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 6 Issue 3 August - October 2018

Research Paper

Correction of Power Factor and Balancing of 3 Phase Unbalanced Load

Shekhappa G. Ankaliki * , Akshay Hegde, Sanjeeth Amminabhavi *

* Professor & Head, Department of Electrical & Electronics Engineering, SDM College of Engineering and Technology, Dharwad, India.

_* PG Scholar, Department of Electrical & Electronics Engineering,SDM College of Engineering and Technology, Dharwad, India.

Ankaliki, G. S., Hegde, A., and Amminabhavi, S. (2018). Power Factor Correction and Balancing of Unbalanced Load. i-manager’s Journal on Power Systems Engineering, 6(3), 1-6. https://doi.org/10.26634/jps.6.3.15482

Abstract

This paper presents correction of power factor and balancing of three phase unbalanced load. The analytical way of correction of power factor and balancing the three phase unbalanced delta connected load is carried out. The analytical results are compared with Matlab simulation results. Simulated results reveal that after correction of power factor and balancing of three phase unbalanced load, all three supply currents are in phase with their respective phase voltages and equal in magnitude resulting in a balanced load on supply system

References

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[2]. Ghosh, A., & Joshi, A. (2000). A new approach to load balancing and power factor correction in power distribution system. IEEE Transactions on Power Delivery, 15(1), 417-422.

[3]. Gueth, G., Enstedt, P., Rey, A., & Menzies, R. W. (1987). Individual phase control of a static compensator for load compensation and voltage balancing and regulation. IEEE Transactions on Power Systems, 2(4), 898-905.

[4]. Husain, Z., Singh, R. K., & Tiwari, S. N. (2010, June). Balancing of unbalanced load and power factor correction in multi-phase (4-phase) load circuits using DSTATCOM. In Proceedings of the World Congress on Engineering (Vol. 2).

[5]. Mayordomo, J. G., Izzeddine, M., & Asensi, R. (2002). Load and voltage balancing in harmonic power flows by means of static VAr compensators. IEEE Transactions on Power Delivery, 17(3), 761-769.

[6]. Miller, T. J. E. (2010). Reactive Power Control in Electrical Systems. Wiley India.

[7]. Otto, R. A., Putman, T. H., & Gyugyi, L. (1978). Principles and applications of static, thyristor-controlled shunt compensators. IEEE Transactions on Power Apparatus and Systems, PAS-97(5), 1935-1945.

[8]. Pan, Z., Peng, F. Z., & Wang, S. (2005). Power factor correction using a series active filter. IEEE Transactions on Power Electronics, 20(1), 148-153.

[9]. Quintela, F. R., Arévalo, J. M. G., Redondo, R. C., & Melchor, N. R. (2011). Four-wire three-phase load balancing with Static VAr Compensators. International Journal of Electrical Power & Energy Systems, 33(3), 562- 568.

[10]. Said, I. K., & Pirouti, M. (2009). Neural network-based load balancing and reactive power control by Static VAR compensator. International Journal of Computer and Electrical Engineering, 1(1), 25-31.

[11]. Steinmetz, C. P. (1917). Theory and Calculation of Electrical Apparatus. New York, USA: McGraw Hill.

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Research Paper

Impacts of Micro-grid and DG on Radial Distribution Network

Rohit Nandi * , Rahul Pathak**

* _** Assistant Professor, Dr. Akhilesh Das Gupta Institute of technology and Management, Shastri park, New Delhi, India.

Nandi, R., and Pathak, R. (2018). Impacts of Micro-grid and DG on Radial Distribution Network. i-manager’s Journal on Power Systems Engineering, 6(3), 7-14. https://doi.org/10.26634/jps.6.3.15500

Abstract

Micro-grid and DG (Distributed generator) plays a crucial role in modern power systems. The large network of any power system ends at distribution side where high current and low voltage level is suitable for operation. This paper briefly describes about different type of DG system and micro-grid components. It covers brief idea about micro-grid controlling scheme and its mode of operation. The effect of external power source and its impacts on load flow study have been demonstrated on IEEE 33 bus radial distribution system. The techniques used for selection and allocation of DG have been mentioned and used analysis based on proposed radial distribution model. The variation of parameters (i.e. voltage and active power loss) after introduction of external active power units have been represented in this paper

References

[1]. Bina, M. T., & Kashefi, A. (2011). Three-phase unbalance of distribution systems: Complementary analysis and experimental case study. International Journal of Electrical Power & Energy Systems, 33(4), 817- 826.

