i-manager Publications

i-manager's Journal on Power Systems Engineering (JPS)

Current Issue Vol. 11 Issue 3

Voltage Stability and Power Loss Minimization with STATCOM using Particle Swarm Optimization and Hybrid Firefly Particle Swarm Optimization Algorithms
Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage
Performance Analysis of Distribution System under Different Loading Conditions using Test Bench
Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate
Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors

Most Cited

Volume 4 Issue 3 August - October 2016

Research Paper

Digital Simulation of Eight Bus System with DPFC by Employing Five Level Inverter

Akhib Khan Bahamani* , Sreerama Reddy G.M, V. Ganesh*

* Research Scholar, JNTUA University, Anantapur, Andhra Pradesh, India.

Professor and Head, Department of Electronics and Communication Engineering, C.B.I.T, Kolar, Karnataka, India.

* Professor, Department of Electrical and Electronics Engineering, JNTUA, JNTUA College of Engineering, Pulivendula, Andhra Pradesh, India.

Bahamani, A. K., Reddy, G. S., and Ganesh, V. (2016). Digital Simulation of Eight Bus System with DPFC by Employing Five Level InverterPaper. i-manager’s Journal on Power Systems Engineering, 4(3), 1-11. https://doi.org/10.26634/jps.4.3.8267

Abstract

In recent times, Distributed Power Flow Controller is an important device within the family of FACTS Devices. This paper investigates Multi Level Inverter (MLI) based Distributed Power Flow Controller (DPFC) system for voltage sag mitigation and harmonic reduction. The DPFC employs a Shunt based Static Compensator (STATCOM) and multiple series converters to improve the power quality. DPFC was placed at the correct location in the power transmission system to gain advantages like improved voltage profile and reduced power loss. Circuit models are developed for Eight bus system with and without DPFC. The MATLAB/SIMULINK results obtained shows an improved performance in voltage sag mitigation, voltage quality of load busses, power quality improvement, comparison of the bus voltages with and without DPFC and reduction in load voltage harmonics. The results indicate that MLI based DPFC has improved in power quality and reduction in total harmonic reduction.

References

[1]. Y.H Song, and A. John, (1999). “Flexible AC Transmission System (FACTS)”. IEEE Power and Energy Series, Vol.30, london, UK: Institutional of Electric Engineers.

[2]. N.G. Hingorani, and L. Gyugyi, (2000). Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems. New York: IEEE Press.

[3]. L. Gyugvi, CD Schauder, S.L. Williams, T.R Rietman, D.R. Torgerson, and A. Edris, (1995). “The unified power flow controller: A new approach to power transmission control”. IEEE Trans Power Del. Vol.10, No.2, pp.1085- 1097.

[4]. A.A. Edris, (1995). “Proposed terms and defination for Flexible AC Transmission System (FACTS)”. IEEE Trans Power Del. Vol.12, No.4, pp.1848-1843.

[5]. K.K. Sen, (1997). “SSSC- Static Synchronous Series Compensator - Theory modeling and application”. IEEE Trans Power Del., Vol. 13, No. 1, pp. 241-246.

[6]. M.D. Deepak, and E.B. Williams, (2007). “A Distributed Static Series Compensater system for realizing active power flow control on existing power lines”. IEEE Trans Power Del., Vol. 22, No. 2, pp. 642-649.

[7]. Y. Zhihui, and B. Ferreira, (2009). “DPFC control during shunt converter failure”. In Proc. IEEE Energy Converters. Congr. Expo. (ECCE), pp. 2727-2732.

[8]. Y. Zhihui, and B. Ferreira, (2009). “Utilizing distributed power flow controller for power oscillation damping”. In Proc. IEEE Power Energy Soc. Gen. Meet (PES), pp.1-5.

[9]. Y. Sozer, and D.A. Torrey, (2009). “Modeling and control of utility interactive converters”. IEEE Power Trans, Power Electron, Vol.24, No.11, pp.2475-2483.

[10]. Zhiyui Yuan, and Haan, (2010). “Principle and analysis of the DPFC”. IEEE Transaction on Power Electronics, Vol.25, No.10.

