Informatics Publishing Limited

Vishal Kumar Sinha ¹, Waseem Akhtar ¹, Vidyamani Kumar ¹, Vikas Pratap Singh ¹, Vivek Kumar ¹, K. Mannivannan ¹

Affiliations
1 Dr. M.G.R Educational and Research Institute (University), Chennai, IN

Abstract

We know that the energy demands are increasing day by day. And we are also aware of the fact that conventional sources would not be sufficient to meet the increasing energy demands and would get exhausted in upcoming years. Thus, now we are focusing on two strategies, i.e., firstly we aim at conservation of energy and secondly, we are focusing more on renewable sources of energy. Our project is based on this fact only, i.e., use of renewable sources of energy. The main features of our project are PV generator, wind generator, fuel cell and a backup unit. We know that the power produced by PV and wind generator are not enough and hence the output of PV and wind generator are boosted using boost converter. Moreover, we are using an MPPT so that maximum power can be obtained from PV cell. Fuel cell is another important part of our proposed system. The main reason behind using the fuel cell is that the weather may not be favorable all the time. In such conditions, fuel cell would be adequate to supply the load as the main concept of fuel cell is that it stores the chemical energy and converts this chemical into electrical energy.

Keywords

PV System, Wind System, Fuel Cell, Lead Acid Accumulator.

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Chaturvedi D K ¹, Isha Yadav ¹, Vikas Pratap Singh ²

Affiliations
1 Department of Electrical Engineering, Dayalbagh Educational Institute, Deemed University Dayalbagh, Agra - 282005, IN
2 Senior Research Fellow, Energy Efficiency and Renewable Energy Division, Central Power Research Institute, Bangalore-560080, IN

Abstract

The increasing demand for energy is one of the biggest reasons behind the integration of solar energy into the electric grids or networks to ensure the efficient use of energy PV systems it becomes important to forecast information reliably. The accurate prediction of solar irradiance variation can enhance the quality of service This integration of solar energy and accurate prediction can help in better planning and distribution of energy Here in this paper, a deep review of methods which are used for solar irradiance forecasting is presented These methods help in selecting the appropriate forecast technique according to the needs or requirements. This paper also presents the metrics that are used for evaluating the performance of a forecast model.

Keywords

Solar forecasting, physical method, statistical method, hybrid method, evaluation metrics

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

Affiliations
1 Dayalbagh Educational Institute (Deemed University), Agra, IN
2 Hindustan College of Science and Technology, Mathura, IN
3 Central Power Research Institute Bangalore, IN

Abstract

This paper presents the performance study of single axis tracking system compared static PV system. To increase the efficiency of PV System. We designed a simple and cost effective 170W sun tracking system for the experiment. The whole experimental setup has been implemented in Simulink^TM platform for the analysis of improved efficiency. The objective of this paper to optimize the solar energy receivers. In this paper, a Simulink model of the static PV system and Tracking PV system has been presented. In the fabrication of real sun tracker system we used a 24 VDC motor and a simple LDR based control circuit for the tracking purpose. The block diagram with detailed description and performance of the tracking system are presented.

Keywords

Dc-motor Model, Simulink Based Static Pv System, Solar Tracking System, Photovoltaic

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Chaturvedi D. K. ¹, Devendra Singh ², Vikas Pratap Singh ³

Affiliations
1 Department of Electrical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, Agra-282110, IN
2 M.Tech. Student in the Department of Electrical Engineering, Faculty of Engineering, Dayalbagh Educational Institute, Agra-282100, IN
3 Vikas Pratap singh, Energy Efficiency and Renewable Energy Division, Central Power Research Institute, Bangalore and IIT Jodhpur, IN

Abstract

A variety of fan faults occur in our day to day life such as electrical faults(winding faults), mechanical faults (broken rotor bars, eccentricity, bearing faults) etc. To detect the fault, many motor variables may be taken such as current, voltage, speed, sound, temperature and vibrations, so that the preventive action may be taken before the occurrence of faults in the fan. Current signature is useful for finding electrical faults such as stator faults etc. and acoustic signature is useful for finding mechanical faults such as rotor faults etc. In this paper, the on line current, voltage, rpm and temperature reading of faulty fan and healthy fan are recorded. These recorded signals are used to train a neural network so that it is able to detect the fault.

