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i-manager's Journal on Electrical Engineering (JEE)

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Volume 11 Issue 1 July - September 2017

Research Paper

Effect Of Stochastic Nature Of Wind EnergyOn Power System

Ann Hesham Ahmed* , Ahmed M. Asim, Mahmoud Abdallah Attia*

* Project Engineer, Electrical Power System Company, Cairo, Egypt.

Teacher Assistant and MSc Student, Ain Shams University, Cairo, Egypt.

* Department of Electrical Power and Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt.

Ahmed, A., Asim, A. M., and Attia, M. A. (2017). Effect of Stochastic Nature Of Wind Energy On Power System. i-manager’s Journal on Electrical Engineering,11(1), 1-9. https://doi.org/10.26634/jee.11.1.13671

Abstract

As the utilization of wind energy grows larger and larger, the need for technical improvement and theoretical understanding becomes significant. Wind energy has been used for many years, however the central questions regarding turbulence are still to be answered. In this complex situation, it is important to analyze the phenomena involved in wind energy extraction. This work presented a stochastic analysis of the power output for a wind turbine based on a Monte Carlo simulation to see how fluctuations in the wind speed will affect the power performance characteristics. It is shown in the presented work by means of a simple model that the probability of power characteristics determined varies with different turbulent wind fields. Then this model is applied on an IEEE 9 bus network.

References

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[4]. Diaa, I. M., Badra, N. M., & Attia, M. A. (2016). Harmony Search and Nonlinear Programming based Hybrid approach to enhance Power System performance with Wind Penetration, International Electrical Engineering Journal (IEEJ), 7(7), 2323-2330.

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[8]. Krohn, S., Morthorst, P. E, & Awerbuch, S. (2009). The Economics of Wind Energy, The European Wind Energy Association Report (EWEA) .

[9]. Meibom, P., Barth, R., Hasche, B., Brand, H., Weber, C., & O'Malley, M. (2011). Stochastic optimization model to study the operational impacts of high wind penetrations in Ireland. IEEE Transactions on Power Systems, 26(3), 1367- 1379.

[10]. Robert, C. P. (2004). Monte Carlo Methods. John Wiley & Sons, Ltd.

[11]. Saber, A. Y., & Venayagamoorthy, G. K. (2011). Plugin vehicles and renewable energy sources for cost and emission reductions. IEEE Transactions on Industrial electronics, 58(4), 1229-1238.

[12]. Shafiullah, G. M., Oo, A. M., Ali, A. B. M., & Stojcevski, A. (2013). Influences of wind energy integration into the distribution network. Journal of Wind Energy, 2013, Article ID 903057.

[13]. Singh, B. (2012). Introduction to FACTS controllers in wind power farms: A technological review. International Journal of Renewable Energy Research (IJRER), 2(2), 166- 212.

[14]. Tavner, P. (2012). Offshore Wind Turbines: Reliability. Availability and Maintenance. The Institution of Engineering and Technology, London, UK.

[15]. Tavner, P. J., Xiang, J., & Spinato, F. (2007). Reliability analysis for wind turbines. Wind Energy, 10(1), 1-18.

[16]. Taylor, H. M., & Karlin, S. (2014). An Introduction to Stochastic Modeling. Academic Press.

[17]. Wind farm - ESL Resources. (2017). In Michellehenry.fr. Retrieved 21 September 2017, from http://www.michelle henry.fr/windfarm.htm

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Research Paper

Loss Reduction, Voltage Improvement and ReliabilityOptimization in Distribution Systems Using NetworkReconfiguration with Loss Sensitivity Factor Method

G. Sasikumar* , S.Sarat Kumar, S.V. Jayaram Kumar*

* Associate Professor, Department of Electrical and Electronics Engineering, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India.

Professor, Department of Electrical and Electronics Engineering, M.V.G.R College of Engineering, VZM, India.

* Former Professor, JNTUH, Adjunct Professor, Department of Electrical and Electronics Engineering, GRIET, Hyderabad, India.