[11]. Behrouz Soulat, Ali Ajami, and Amin Safari, (2013). “A Novel Modelling and controlling of Distributed Power Flow Controller (dpFC) based on PSO Algorithm”. ECTI Transaction on Electrical Engineering, Vol.11, No.1.

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Research Paper

Decision Tree Technique of High Impedance Fault detection in Distribution Feeder

N. Rajasekhar Varma* , Sanker Ram**

* Associate Professor & HOD, Department of Electrical and Electronics Engineering, RSS College of Engineering and Technology, Anantapur, Andhra Pradesh, India.

** Professor, Department of Electrical and Electronics Engineering, Jawaharlal Nehru Technological University, College of Engineering, Hyderabad, Telangana, India.

Varma, N. R., and Ram, B. S. (2016). Decision Tree Technique of High Impedance Fault detection in Distribution Feeder. i-manager’s Journal on Power Systems Engineering, 4(3), 12-27. https://doi.org/10.26634/jps.4.3.8268

Abstract

Distribution lines subjected to vagaries of nature are prone to metal fatigue, which results in snapping of live conductors. These broken conductors, upon contact with earthed objects or, among themselves, cause High Impedance Faults (HIF) which are difficult to be detected, based on system parameters. The faults cause arcing grounds, which are prone to fire hazards, leading to loss of life and property. This paper presents a novel method of HIF in distribution feeders, using Wavelet and Decision Tree approaches. Wavelet approach has proved to be successful in understanding and evolving solutions to many problems in Power Quality, Power System Protection, and Transient Analysis. The technique adopted, uses Wavelet Transform (WT) in the pre-processing stage for feature extraction, which is used to prepare the necessary data, to be used in the Decision Tree. The current waveform, when measured at the relaying point, yields coefficients which are used as the inputs to the decision tree. A realistically developed HIF model using a typical IEEE 13 Radial Distribution System was used to determine the performance of the technique for different types of HIF and Capacitor switching, linear faults and non linear load switching, etc. The method was found to be robust, fast, and accurate.

References

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[5]. M. Aucoin, and B.D. Russell, (1987). “Detection of distribution high impedance faults using burst noise signals near 60 Hz”. IEEE Trans. Power Del. Vol.2, No.2, pp.342-348.

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[10]. T.M. Lai, L.A. Snider, E. Lo, and D. Sutanto (2005). “High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion”, IEEE Trans. Power Deliv. Vol.20, pp.397-407.

[11]. A.-R. Sedighi, M.-R.Haghifam, O.P. Malik, and M.-H. Ghassemian (2005). “High impedance fault detection based on wavelet transform and statistical pattern recognition”, IEEE Trans. Power Deliv., Vol.20, No.4, pp.2414-2421.

[12]. M. Yang, J. Gu, C. Jeng, and Wen-Shiow (2004). “Detection high impedance fault in distribution feeder using wavelet transform and artificial neural networks”. In: International Conference on Power System Technology- Powercon 2004, Singapore, Vol.21-24, pp.652-657.

[13]. L. G-Santander, P. Bastard, M. Petit, I. Gal, E. Lopez, and H. Opazo (2005). “Down-conductor fault detection and location via a voltage based method for radial distribution networks”, IEE Proc. Gener. Transm. Distrib., Vol.152, pp.180-184.

[14] W. H. Kersting, (2001). “Radial Distribution Test Feeders”. PES Summer Meeting, IEEE, Vol. 2, pp. 908-912.

[15]. W. H. Kersting, (2010). “Description of the Comprehensive Distribution Test Feeder”. IEEE Power & Energy Society.

[16]. Ibrahem Baqui, Inmaculada Zamora, Javier Mazón, and Garikoitz Buigues, (2011). “High impedance fault detection methodology using wavelet transform and Artificial Neural Networks”. Electric Power Systems Research, Elsvier, Vol.81, pp.1325-1333.

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Research Paper

Multi-Attributes Based Health Assessment of Power Transformers

Chilaka Ranga* , Ashwani Kumar Chandel, Rajeevan Chandel*

* Ph.D Scholar, Department of Electrical Engineering, NIT, Hamirpur, HP, India.

