter, control rules, fuzzy inference system, mamdani-type

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Vikas Pratap Singh ¹, Pratap Srivastava ²

Affiliations
1 Ph.D. Scholar, Indian Institute of Technology Jodhpur, Rajasthan, IN
2 Dayalbagh Educational Institute, Dayalbagh Agra, IN

Abstract

In 21st century forecasting of solar power generation is an important issue due to grid integration. So solar power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. In this work, Solar power generation forecasting is carried out based on the data collected from a 5MW Gujarat Power Cooperation limited solar photovoltaic power plant which is installed in Charanka, Gujarat. In this paper we discussed about the single exponential smoothing for solar power forecasting problem.

Keywords

Solar power, forecasting, exponential smoothing.

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D. K. Chaturvedi ¹, Mayank Pratap Singh ¹, Md. Sharif Iqbal ¹, Vikas Pratap Singh ²

Affiliations
1 Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P, IN
2 Central Power Research Institute, Bangalore,, IN

Abstract

The induction motor is commonly used in industries due to its rugged construction and almost no maintenance. To precisely control the induction motor, accurate estimation of parameters is required. Artificial Neural Network (ANN) is used in the past for parameter estimation. The conventional ANN has its own problems such as learning issues, unknown size of ANN and its connections, etc. To overcome some of its problems generalized neural network is used in this paper. The GNN is trained to estimate parameters of three phase induction motor. Experimental setup is developed in DEI, which is consisting of a 415 V, 3Φ squirrel cage induction motor, data acquisition system and on-line parameter estimator.

Keywords

Parameter estimation, three phase induction motor, ann , generalized neuron

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D. K. Chaturvedi ¹, Md. Sharif Iqbal ¹, Mayank Pratap Singh ¹, Vikas Pratap Singh ²

Affiliations
1 Dept. of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
2 Central Power Research Institute, Bangalore, IN

Abstract

Induction motors are popularly used as an electric drives are the critical component in industrial systems. Most of the faults in induction motor are because of excessive heat generated in the machine. In the industrial application a large rating of induction motors are used which produce a significant heat. The heat is produced in the motor due to the different losses accumulated in the machine. Hence a healthy cooling system is always required to dissipate the heat and maintain the motor temperature within acceptable limits. This paper deals with the problem occurred specially in the cooling system under different operating conditions and investigate them. The on-line information is gathered from the machine about temperature, current and vibration signatures at different operating condition and the health of the cooling system is analyzed. Soft computing techniques are utilized for this purpose.

Keywords

Induction motor, cooling system, temperature, current signature, vibration, soft computing.

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D. K. Chaturvedi ¹, Mayank Pratap Singh ², Md. Sharif Iqbal ², Vikas Pratap Singh ³

Affiliations
1 Professor at Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
2 Research Scholar at Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
3 Senior Research Fellow at Central Power Research Institute, Bangalore, IN

Abstract

The parameters of induction motor depends on various factors such as: machine internal state, machine ageing, magnetic saturation, operating conditions, the coupling effect between the internal system and external system. The paper deals with an overview of parameter estimation of three phase induction motor using different soft computing techniques. The soft computing techniques which are considered in the paper are fuzzy system, artificial neural network (ANN), Neuro-Fuzzy, genetic algorithms (GA) and particle swarm optimization (PSO). It is observed that the estimated parameter using soft computing techniques were much closer to actual value.

Keywords

Induction motor, parameter estimation, soft computing techniques, ANN, Neuro-Fuzzy, GA, PSO

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Neeraj Tiwari ¹, Sanjeev Kumar ², Vikas Pratap Singh ³

Affiliations
1 NeerajTiwari, Associate Professor, National Institute of Engineering and Management, Mathura, IN
2 Professor, Hindustan College of Science and Technology Mathura, IN
3 SRF, Central Power Research Institute, ERED Bangalore, IN

Abstract

This paper describes an approach to the design and implementation of sun tracker stand in PV system making 120 Volt string. For the strength analysis against wind pressure the PV system with tracker stand has been implemented in solid work software version SP-13. Another part of this paper is the comparison of power drawn from The PV system with tracker and without a tracker. The data received in real experimental setup. We analyzed that the efficiency of PV systems can be increased by 42 % compared to the static PV system by implementing the tracker techniques in the PV System.

Keywords

photo voltaic system, dual axis sun tracker system, control circuit, solid work.

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D. K. Chaturvedi ¹, Rahul Umrao ², Vikas Pratap Singh ³

Affiliations
1 Professor, Department of Electrical Engineering, DEI Deemed University, Agra, IN
2 Allen Institute of Technology Kanpur, IN
3 Senior Research Fellow, ERED, CPRI, Bangalore, IN

Abstract

Fuzzy logic controller is based on human experience. Human experience is encoded in the form of fuzzy rule base to control the system. It is difficult to decide the size of fuzzy rule base. As the number of rules increases the performance of controller is better. At the same time its complexity increases which in turn affects the computation time and memory requirements. To overcome these problems, a Polar Fuzzy logic controller (PFC) is proposed for the load frequency control problem of nonlinear three area interconnected power system. In this paper, The PFC is made adaptive using Real Coded Genetic algorithm- fuzzy system (RCGAF) approach. The performance of simple PFC and adaptive PFC using RCGAF is compared with fuzzy and conventional PI controller.

Keywords

Load frequency control, adaptive polar fuzzy logic, real coded genetic algorithm, power systems.