Kumar, G. S., Kumar, S. S., and Kumar, S. V. J. (2017). Loss Reduction, Voltage Improvement and Reliability Optimization in Distribution Systems Using Network Reconfiguration with Loss Sensitivity Factor Method. i-manager’s Journal on Electrical Engineering, 11(1), 10-18. https://doi.org/10.26634/jee.11.1.13672

Abstract

Network reconfiguration is an operation strategy, which alters the topological structure of the distribution feeders by rearranging the status of switches in order to obtain an optimal configuration, minimise system losses, improve voltage profile, and reliability. In this paper, Loss Sensitivity Factor based Network Reconfiguration Algorithm is proposed to decide the switching combinations and to find the best combination of switches for minimum active power loss, improvement of voltage profile, and reliability. The proposed algorithm has been applied to 33-bus Radial Distribution System and the obtained results are analysed.

References

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[2]. Brown, R. E. (2003, July). Network reconfiguration for improving reliability in distribution systems. In Power Engineering Society General Meeting, 2003, IEEE (Vol. 4, pp. 2419-2424). IEEE.

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[6]. Kansal, S., Sai, B. B. R., Tyagi, B., & Kumar, V. (2011). Optimal placement of distributed generation in distribution networks. International Journal of Engineering, Science and Technology, 3(3), 47-55.

[7]. Kazemi, A., & Sadeghi, M. (2009, March). Sitting and sizing of distributed generation for loss reduction. In Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific (pp. 1-4). IEEE.

[8]. Kumar, G. S., Kumar, S. S., & Kumar, S. J. (2017). LSF Based Network Reconfiguration for Loss Reduction in Radial Distribution System. International Journal of Control Theory and Applications, 10(16), 181-189.

[9]. Lantharthong, T., & Phanthuna, N. (2012). Techniques for reliability evaluation in distribution system planning. World Academy of Science, Engineering and Technology, 6, 392-395.

[10]. Merlin, A. (1975). Search for a minimum-loss operating spanning tree configuration for an urban power th distribution system. Proc. of 5 PSCC 1975, 1, 1-18.

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[12]. Peponis, G. J., Papadopoulos, M. P., & Hatziargyriou, N. D. (1995). Distribution network reconfiguration to minimize resistive line losses. IEEE Transactions on Power Delivery, 10(3), 1338-1342.

[13]. Raju, G. V., & Bijwe, P. R. (2008). Efficient reconfiguration of balanced and unbalanced distribution systems for loss minimisation. IET Generation, Transmission & Distribution, 2(1), 7-12.

[14]. Rao, R. S., Narasimham, S. V. L., & Ramalingaraju, M. (2008). Optimization of distribution network configuration for loss reduction using Artificial Bee Colony algorithm. International Journal of Electrical Power and Energy Systems Engineering, 1(2), 116-122.

[15]. Rao, R. S., Narasimham, S. V. L., Raju, M. R., & Rao, A. S. (2011). Optimal network reconfiguration of large-scale distribution system using harmony search algorithm. IEEE Transactions on Power Systems, 26(3), 1080-1088.

[16]. Sankar, V. (2015). System Reliability Concepts. Himalaya Publishing House.

[17]. Vitorino, R. M., Jorge, H. M., & Neves, L. M. (2009, March). Network reconfiguration using a genetic approach for loss and reliability optimization in distribution systems. In Power Engineering, Energy and Electrical Drives, 2009. POWERENG'09. International Conference on (pp. 84-89). IEEE.

[18]. Zhang, D., Fu, Z., & Zhang, L. (2007). An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems. Electric Power Systems Research, 77(5), 685-694.

[19]. Zhu, J. Z. (2002). Optimal reconfiguration of electrical distribution network using the refined genetic algorithm. Electric Power Systems Research, 62(1), 37-42.

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Research Paper

ANT Colony Optimization Based Shunt Active Power FilterFor Harmonic Compensation

Shubhendra Yadav* , Satyendra Singh**

* PG Scholar, Institute of Engineering and Technology, an Autonomous Constituent College of Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India.

** Assistant Professor, Department of Electrical Engineering, Institute of Engineering and Technology, an Autonomous Constituent College of Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India.