Professor and Head, Department of Electrical Engineering, NIT, Hamirpur, HP, India.

* Professor, Department of Electronics and Communication Engineering, NIT, Hamirpur, HP, India.

Ranga, C., Chandel, A. K., and Chandel, R. (2016). Multi-Attributes Based Health Assessment of Power Transformers. i-manager’s Journal on Power Systems Engineering, 4(3), 28-38. https://doi.org/10.26634/jps.4.3.8269

Abstract

Condition monitoring of power transformers improves the reliability and the safety of an electrical power system. It protects the transformers from fire hazards, and avoids a huge revenue loss to the utilities. The health status of transformers is decided by their several influencing factors. An accurate health assessment of transformers based on various influencing factors has been a challenging task for the researchers as well as the diagnostic experts. In the present paper, a new multi-criterion technique for assessing the health condition of the transformers has been proposed. The main aspects of transformers have been taken into consideration in evaluating their present health status. The overall outcome of the proposed model depends upon all considered attributes as a whole, but not on any single attribute. Hence the proposed approach determines the more reliable and accurate health condition of transformers. It removes the over influence of the attributes in an exact decision making. It also overcomes the shortcomings of the conventional health assessment methods of transformers. Final calculated factors imply what kind of action needs to be implemented for optimal performance and life extension of the transformers.

References

[1]. Jahromi, A., Piercy R., Cress S., and Fan W. (2009). “An approach to power transformer asset management using health index”. IEEE Electrical Insulation Magazine, Vol.25, pp.20-34.

[2]. Dominelli, N. (2004). “Equipment Health Rating of Power Transformers”. IEEE International Symposium on Electrical Insulation, pp. 163-168.

[3]. Gorgan, B., Notingher, P., Badicu, L., and Tanasescu, G. (2010). “Calculation of power transformers health indexes”. Electrical Engineering Series, Vol.34, pp.13-18.

[4]. Xiang, Z., and Gockenbach, E. (2008). “Asset management of transformers based on condition monitoring and standard diagnosis”. IEEE Electrical Insulation Magazine. Vol.24, pp.26-40.

[5]. Spacek, J. (2008). “Maintenance strategies of power equipments with a brief view to condition monitoring of power transformers”. International Conference on Modern Technique and Technologies (MTT), pp. 16-19.

[6]. Lelekajis, A., and Martin, D. (2007). “Comparision of dissolved gas in oil analysis methods using a dissolved gas in oil standard”. IEEE Electrical Insulation Magazine. Vol.27, pp.1-5.

[7]. Yuan, Z., and Chen, M. (2010). “Make use of water and furfural to carry out transformer aging estimation”. IEEE Electrical Insulation Magaine, Vol.22, pp.1-3.

[8]. Piotr, P., and Hanna, M. (2010). “The influence of water content and ageing degree of paper insulation on its mechanical strength”. International Conference on Solid Dielectrics, Vol.5, pp.1-3.

[9]. Rahi, O. P., Chandel, A. K., and Sharma, M. G. (2010). “Refurbishment and up rating of Old Hydro Power Plants”. Indian Journal of Power and River Valley Development. Vol.2, pp.143-147.

[10]. Milan, Z. (1975). Multiple Criterion Decision Making. Tata McGraw-Hill: Delhi.

[11]. Magie, J. F. (1964). Decision Trees for Decision Making. Harvard Business Review.

[12]. Schultz, R. L. (1980). “Descriptive decision making and its applications”. In Applications of Management Science (JAI Press).

[13]. Stewart, T. J. (1997). Scenario Analysis and Multicriteria Decision Making. Springer, Berlin, pp.519-528.

[14]. International Energy Agency, (2004). Guidelines for Hydroelectric Generator Upgrading.

[15]. IEA, (2001). Guidelines on Methodology for Hydroelectric Francis Turbine upgrading by Runner Replacement.

[16]. Tang, W. H., and Hu, W. (2011). Condition Monitoring and Assessment of Power Transformers using Computational Intelligence. London: ISBN 978- 0857290519.