[2]. Bullich-Massagué, E., Díaz-González, F., Aragüés- Peñalba, M., Girbau-Llistuella, F., Olivella-Rosell, P., & Sumper, A. (2018). Microgrid clustering architectures. Applied Energy, 212, 340-361.

[3]. Chakravorty, M., & Das, D. (2001). Voltage stability analysis of radial distribution networks. International Journal of Electrical Power & Energy Systems, 23(2), 129- 135.

[4]. El-Khattam, W., & Salama, M. M. (2004). Distributed generation technologies, definitions and benefits. Electric Power Systems Research, 71(2), 119-128.

[5]. Elnashar, M. M., El Shatshat, R., & Salama, M. M. (2010). Optimum siting and sizing of a large distributed generator in a mesh connected system. Electric Power Systems Research, 80(6), 690-697.

[6]. Jagtap, K. M. (2014, February). Impact of different types of distributed generation on radial distribution network. In 2014 International Conference on Reliability Optimization and Information Technology (ICROIT) (pp. 473-476). IEEE.

[7]. Kamel, R. M., & Kermanshahi, B. (2009). Optimal size and location of distributed generations for minimizing power losses in a primary distribution network. Scientia Iranica. Transaction D, Computer Science & Engineering, Electrical, 16(2), 137.

[8]. Kaur, A., Kaushal, J., & Basak, P. (2016). A review on microgrid central controller. Renewable and Sustainable Energy Reviews, 55, 338-345.

[9]. Kumar, S. A., & Bhimarasetti, R. T. (2018, June). Multiple distribution generation location in reconfigured radial distribution system distributed generation in distribution system. In IOP Conference Series: Earth and Environmental Science (Vol. 164, No. 1, p. 012011). IOP Publishing.

[10]. Levron, Y., Guerrero, J. M., & Beck, Y. (2013). Optimal power flow in microgrids with energy storage. IEEE Transactions on Power Systems, 28(3), 3226-3234.

[11]. Momoh, J. A., Meliopoulos, S., & Saint, R. (2012). Centralized and distributed generated power systems-a comparison approach. Future Grid Initiative White Paper, Power Systems Engineering Research Center, Arizona State University.

[12]. Prabhala, V. A. K., Baddipadiga, B. P., & Ferdowsi, M. (2014, October). DC distribution systems - An overview. In 2014 International Conference on Renewable Energy Research and Application (ICRERA) (pp. 307-312). IEEE.

[13]. Safari, A., Jahani, R., Shayanfar, H. A., & Olamaei, J. (2010). Optimal DG allocation in distribution network. International Journal of Electrical and Electronics Engineering, 4(8), 550-553.

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Research Paper

Performance of Condensate-Vacuum-and-Extraction Pump of BSP with Process Optimization and Optimum Neural Network based Learning System

Sanjeev Karmakar* , Gyan Ranjan Biswal**

* Associate professor, Bhilai Institute of Technology , Bhilai House, Durg, Chhattisgarh, India.

** Assistant Professor, Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, India.

Karmakar, S., and Biswal, R.G (2018). Performance of Condensate-Vacuum-and-Extraction Pump of BSP with Process Optimization and Optimum Neural Network based Learning System. i-manager’s Journal on Power Systems Engineering, 6(3), 15-25. https://doi.org/10.26634/jps.6.3.15305

Abstract

Surface condenser of a power generation plant experiences maximum loss in thermal efficiency (in terms of electrical power output), typically more than 40% of the total generation capacity. The manuscript brings a novel Control and Instrumentation (C&I) approach to enhance the performance of surface condensing unit along with the design issues. This paper presents a control algorithm to get better performance of surface condensation section. The system is designed for maintaining levels of the optimal selection of condensate vacuum pump and condensate extraction pump to minimize the pressure loss involved with the system/section. The work includes a comparison between all the systems presented for system reliability. The 3-parameters Weibull distribution function is uniquely considered for evaluating the design issues of condenser module. It includes the location parameter for identification of faults and execution of operation in real-time. In addition, a process learning system is developed to enhance the performance supervision of the surface condenser in real-time. Effectiveness of the proposed model is validated on real-time automation platform based on specifications of IEEE C37.1-2007, IEC 61131-3 and IEEE 1413-2010.