Yadav, S., and Singh, S. (2017). ANT Colony Optimization Based Shunt Active Power Filter For Harmonic Compensation. i-manager’s Journal on Electrical Engineering, 11(1), 19-26. https://doi.org/10.26634/jee.11.1.13673

Abstract

This paper presents a comprehensive study on the performance of Shunt Active Harmonic Filter (SAHF) for harmonic compensation, where Ant Colony Optimization technique is used for optimization purpose. This optimization technique operates for the optimal PI control parameters which regulate the DC link voltage. Instantaneous real and reactive power (p-q) theory is used for calculating compensating currents. The simulation results show that Shunt Active Harmonic Filter (SAHF) for six pulse controlled rectifier proves to be very effective in mitigation of the harmonics present for various firing angles. The simulation is carried out with the help of MATLAB-SIMULINK tool box.

References

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[7]. Emanuel, A. E., Orr, J. A., Cyganski, D., and Gulchenski, E. M. (1995). A survey of harmonics voltages, currents at the customer's bus. IEEE Trans. Power Delivery, 8, 411–421.

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[9]. Fujita, H., and Akagi, H. (1991). A practical approach to harmonic compensation in power systems-series connection of passive and active filters. IEEE Transactions on Industry Applications, 27(6), 1020-1025.

[10]. Hamadi, A., Rahmani, S., and Al-Haddad, K. (2010). A hybrid passive filter configuration for VAR control and harmonic compensation. IEEE Transactions on Industrial Electronics, 57(7), 2419-2434.

[11]. Kale, M., and Özdemir, E. (2005). Harmonic and reactive power compensation with shunt active power filter under non-ideal mains voltage. Electric Power Systems Research, 74(3), 363-370.

[12]. Karuppanan, P., and Mahapatra, K. K. (2014). Active harmonic current compensation to enhance power quality. International Journal of Electrical Power and Energy Systems, 62, 144-151.

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[14]. Parthasarathy, S., Rahini, S., and Kumar, S. K. (2015, March). Performance evaluation of Shunt Active Harmonic filter under different control techniques. In Circuit, Power and Computing Technologies (ICCPCT), 2015 International Conference on (pp. 1-8). IEEE.

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Research Paper

A Simulation Platform for Permanent MagnetSynchronous Motor Drives: Matlab/Simulink Simulation

S. Sakunthala* , R. Kiranmayi, P. Nagaraju Mandadi*

* Adhoc Lecturer & Research Scholar, Department of Electrical and Electronics Engineering, JNTUACEK â€“ Kalikiri, JNTUA University, Ananthapuram, AP, India.

Professor and Head, Department of Electrical and Electronics Engineering, JNTUA College of Engineering, Anantapur, AP, India.

* Professor, Department of Electrical and Electronics Engineering, SITIAMS, Chittoor, AP, India.

Sakunthala, S., Kiranmayi, R., and Mandadi, P. N. (2017). A Simulation Platform for Permanent Magnet Synchronous Motor Drives: Matlab/Simulink Simulation. i-manager’s Journal on Electrical Engineering, 11(1), 27-33. https://doi.org/10.26634/jee.11.1.13674

Abstract

In the present circumstances, industries are highly increasing and demanding process in all sectors. Permanent Magnet Synchronous Motor gives better results in quality, increased production, and reduced costs. Permanent Magnet Synchronous Motor (PMSM) drive plays a vital role in each and every industry. There is a necessity to upgrade the models of the electric motors and drives for a better simulation. This paper introduces the design and evolution of a simulation platform of PM Synchronous Motor drive. This paper provides advanced modeling and Matlab simulation tools for PM Synchronous Motor drive to designers and the developers of electric motor drive control systems allowing them to model the independent components using the appropriate software. This paper shows the methodology to interface PMSM Motor on a single simulation platform. In this work, the electric machine model is developed using MATLAB software. Whereas the power electronic converter and PMSM drive control models are designed using mathematical equations in MATLAB/SIMULINK.