[17]. Han, Y., and Song, Y. H. (2003). “Condition Monitoring Techniques for Electrical Equipment- A Literature Survey”. IEEE Transactions on Power Delivery. Vol.18, pp.4-13.

[18]. Fofana, I., and Borsi, H., Gockenbach, E., Farzaneh, M. (2006). “Ageing of transformer insulating materials under selective conditions”. European Transactions on Electric Power. pp.1-21.

[19]. Shintemiro, A., Tang, W. A., and Wu, Q. H. (2010). “Improved modelling of power transformer winding using bacterial swarming algorithm and frequency response analysis”. Electric Power Systems Research. Vol.80, pp.1111-1120.

[20]. Wang, H., and Butler, K. L. (2001). “Finite element analysis of internal winding faults in distribution transformers”. IEEE Transactions on Power Delivery. Vol.16, pp.1321-1329.

[21]. CIGRE Working Group, (1983). “An international survey on failures in large power transformers in service”. Electra, pp.88-96.

[22]. Wang, M., and Vandermaar, A. J. (2001). “Review of condition assessment of power transformers in service”. IEEE Electrical Insulation Magazine. Vol.18, pp.12-25.

[23]. Persson, C., and Stevenson, J. O. (2001). “Replacement and refurbishment strategies for transformer populations”. CIGRE Colloquium, pp.12-20.

[24]. IEC Publication 60567, (1992). Guide for the Sampling of Gases and Oil from Oil-filled Electrical Equipment and for the Analysis of Free and Dissolved Gases.

[25]. Noonan, T. (2000). “Power transformer on-site condition assessment testing”. International Council on Large Electric Systems, (CIGRE), Paris, France.

[26]. Brooks, R. S., and Urbani, G. S. (1998). “Using the recovery voltage method to evaluate aging in oil-paper insulation”. IEEE Int. Conf. Conduction and Breakdown in Solid Dielectrics, Vasteras, Sweden, pp.93-97.

[27]. Thomas, P., and Shukla, A. K. (2001). “Aging studies on paper – oil to assess the condition of solid insulation th used in power transformers”. IEEE 7 Int. Conf. Solid Dielectrics, Eindhoven: the Netherlands.

[28]. Borsi, H., and Gockenbach, E. (2007). “Monitoring, diagnosis and life management of power transformers”. Conf. Maintenance Operation high-Voltage Electrical Equipment, Sydney: Australia.

[29]. IEEE Std. IEEE Guide for Protective Relay Applications to Power Transformers. C37.91-2000.

[30]. Webster, J., (1999). Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons.

[31]. Oliveira, L. M., and Marques, A. J. (2002). “On-line diagnostics of transformer winding insulation failures by Park's vector approach”. International Electrical Insulation Conference, Berlin-Germany, pp.16-21.

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Research Paper

Optimal Conductor Selection Using Grey Wolf Optimization

M. Laxmidevi Ramanaiah* , M. Damodar Reddy**

* Research Scholar, Department of Electrical and Electronics Engineering, Sri Venkateswara University College of Engineering, SV University, Tirupati, India.

** Professor, Department of Electrical and Electronics Engineering, Sri Venkateswara University College of Engineering, SV University, Tirupati, India.

Laxmidevi, R. M., and Reddy, M. D. (2016). Optimal Conductor Selection Using Grey Wolf Optimization. i-manager’s Journal on Power Systems Engineering, 4(3), 39-43. https://doi.org/10.26634/jps.4.3.8270

Abstract

Conductor selection plays an important role in distribution system. The usual approach is to select the conductor with the least cost. This has an adverse effect on the losses. There is a need to determine the conductors in such a way that there is reduction in the cost of conductor and reduction in losses. Initially, the type of conductors are selected based on flat voltage profile. To reduce the cost of losses incurred on energy and cost of depreciation and interest, the optimization method named as Grey Wolf Optimization (GWO) is proposed. Also the increase in load which can be applied to the network without changing the configuration of the conductors obtained after optimization is determined. The systems used to test the given objective are 16 bus, 22 bus, and 24 bus systems with MATLAB.