References

[1]. Alvarez, E. G., Stothert, A., Antoine, M., & Morton, S. (2008). U.S. Patent No. 7,426,456. Washington, DC: U.S. Patent and Trademark Office.

[2]. Arnold, J. J., & Capener, J. R. (2008). Modern Power Station Practice (3^rd Ed.). London: Pergamon Press, Elsevier, British Elect. Int.

[3]. Bansal, R. C. (2006). Overview and literature survey of artificial neural networks applications to power systems (1992-2004). Journal of Institution of Engineers (India)–Electrical Engineering, 86(1), 282-296.

[4]. Birolini, A. (2007). Reliability Engineering: Theory and th Practice (5 Ed.). Berlin, Germany: Springer Science & Business Media.

[5]. Biswal, G. R., Maheshwari, R. P., & Dewal, M. L. (2012). Modeling, control and monitoring of S3RS based hydrogen cooling system in thermal power plant. IEEE Transactions on Industrial Electronics, 59(1), 562-570.

[6]. Currier, J. (2009). U.S. Patent Application No. 12/044,641.

[7]. Dozortsev, V. M., & Kreidlin, E. Y. (2010). State-of-the-art automated process simulation systems. Automation and Remote Control, 71(9), 1955-1963.

[8]. Farrell, C. C., & Billett, R. A. (2009). U.S. Patent Application No. 12/436,326.

[9]. Fujita, I., & Machii, K. (2012). U.S. Patent No. 8,157,898. Washington, DC: U.S. Patent and Trademark Office.

[10]. Ganapathy V. (2003). Industrial Boilers and Heat Recovery Steam Generators: Design, Applications, and Calculations. New York: Marcel Dekker.

[11]. Karmakar, S., Shrivastava, G., & Kowar, M. K. (2014). Impact of learning rate and momentum factor in the performance of back-propagation neural network to identify internal dynamics of chaotic motion. Kuwait Journal of Science, 41(2), 151-174.

[12]. Kawai, K., Takizawa, Y., & Watanabe, S. (1999). Advanced automation for power-generation plants–past, present and future. Control Engineering Practice, 7(11), 1405-1411.

[13]. Kelkar, S., & Kamal, R. (2014). Adaptive fault diagnosis algorithm for controller area network. IEEE Transactions on Industrial Electronics, 61(10), 5527-5537.

[14]. Madni, A. M., Sridhar, P., & Jamshidi, M. (2007, April). Fault-tolerant data acquisition in sensor networks. In 2007 IEEE International Conference on System of Systems Engineering (pp. 1-6). IEEE.

[15]. Michlin, Y. H., Grabarnik, G. Y., & Leshchenko, E. (2009). Comparison of the mean time between failures for two systems under short tests. IEEE Transactions on Reliability, 58(4), 589-596.

[16]. Rueda, A., & Pawlak, M. (2004). Pioneers of the reliability theories of the past 50 years. In Annual Symposium Reliability and Maintainability, 2004-RAMS (pp. 102-109). IEEE.

[17]. Nguyen, T. V., Knudsen, T., Larsen, U., & Haglind, F. (2014). Thermodynamic evaluation of the Kalina splitcycle concepts for waste heat recovery applications. Energy, 71, 277-288.

[18]. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by error propagation. In Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1, D. E. Rumelhart, J. L. McClelland, & Corporate PDP Research Group (Eds.). Cambridge, MA, USA: MIT Press. (pp.318- 362).

[19]. Shafiee, Q., Stefanović, Č., Dragičević, T., Popovski, P., Vasquez, J. C., & Guerrero, J. M. (2014). Robust networked control scheme for distributed secondary control of islanded microgrids. IEEE Transactions on Industrial Electronics, 61(10), 5363-5374.

[20]. Spanger, G. S. (2009). U.S. Patent Application No. 11/898,452.

[21]. Van Gemund, A. J., & Reijns, G. L. (2012). Reliability analysis of k-out-of-n systems with single cold standby using Pearson distributions. IEEE Transactions on Reliability, 61(2), 526-532.

[22]. Yoshii, T., Goshima, S., Takigawa, Y., Obara, F., Nemoto, A., Kawano, S., ... & Nakajima, S. (2009). U.S. Patent No. 7,481,264. Washington, DC: U.S. Patent and Trademark Office.