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D. K. Chaturvedi ¹, Md. Sharif Iqbal ², Mayank Pratap Singh ², Vikas Pratap Singh ³

Affiliations
1 Professor, Department of Electrical Engineering, DEI Deemed University, Agra, IN
2 PhD Research Scholar, Department of Electrical Engineering, DEI Deemed University, Agra, IN
3 Senior Research Fellow, ERED, CPRI, Bangalore, IN

Abstract

Induction motor is singly excited and brushless,very simple, compact and extremely rugged in construction and most reliable and low cost motor. Although, these motors are reliable but often exposed to hostile environments during its operation which leads to early deterioration leading to the motors failure. Faults and failures of induction machines can lead to excessive downtimes and generate large losses in terms of maintenance and revenues. This paper deals with the study of identification of different type of faults and the health monitoring techniques commonly used in induction motors.

Keywords

Faults, health monitoring, fault diagnostic technique, induction motor.

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D. K. Chaturvedi ¹, Manmohan ², Rahul Umrao ³, Vikas Pratap Singh ⁴

Affiliations
1 Dept. of Electrical Engineering Faculty of Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
2 Department of Electrical Engineering Faculty of Engineering Dayalbagh Educational Institute (Deemed University) Dayalbagh, AGRA - 282005 (UP), IN
3 Dept. of Electrical Engineering Allen house Institute of Technology, Kulgaon Road, Rooma, Chakeri Ward, Kanpur, Uttar Pradesh - 208008, IN
4 IIT Jodhpur and Energy Efficiency and Renewable Energy Division, Central Power Research Institute, Bangalore - 560080, IN

Abstract

The Fuzzy Logic Controller has proven its worthiness for nonlinear complex systems. Multi-area power system is quite complex and nonlinear in nature. In this paper, Fuzzy logic controller (FLC) is developed for three area nonlinear power system. But there are inherent drawbacks of FLC such as its performance depends on number of rules, long computation time, large memory requirement etc. To overcome these problems, a polar fuzzy controller (PFC) is proposed to control the load frequency deviations in multi area power system. The PFC works on the basis that an angle acts as an input and controller response as an output. In conventional PI controller and FLC, two gains are to be tuned;whereas the PFC needs only one gain to be tuned, because the angle of PFC is calculated from the ratio of frequency deviation and the integral of frequency deviation. Hence, only one gain is sufficient to tune it. In PFC, only two rules are sufficient in the rule base. The work is extended to test the performance of proposed PFC in real time environment with the help of OPAL-RT simulator (OP 5142 v 10.2.4).

Keywords

Load frequency control, Polar fuzzy Controller, Real time simulation, AGC.

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Neha Adhikari ¹, Vikas Pratap Singh ²

Affiliations
1 Engineering Officer Grade-3, Energy Efficiency and Renewable Energy Division, CPRI, Bangalore-560080, IN
2 Energy Efficiency and Renewable Energy Division, Central Power Research Institute, Bangalore-560080, IN

Abstract

This paper presents the studies on the solar photovoltaic system in the partial shading conditions. The standalone solar photovoltaic system for residential application of 2 kW power rating is considered in the system analysis. The proposed system is using a set of batteries for energy storage with a flyback dc-dc converter and a single phase voltage source inverter is designed with the controller to regulate the power quality at the consumer end. The studies are carried out as case studies on the different conditions of the shading and results are presented to analyze the PV output power and evaluate the overall system performance. Based on the results obtained few measures are suggested to keep the check on the performance in such conditions.

Keywords

Solar photovoltaic, MPPT controller, Inverter, Partial shading, Standalone energy system

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Vikas Pratap Singh ¹, Vivek Vijay ¹, D. K. Chaturvedi ², Neha Adhikari ³

Affiliations
1 Indian Institute of Technology Jodhpur, IN
2 Department of Electrical Engineering Faculty of Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
3 ERED, Central Power Research Institute, Bangalore - 560080, IN

Abstract

The various forms of solar energy - solar heat, solar photovoltaic, solar thermal electricity, and solar fuels offer a clean, climate-friendly, very abundant and in-exhaustive energy resource to mankind. Solar power is the conversion of sun light into electricity, directly using photovoltaic (PV). The forecasting of energy Demands have become concerns for facility managers, and predicting energy generation plays a critical role in power-system management, scheduling, and dispatch operations. A reliable energy supply forecast helps to prevent unexpected loads and provides vital information for decisions made on energy generation and purchase. However, study of energy generation prediction by the photovoltaic (PV) system has been limited over the years, especially concerning short-term predictions. This study will helps in providing the details on different type of models and techniques of solar power forecasting.

Keywords

Solar forecasting; Forecasting models; Forecasting techniques.

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D. K. Chaturvedi ¹, A. P. Sinha ², Vikas Pratap Singh ³

Affiliations
1 Professor, Dept. of Electrical EngineeringFaculty of Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
2 Faculty, Dept. of Electrical Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
3 Energy Efficiency and Renewable Energy Division, Central Power Research Institute, Bangalore-560080, IN

Abstract

Soft computing techniques are extensively used for electrical load forecasting in the past such as ANN, Fuzzy Systems, GA etc.. ANN has some limitations, such unknown structure of ANN, Decision of neuron type, problem of training data and time, stuck in local minima etc. To overcome the drawbacks of ANN, a Generalized Neural Network (GNN) has been proposed. In this paper, different variants of GNN have been proposed to improve its performance such as GNN integrated with wavelet transform and trained with adaptive genetic algorithm and fuzzy system to forecast the short term week day electrical load. Performance of the proposed algorithm is compared with other GNN and its other variants on the basis of prediction error.

Keywords

Load Forecasting, ANN, Generalized neural network, Wavelet, Adaptive Genetic algorithms, Fuzzy systems.

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