References

[1]. Tram, H. N., and Wall, D. L. (1988). “Optimal conductor selection in planning radial distribution systems”. IEEE Transactions on Power Systems, Vol.3, No.1, pp.200-206. http://doi.org/10.1109/59.43199

[2]. Mandal, S., and Pahwa, A. (2002). “Optimal selection of conductors for distribution feeders”. IEEE Transactions on Power Systems, Vol.17, No.1, pp.192-197. http://doi.org/ 10.1109/59.982213

[3]. Sivanagaraju, S., Sreenivasulu, N., Vijayakumar, M., and Ramana, T. (2002). “Optimal conductor selection for radial distribution systems”. Electric Power Systems Research, Vol. 63, No. 2, pp. 95-103. http: //doi.org/10. 1016/S0378-7796(02)00081-0

[4]. Ranjan, R., Chaturvedi, A., Solanki, P.S., and Das, D.(2003). “Optimal conductor selection of radial distribution feeders using evolutionary programming”. In TENCON 2003, Conference on Convergent Technologies for Asia-Pacific Region, Vol.1, pp.456-459. http://doi.org/ 10.1109/TENCON.2003.1273364

[5]. Sivanagaraju, S., and Viswanatha Rao J. (2003). “Optimal conductor selection in radial distribution system using discrete Particle Swarm Optimization”. World Journal of Modelling and Simulation, Vol.5, pp.96-104.

[6]. Ramalinga Raju, M., Ramachandra Murthy, K. V. S., Ravindra, K., and Srinivasa Rao, R. (2010). “Optimal conductor selection for agricultural distribution system - A case study”. In 2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010. http://doi.org/10.1109/ICIAS.2010.5716178

[7]. Srinivasa Rao .R, Satish K., and Narasimham S V. L. (2012). “Optimal Conductor Size Selection in Distribution Systems Using the Harmony Search Algorithm with a Differential Operator”. Electric Power Components and Systems, Vol.40, pp.41-56. http://dx.doi.org/10. 1080/15325008. 2011.621922

[8]. Mirjalili, S Mirjalili S.M, and Lewis, (2014). “Grey Wolf Optimizer”. Advances Engg Softw., Vol. 69, pp. 46-61.

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Research Paper

SVPWM controlled Inverter for Solar Power Generation

Mayank Tyagi* , Ritesh Sharma**

* M.Tech Scholar, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh,

** Assistant Professor, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Uttar Pradesh, India.

Tyagi, M., and Sharma, R. (2016). SVPWM controlled Inverter for Solar Power Generation: A Review. i-manager’s Journal on Power Systems Engineering, 4(3), 44-52. https://doi.org/10.26634/jps.4.3.8271

Abstract

ln this paper, performance of solar photovoltaic power system using State Vector Pulse Width Modulation technique is studied. As we know the solar photovoltaic power generation is getting a wide attention because of its clean and renewable energy, which is the need of the hour to use as an alternate to the conventional energy. However, the power produced by solar PV system contains some power quality problems such as low output voltage, harmonics, ripples, and poor power factor. SVPWM techniques can be applied to reduce such problems. Such methods will be studied in this paper of solar PV power generation containing boost converter.

References

[1]. Photovoltaic System, (n.d.). In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Photovoltaic_system

[2]. Solanki C.S, (2011). Solar Photovoltaics - Fundamentals, Technologies and Applications. Third Edition, PHI Publications.

[3]. P.S. Bimbhra, (2003). Power Electronics. 3 Edition, Khanna Publishers, New Delhi.

[4]. M.H. Rashid, (2001). A Power Electronics Handbook, Academic Press.

[5]. Yuan Deng-Ke, XU Guo-Qing, HU Bo, Xiang An, and Kang Jin-Song, (2008). “Research on a Novel SVPWM for Three-Phase VSI”. In IEEE Vehicle Power and Propulsion Conference (VPPC), Harbin, China.

[6]. Yuan Deng Ke, Tao Sheng Gui, and Gong Xi Guo, (2004). “Principle and characteristics analysis of Space Vector PWM”. The World of Inverters, Vol.12, pp.15-20.