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Research Paper

Reliability Assessment of Radial Distribution System with Different Automation Schemes of One and Half Breaker Substation

S. Deepti* , E. Vidya Sagar **

* Associate Professor, Department of Electrical and Electronics Engineering, Bhoj Reddy Engineering for Women, Hyderabad, Telangana India.

** Associate Professor, Department of Electrical Engineering, Osmania University, Hyderabad, Telangana, India.

Deepti, S., and Sagar, E. V. (2018). Reliability Assessment of Radial Distribution System with Different Automation Schemes of One and Half Breaker Substation. i-manager’s Journal on Power Systems Engineering, 6(3), 26-31. https://doi.org/10.26634/jps.6.3.15306

Abstract

A radial distribution system consists of 33/11 kV substation, 11kV feeders, distribution transformers, service mains and load points. The reliability of the radial distribution system has a significant influence on overall power system reliability. One of the method to improve the reliability of distribution system is automating both the substation and feeders. The automation process will reduce the restoration time after occurrence of fault and hence the annual average outage duration of load points decreases. In this paper (i) the effect of centralized star and redundant star automation schemes on load points of one and half breaker substation, (ii) the reliability indices of 11 kV radial feeder for non-automated and iii) automated scheme are evaluated. Further, the reliability indices of the complete distribution system for the above said cases are evaluated. Reliability of substation is evaluated using cut-set method and reliability of feeder is evaluated using Failure Mode and Effective Analysis Method (FMEA). Results obtained shows that redundant star automation scheme is better over the centralized star automation scheme. It is also concluded from the results that redundant star substation and feeder automation have more effective impact on distribution reliability.

References

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[2]. Billinton, R., & Allan, R. N. (1996). Reliability Evaluation of Power Systems (2^nd Ed.). New York: Plenum.

[3]. Brown, R. E. (2008). Electric Power Distribution Reliability (3^rdEd.). Florida: CRC Press.

[4]. Brown, R. E., & Taylor, T. M. (1999). Modeling the impact of substations on distribution reliability. IEEE Transactions on Power Systems, 14(1), 349-354.

[5]. Dong, Z., Koval, D. O., & Propst, J. E. (2004). Reliability of various industrial substations. IEEE Transactions on Industry Applications, 40(4), 989-994.

[6]. Hajian-Hoseinabadi, H., Hasanianfar, M., & Golshan, M. E. H. (2012). Quantitative reliability assessment of various automated industrial substations and their impacts on distribution reliability. IEEE Transactions on Power Delivery, 27(3), 1223-1233.

[7]. Heidari, S., & Fotuhi-Firuzabad, M. (2016, October). Reliability evaluation in power distribution system planning studies. In 2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) (pp. 1-6). IEEE.

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[9]. Sagar, E. V., & Prasad, P. V. N. (2010, June). Reliability evaluation of automated radial distribution system. In 2010 IEEE 11^th International Conference on Probabilistic Methods Applied to Power Systems (pp. 558-563). IEEE.

[10]. Tournier, J. C., & Werner, T. (2010). A quantitative evaluation of IEC61850 process bus architectures. In IEEE Power and Energy Society General Meeting 2010 (pp. 1- 8).

[11]. Wu, M. Y., Ridzuan, M. I., & Djokic, S. Z. (2016, November). Smart grid functionalities for improving reliability of rural electricity networks. In Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MedPower 2016) (pp. 1-7). IET.

[12]. Yunus, B., Musa, A., Ong, H. S., Khalid, A. R., & Hashim, H. (2008, December). Reliability and availability study on substation automation system based on IEC 61850. In 2008 IEEE 2^nd International Power and Energy Conference (pp. 148-152). IEEE.

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Review Paper

Spectacular Simulation Review - Analysis of different wind turbine companies by Weibull Analysis

Sunil Kumar Jilledi* , Shalini J., Ashok Kumar Mechiri*

* Research Scholar, OPJS University, Churu, India, and Lecturer, Department of Electrical and computer Engineering, Mainefhi College of Engineering and Technology, Eritrea, East Africa

Assistant Professor, Department of Dairy Engineering, Dairy Technology College, Sri Venkateswara Veterinary University, Andhra Pradesh, India.