Keywords

Wavelet, ANN, Ceiling Fan, Fault detection

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Vikas Pratap Singh ¹, Kumar Vaibhav ²

Affiliations
1 Senior Research Fellow, ERED, Central Power Research Institute, Bangalore-560080, IN
2 Assistant Professor, Amity University, Jaipur Rajasthan, IN

Abstract

In 21^st century Renewable energy sources, especially Solar Energy, are to play a larger role in Hybrid Generation. There exist a number of technological, environmental and political challenges linked to supplementing existing electricity generation capacities with solar energy. Solar power forecasting can avoid many of the balancing issues, if accurate forecasts of solar output are available. Anybody trading in solar energy can negotiate a better price, if they have precise information about the volume they have to sell at any particular time.

Keywords

Solar Power Forecasting, Pv Power

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Vikas Pratap Singh ¹, Vivek Vijay ¹, S. H. Gaurishankar ¹, D. K. Chaturvedi ², N. Rajkumar ³

Affiliations
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN

Abstract

In 21st century solar power variability is an important issue due to grid integration. In these days grid integration is very popular because of heavy load. So solar power, wind power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. The main objective of this paper is to analyse solar power variability due to seasonal variation in Jodhpur. Jodhpur is known as sun-city for an average 320 sunny days in a year. Average solar insolation available in Jodhpur city is 5.7-6.0 kWh/m² per day. This is second highest insolation in the world. In this paper, the Solar power variability analysis is carried out based on the data collected from a typical 43 kW amorphous silicon solar photovoltaic system installed in Jodhpur. Mansoon, winter and summer seasons are used for analysis of variation in Photovoltaic Generation due to change of solar insolation. Output of solar photovoltaic system depends on solar insolation and in this paper we have analysed the variation in solar power according to rainy, winter and summer seasons and used artificial neural network to predict the power output from PV system. The paper showed that proposed ANN model is more accurate and study of variability in solar power can help in plant operation, power scheduling and dispatchability.

Keywords

No Keywords

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Vikas Pratap Singh ¹, Vivek Vijay ¹, S. H. Gaurishankar ¹, D. K. Chaturvedi ², N. Rajkumar ³

Affiliations
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN

Abstract

In 21st century solar power variability is an important issue due to grid integration. In these days grid integration is very popular because of heavy load. So solar power, wind power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. The main objective of this paper is to analyse solar power variability due to seasonal variation in Jodhpur. Jodhpur is known as sun-city for an average 320 sunny days in a year. Average solar insolation available in Jodhpur city is 5.7-6.0 kWh/m² per day. This is second highest insolation in the world. In this paper, the Solar power variability analysis is carried out based on the data collected from a typical 43 kW amorphous silicon solar photovoltaic system installed in Jodhpur. Mansoon, winter and summer seasons are used for analysis of variation in Photovoltaic Generation due to change of solar insolation. Output of solar photovoltaic system depends on solar insolation and in this paper we have analysed the variation in solar power according to rainy, winter and summer seasons and used artificial neural network to predict the power output from PV system. The paper showed that proposed ANN model is more accurate and study of variability in solar power can help in plant operation, power scheduling and dispatchability.

Keywords

No Keywords

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Vikas Pratap Singh ¹, Vivek Vijay ¹, B. Ravindra ¹, D. K. Chaturvedi ², Rajashekhar P. Mandi ³

Affiliations
1 Indian Institute of Technology Jodhpur, Old Residency Road, Jodhpur - 342 011, Rajathan, IN
2 Dayalbagh Educational Institute, Dayalbagh, Agra – 282005, Uttar Predesh, IN
3 Central Power Research Institute, Bangalore - 560 080, IN

Abstract

The main objective of this paper is to review the state of the art of IIT Jodhpur Rooftop installed 110 kW PV systems. This is done analyzing the operational data of 110 kW PV systems (43.30 kW located in Block 1 and 58.08 kW in Block 2). Performance analysis depends on three basic term of solar PV. How much energy do they produce? What level of performance is associated to their production? Which are the key parameters that most influence their quality? During the year 2011, the PV systems in Jodhpur, India have produced a mean annual energy of 1290.64 kWh/kWp in block-1 and 1290.64 kWh/kWp in Block-2. As a whole, the location of Solar PV system is the main reason of energy variability and system output. The overall mean Performance Ratio is 75% in both Blocks. Solar power variability depends on the two variables, deterministic and stochastic variable. In last few years researcher work on finding deterministic variable such as system losses (module efficiency, DC cable losses, inverter losses and AC cable losses) but these deterministic variables are not enough to give accurate forecasting so with the help of combined effect of these both variable give accurate plant performance and reliable solar power forecasting for solar power scheduling and dispatchability.

Keywords

PV System description, Roof of academic blocks, Performance analysis of solar PV, Performance ratio, Deterministic variables and Stochastic variables

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