[7]. Mohseni, and M. Islam, (2010). “New Vector-Based Scheme for Three-Phase PWM Voltage-Source Inverters”. IEEE Transactions on Power Electronics, Vol.25, No.9.

[8]. P. Verdelho, (1998). “Voltage type inverter control methods in unbalanced and non-sinusoidal conditions”. th In Conf. Rec. 24 IEEE-IES Annu. Meeting, pp.479-484.

[9]. O. Ogasawara, H. Akagi, and A. Nabel, (1989). “A novel PWM scheme of voltage source inverters based on space vector theory”. In Proc. EPE European Conf. Power Electronics and Applications, pp.1197-1202.

[10]. Chengshanmei, (2002). “The SVPWM simulation in Simulink”. Electrical Automation, Vol.24, No.3, pp.38-41.

i-manager's Journal on Power Systems Engineering (JPS)

Current Issue Vol. 11 Issue 3

Most Read

Most Cited

Volume 4 Issue 3 August - October 2016

Digital Simulation of Eight Bus System with DPFC by Employing Five Level Inverter

Akhib Khan Bahamani* , Sreerama Reddy G.M**, V. Ganesh***

Bahamani, A. K., Reddy, G. S., and Ganesh, V. (2016). Digital Simulation of Eight Bus System with DPFC by Employing Five Level InverterPaper. i-manager’s Journal on Power Systems Engineering, 4(3), 1-11. https://doi.org/10.26634/jps.4.3.8267

Abstract

References

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Decision Tree Technique of High Impedance Fault detection in Distribution Feeder

N. Rajasekhar Varma* , Sanker Ram**

Varma, N. R., and Ram, B. S. (2016). Decision Tree Technique of High Impedance Fault detection in Distribution Feeder. i-manager’s Journal on Power Systems Engineering, 4(3), 12-27. https://doi.org/10.26634/jps.4.3.8268

Abstract

References

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Multi-Attributes Based Health Assessment of Power Transformers

Chilaka Ranga* , Ashwani Kumar Chandel**, Rajeevan Chandel***

* Ph.D Scholar, Department of Electrical Engineering, NIT, Hamirpur, HP, India. ** Professor and Head, Department of Electrical Engineering, NIT, Hamirpur, HP, India. *** Professor, Department of Electronics and Communication Engineering, NIT, Hamirpur, HP, India.

Ranga, C., Chandel, A. K., and Chandel, R. (2016). Multi-Attributes Based Health Assessment of Power Transformers. i-manager’s Journal on Power Systems Engineering, 4(3), 28-38. https://doi.org/10.26634/jps.4.3.8269

Abstract

References

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Optimal Conductor Selection Using Grey Wolf Optimization

M. Laxmidevi Ramanaiah* , M. Damodar Reddy**

Laxmidevi, R. M., and Reddy, M. D. (2016). Optimal Conductor Selection Using Grey Wolf Optimization. i-manager’s Journal on Power Systems Engineering, 4(3), 39-43. https://doi.org/10.26634/jps.4.3.8270

Abstract

References

Full Article (HTML)

Pdf

SVPWM controlled Inverter for Solar Power Generation

Mayank Tyagi* , Ritesh Sharma**

* M.Tech Scholar, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh, ** Assistant Professor, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Uttar Pradesh, India.

Tyagi, M., and Sharma, R. (2016). SVPWM controlled Inverter for Solar Power Generation: A Review. i-manager’s Journal on Power Systems Engineering, 4(3), 44-52. https://doi.org/10.26634/jps.4.3.8271

Abstract

References

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Akhib Khan Bahamani* , Sreerama Reddy G.M, V. Ganesh*

Chilaka Ranga* , Ashwani Kumar Chandel, Rajeevan Chandel*

* Ph.D Scholar, Department of Electrical Engineering, NIT, Hamirpur, HP, India.

Professor and Head, Department of Electrical Engineering, NIT, Hamirpur, HP, India.

* Professor, Department of Electronics and Communication Engineering, NIT, Hamirpur, HP, India.

* M.Tech Scholar, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh,

** Assistant Professor, Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Uttar Pradesh, India.