*Associate Professor, Eritrea Institute of Technology, Asmara, Eritrea, East Africa.

Jilledi, S. K., Shalini, J., and Mechiri, A. K., (2018). Simulation Review - Analysis of Different Wind Turbine Companies by Wei bull Analysis for Powers Tacular. i-manager’s Journal on Power Systems Engineering, 6(3), 32-42. https://doi.org/10.26634/jps.6.3.15709

Abstract

Renewable energy sources are playing a vital role in the power sector. Among the renewable energy sources, wind energy is playing a vital role. As the power of wind energy system increases, the control of their system becomes complex. Active and reactive power becomes increasingly more important from a system to satisfy the load demand for the consumers. To improve the power production, in the market, many companies are in the competition. Weibull analysis is used for analysis of wind speed. Based on the wind probability distribution function (pdf), the power curve and power distribution is calculated. This paper provides the detail set of power production of different types of wind power plants. A case study has been performed using simulation software by considering the base data of the companies.

References

[1]. Wind Energy Industry Manufacturing Supplier Hand book (2011). Retrieved from www.wire-net.org/pdf/ WindEnergyMFGSupplierHandbook.pdf.

[2]. Annual Report. (2014-2015). Revised list of models and manufacturers of wind turbines by Centre for Wind Energy Technology (CWET). National Institute of Wind Energy. Retrieved form https://niwe.res.in/assets /Docu/annual_report/Annual_Report_2014_2015_ English.pdf

[3]. Azad, A., Rasul, M., & Yusaf, T. (2014). Statistical diagnosis of the best weibull methods for wind power assessment for agricultural applications. Energies, 7(5), 3056-3085.

[4]. Bhadra, S. N., Kastha, D., & Banerjee, S. (2005). Wind Electrical Systems. Oxford University Press.

[5]. Chadee, J. C., & Sharma, C. (2001). Wind speed distributions: a new catalogue of defined models. Wind Engineering, 25(6), 319-337.

[6]. Conradsen, K., Nielsen, L. B., & Prahm, L. P. (1984). Review of Weibull statistics for estimation of wind speed distributions. Journal of climate and Applied Meteorology, 23(8), 1173-1183.

[7]. Dena, D. (2010). Grid Study II. Integration of Renewable Energy Sources in the German Power Supply System from 2015–2020 with an Outlook to 2025. Summary of the main results by the project steering group.

[8]. Dewind. (1995). Retrieved from https://www.thewindpower.net/ manufacturer_en_1_dewi nd.php

[9]. Fuhrlaender. (1991). Retrieved from https://www.thewindpower.net/ manufacturer_en_44_fuhr lander.php

[10]. Gamesa 2.0-2.5MW Technical Evolution. (n.d). Retrieved from https://www.siemensgamesa. com/enint/-/ media/siemensgamesa/downloads/en/investorsand- shareholders/corporate-governance/ generalshareholders- meetings/2018/documentation/is-2017- eng.pdf

[11]. Gamesa Sustainability Report. (2013). Retrieved from https://www.siemensgamesa.com/en-int/- /media/siemensgamesa/downloads/en/investors-ands hare holders/corporate-governance/general-shareholders-meetings/2018/documentation/is-2017- eng.pdf

[12]. Ge. (n.d). Wind Turbines Available in India. https://www.ge.com/in/wind-energy/wind-turbines-inindia

[13]. Gertmar, L., Liljestrand, L., & Lendenmann, H. (2007). Wind energy powers-that-be successor generation in globalization. IEEE Transactions on Energy Conversion, 22(1), 13-28.

[14]. Jilledi, S. K., & Shalini, J. (2017). A novelty comparison of power with assorted parameters of a horizontal wind axis turbine for NACA 5512. In R. Rajesh, B. Mathivanan (1^st Eds.). Communication and Power Engineering (pp. 357-364). https://doi.org/10.1515/ 9783110469608

[15]. Jilledi, S. K., Shalini, J., Teshome, B.,Tuka, M. B., & Wakijira, E. (2013). Improvement of active and reactive power at the wind based renewable energy sources: A case study on ADAMA wind power plant. International Journal of Scientific & Engineering Research, 4(9), 2696- 2702.

