i-manager Publications

i-manager's Journal on Circuits and Systems (JCIR)

Current Issue Vol. 12 Issue 1

Dynamic Simulation and Sensitivity Analysis of Steam Generation Solar Power Plant
Unified Power Quality Conditioner (UPQC) Research Study on Steady - State Power Flow
Photovoltaic Module Failure Detection using Machine Vision and Lazy Learning Technique
Design and Implementation of Wallace Tree Multiplier and Its Applications in FIR Filter
Review on Obstacle Detection in Solar Panel Cleaning Applications

Most Cited

Volume 1 Issue 1 December - February 2013

Research Paper

Wind Generator Allocation in Distribution Systems Considering Uncertainty In Generation And Time Varying Load Profile

K. Ravindra* , R. Srinivasa Rao, SVL Narasimham*

* Assistant Professor, Electrical Engineering Department, Jawaharlal Nehru Technological University, Kakinada, India.

Associate Professor, Electrical Engineering Department, Jawaharlal Nehru Technological University, Kakinada, India.

* Professor of Computer Science and Engineering, School of IT, Jawaharlal Nehru Technological University, Hyderabad, India.

K. Ravindra, R. Srinivasa Rao and SVL Narasimham (2013). Wind Generator Allocation In Distribution Systems Considering Uncertainty In Generation And Time Varying Load Profile. i-manager’s Journal on Circuits and Systems, 1(1), 1-9. https://doi.org/10.26634/jcir.1.1.2193

Abstract

In this paper, a simultaneous approach to choose optimal number of wind based Distributed Generation (DG) units and their locations is proposed with an objective of minimizing annual energy loss in a distribution network. Most of the methods developed so far for optimal allocation of DG units assumed constant DG output and network load profile which is unreal. Optimal DG sizes and locations found with above assumptions would not lead to minimum annual energy loss when employed in realistic scenario where there is uncertainty in the DG output power generation and network loads have a time-varying load profile. In this work, wind based generation units are considered as the DG sources for allocation. In order to gauge the effect of uncertainty in wind power generation and time-varying load profile on optimal DG allocation problem, a meta-heuristic method which employs Harmony Search algorithm is used to solve multiple wind based DG units. Performance and effectiveness of the proposed method is demonstrated by carrying out simulations on 33-bus and 69-bus radial distribution systems. Simulation results indicate that consideration of uncertainty in wind power generation and time varying load profile significantly affects location and size of DG resources in distribution systems.

References

[1]. Ackermann, T., Anderson, G., and Soder, L. (2001). Distributed generation: Definition. Elect. Power Syst. Res., 57(3), 195–204.

[2]. Rajkumar Viral, Khatod, D.K. (2012). Optimal planning of distributed generation systems in distribution system: A review. Renewable and Sustainable Energy Reviews, 16(7), 5146-5165.

[3]. Acharya ,N., Mahat, P., Mithulananthan, N. (2006). An analytical approach for DG allocation in primary distribution network. Int. J. Electr. Power Energy Syst., 28(10), 669–678.

[4]. Tuba Gözel, M., Hakan Hocaoglu. (2009). An analytical method for the sizing and siting of distributed generators in radial systems. Electric Power Systems Research, 79(6), 912-918.

[5]. Abu-Mouti, F.S, EL-Hawary M.E. (2011). Optimal Distributed Generation Allocation and Sizing in Distributed Systems via Artificial Bee Colony Algorithm. IEEE Transactions on Power Delivery, 26(4), 2090-2101.

[6]. Moradi, M.H., Abedini, M. (2012). A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems, 34(1), 66-74.

[7]. Duong Quoc Hung and Nadarajah Mithulananthan. (2013). Multiple Distributed Generators Placement in Primary Distribution Networks for Loss Reduction. IEEE Transactions on Industrial Electronics, 60(4), 1700-1708.

[8]. Caisheng Wang, Nehrir, M.H. (2004). Analytical approaches for optimal placement of distributed generation sources in power systems. IEEE Transactions on Power Systems, 19(4), 2068- 2076.

[9]. Dan Zhu, Robert P. Broadwater, Kwa-Sur Tam, Rich Seguin, Haukur Asgeirsson. (2006). Impact of DG Placement on Reliability and Efficiency With Time-Varying Loads. IEEE Transactions on Power Systems, 21(1), 419-427.

[10]. Subcommittee P.M. (1979). IEEE Reliability Test System. IEEE transactions on Power Apparatus and Systems, PAS-98(6), 2047-2054.

[11]. Ravindra Kollu, Srinivasa Rao Rayapudi, Narasimham S V L and Krishna Mohan Pakkurthi. (2012). Mixture probability distribution functions to model wind speed distributions. International Journal of Energy and Environmental Engineering, 3(27), doi:10.1186/2251-6832-3-27.