References

[1]. Apostoaia, C. M. (2012). Co-simulation platform for AC drives control systems. In WASET 2012-ICEMDS International Conference on Electric Machines and Drive Systems (No. 71, pp. 1879-1886).

[2]. Apostoaia, C. M. (2013, May). AC machines and drives simulation platform. In Electric Machines & Drives Conference (IEMDC), 2013 IEEE International (pp. 1295- 1299). IEEE.

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Research Paper

Analysis of Vector Controlled Permanent MagnetSynchronous Motor Using Matlab/Simulink Approach

Preeti Singh* , Ankit Srivastava**

* Associate Professor, Department of Electrical Engineering, AXIS Colleges, Kanpur, India.

** Guest Faculty, Department of Electrical Engineering, H.B.T.U., Kanpur, India.

Singh, P., and Srivastava, A. (2017). Analysis of Vector Controlled Permanent Magnet Synchronous Motor Using Matlab/Simulink Approach. i-manager’s Journal on Electrical Engineering, 11(1), 34-40. https://doi.org/10.26634/jee.11.1.13675

Abstract

In this paper, a mathematical model of PMSM is analysed using the dominant simulation modelling capabilities of MATLAB/SIMULINK. One of the most efficient control strategies of PMSM is Vector control. There are several independent functional module, such as coordinate transformation module, PMSM body module, inverter module, controller modules, and some other modules which play an important role in controlling of PMSM. The combination of these modules results in simulation model of the PMSM control system. The model has many advantages in simulation. The detailed structure of the simulation model in MATLAB/SIMULINK is presented. Finally, a simulation example is proposed to verify the feasibility.

References

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[2]. Boby, K., Kottalil, A. M., & Ananthamoorthy, N. P. (2013). Mathematical modelling of pmsm vector control system based on SVPWM with pi controller using Matlab. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2(1).

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[6]. Štulrajter, M., Hrabovcova, V., & Franko, M. (2007). Permanent magnets synchronous motor control theory. Journal of Electrical Engineering, 58(2), 79-84.

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Research Paper

Modelling and Analysis of D-Facts Device: EnhancedPower Flow Controller

Dheeraj Kumar Dhaked* , Mahendra Lalwani**

* PG Scholar, Rajasthan Technical University, Kota, India.

** Associate Professor, Department of Electrical Engineering, Rajasthan Technical University, Kota, India.

Dhaked, D. K., Lalwani, M. (2017). Modelling and Analysis of D-Facts Device: Enhanced Power Flow Controller. i-manager’s Journal on Electrical Engineering, 11(1), 41-49. https://doi.org/10.26634/jee.11.1.13676

Abstract

Flexible AC Transmission System (FACTS) controllers control the power flowing through transmission lines to improve utilization of power system, transmission loop flow control, reliability and relieve congestion. High cost, reliability and land restriction issues have limited their use in the power system. The Distributed-FACTS (D-FACTS) controller is presented as a new approach to recognize economic power flow control through compound, small, fixed series impedance injections. A new device which is distributed version of Thyristor Controlled Series Capacitor (TCSC) controller, Enhanced Power Flow Controller (EPFC), connects directly to the existing high voltage or extra high voltage lines. It can be manufactured at a lower price than FACTS controllers from conventional low-grade components. This EPFC is distributed over whole transmission line as modules at every short span of length of transmission lines to attain the required power flow control functionality by changing the transmission line reactance dynamically or statically. It uses the concept of DFACTS to control the power flow. The results from an EPFC MATLAB/Simulink model are presented in this paper on a transmission system which is connected with EPFC controller modules.

References

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[4]. Dhaked, D. K., & Lalwani, M. (2017). A comprehensive review Paper on a D-FACTS Controller: Enhanced Power Flow Controller (EPFC). International Journal of Advances in Engineering & Technology, 10(1), 84-92.

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[9]. Fang, D. Z., Xiaodong, Y., Wennan, S., & Wang, H. F. (2003). Oscillation transient energy function applied to the design of a TCSC fuzzy logic damping controller to suppress power system inter area mode oscillations. IEE Proceedings-Generation, Transmission and Distribution, 150(2), 233-238.

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