[16]. Kaoga, D. K., Sergeb, D. Y., Raidandic, D., & Djongyangd, N. (2014). Performance assessment of twoparameter Weibull distribution methods for wind energy applications in the district of Maroua in Cameroon. International Journal of Sciences, Basic and Applied Research (IJSBAR), 17(1), 39-59.

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

Current Issue Vol. 11 Issue 3

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Most Cited

Volume 6 Issue 3 August - October 2018

Correction of Power Factor and Balancing of 3 Phase Unbalanced Load

Shekhappa G. Ankaliki * , Akshay Hegde**, Sanjeeth Amminabhavi ***

* Professor & Head, Department of Electrical & Electronics Engineering, SDM College of Engineering and Technology, Dharwad, India. **_*** PG Scholar, Department of Electrical & Electronics Engineering,SDM College of Engineering and Technology, Dharwad, India.

Ankaliki, G. S., Hegde, A., and Amminabhavi, S. (2018). Power Factor Correction and Balancing of Unbalanced Load. i-manager’s Journal on Power Systems Engineering, 6(3), 1-6. https://doi.org/10.26634/jps.6.3.15482

Abstract

References

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Impacts of Micro-grid and DG on Radial Distribution Network

Rohit Nandi * , Rahul Pathak**

* _** Assistant Professor, Dr. Akhilesh Das Gupta Institute of technology and Management, Shastri park, New Delhi, India.

Nandi, R., and Pathak, R. (2018). Impacts of Micro-grid and DG on Radial Distribution Network. i-manager’s Journal on Power Systems Engineering, 6(3), 7-14. https://doi.org/10.26634/jps.6.3.15500

Abstract

References

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Performance of Condensate-Vacuum-and-Extraction Pump of BSP with Process Optimization and Optimum Neural Network based Learning System

Sanjeev Karmakar* , Gyan Ranjan Biswal**

* Associate professor, Bhilai Institute of Technology , Bhilai House, Durg, Chhattisgarh, India. ** Assistant Professor, Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, India.

Karmakar, S., and Biswal, R.G (2018). Performance of Condensate-Vacuum-and-Extraction Pump of BSP with Process Optimization and Optimum Neural Network based Learning System. i-manager’s Journal on Power Systems Engineering, 6(3), 15-25. https://doi.org/10.26634/jps.6.3.15305

Abstract

References

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Reliability Assessment of Radial Distribution System with Different Automation Schemes of One and Half Breaker Substation

S. Deepti* , E. Vidya Sagar **

* Associate Professor, Department of Electrical and Electronics Engineering, Bhoj Reddy Engineering for Women, Hyderabad, Telangana India. ** Associate Professor, Department of Electrical Engineering, Osmania University, Hyderabad, Telangana, India.

Deepti, S., and Sagar, E. V. (2018). Reliability Assessment of Radial Distribution System with Different Automation Schemes of One and Half Breaker Substation. i-manager’s Journal on Power Systems Engineering, 6(3), 26-31. https://doi.org/10.26634/jps.6.3.15306

Abstract

References

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Spectacular Simulation Review - Analysis of different wind turbine companies by Weibull Analysis

Sunil Kumar Jilledi* , Shalini J.**, Ashok Kumar Mechiri***

Jilledi, S. K., Shalini, J., and Mechiri, A. K., (2018). Simulation Review - Analysis of Different Wind Turbine Companies by Wei bull Analysis for Powers Tacular. i-manager’s Journal on Power Systems Engineering, 6(3), 32-42. https://doi.org/10.26634/jps.6.3.15709

Abstract

References

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Shekhappa G. Ankaliki * , Akshay Hegde, Sanjeeth Amminabhavi *

* Professor & Head, Department of Electrical & Electronics Engineering, SDM College of Engineering and Technology, Dharwad, India.

_* PG Scholar, Department of Electrical & Electronics Engineering,SDM College of Engineering and Technology, Dharwad, India.

* Associate professor, Bhilai Institute of Technology , Bhilai House, Durg, Chhattisgarh, India.

** Assistant Professor, Department of Electrical Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, India.

* Associate Professor, Department of Electrical and Electronics Engineering, Bhoj Reddy Engineering for Women, Hyderabad, Telangana India.

** Associate Professor, Department of Electrical Engineering, Osmania University, Hyderabad, Telangana, India.

Sunil Kumar Jilledi* , Shalini J., Ashok Kumar Mechiri*