[12]. Singh, C., Lago-Gonzales, A. (1989). Improved algorithms for multi-area reliability evaluation using decomposition-simulation approach. IEEE Transactions on Power System, 4(1), 321–328.

[13]. Mekhamer, S.F, Soliman, S.A, Mostafa, M.A, El-Hawary, M.E. (2001). Load flow solution of radial distribution feeders: a new approach. PPT2001, 3, 1-5.

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

[15]. Geem, Z.W., Kim, J.H., Loganathan, G.V. (2001). A new heuristic optimization algorithm: harmony search. Simulation, 76(2), 60–68.

[16]. Venkatesh, B., Rakesh Ranjan, Gooi, H. B. (2004). Optimal reconfiguration of radial distribution systems to maximize loadability. IEEE Trans. on Power Systems, 19(1), 260-266.

[17]. Savier, J. S., Das, D. (2007). Impact of Network Reconfiguration on Loss Allocation of Radial Distribution Systems. IEEE Trans. on Power Delivery, 2(4), 2473-2480.

[18]. Srinivasa Rao, R., Ravindra, K., Satish, K., Narasimham, S. V. L. (2013). Power Loss Minimization in Distribution System using Network Reconfiguration In the Presence of Distributed Generation. IEEE Transactions on Power Systems, 28(1), 317-325.

[19]. http://www.ndbc.noaa.gov.

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Research Paper

Fuzzy Logiccontrol Of Differential Protection For Large Power Transformer

S.Padmini* , Subransu Sekhar Dash, S. Chandrasekhar*, Priyanka Vedula****

* Assistant Professor, SRM University.

Professor and Head, Department of EEE, SRM University, Shruti.

*-**** B. Tech Student, SRM University.

Padmini, S., Dash, S. S., Chandrasekhar, S. and Vedula, P. (2013). Fuzzy Logiccontrol Of Differential Protection For Large Power Transformer. i-manager’s Journal on Circuits and Systems, 1(1), 10-15. https://doi.org/10.26634/jcir.1.1.2194

Abstract

Advances Differential prot ecti on system is us e d t o protect most of the power transformers in power systems. The protection system is based on the differential currents/voltages of the primary an d secondary of the transformers under fault conditions and under normal operating conditions. The inrus currents or the magnetizing currents are generated in the transformer when it is switched on to the transmission system or the external fault in the system is cleared. The inrush currents other than the fault currents may activate the differential protection system if suitable blocking scheme is not incorporated in the protection system of the power transformer. Therefore, identification of inrush current and the fault currents is the key to improve the security of the differential protection scheme. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke's transform. The result obtained concludes an effective method to differentiate the different internal faults with accuracy as well as shows an improvement in the time taken to detect faults

References

[1]. J.H. Harlow, Ed., Electric Power Transformer Engineering, and 2nd ed.Boca Raton, FL: CRC, 2007.

[2]. M. Sengül, B. Alboyaci, and H. B. Cetinkaya, “Case study of sympathetic interaction between transformers caused by inrush transients,”presented at the Int. Conf. Power Systems Transients, Montreal, QC, Canada, Jun. 19-23, 2005.

[3]. Protective Relaying: Theory and Applications, W. A. Elmore, Ed., 2nded. New York: Marcel Dekker, 2004.

[4]. A.G. Phadke and J.S. Thorp, “A new computer-based lux-restrainedcurrent-differential relay for power transformer protection,” IEEE Trans. Power App. Syst., Vol. PAS-102, No. 11, pp. 3624-3629, Nov.1983.

[5]. A. Wiszniewski and B. Kasztenny, “Fuzzy set approach to transformer differential relay,” in Proc. Developments in Power System Protection Conf., York, U.K., Jun. 1993, pp. 169-172.

[6]. M.-C. Shin, C.-W.Park, and J.-H. Kim, “Fuzzy logic-based relaying for large power transformer protection,” IEEE Trans. Power Del., Vol.18, No. 3, pp. 718-724, Jul. 2003.

[7]. S.H. Horowitz and A.G. Phadke, Power System Relaying, 2nd ed. New York: Wiley, 1992.

[8]. Z. Han, S. Liu, S. Gao, and Z. Bo, “Flow-through inrush and its effect on transformer differential protection,” in Proc. Inst. Eng. Technol.9th Int. Conf. Developments in Power System Protection, Mar. 17-20,2008, pp. 296-301.

[9] M. J. Heathcote, The J&P Transformer Book. Oxford, U.K.: Elsevier,2007.

[10]. E. Segatto and D. Coury, “A differential relay for power transformers using intelligent tools,” IEEE Trans. Power Syst., Vol. 21,No. 3.

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Research Paper

Reducing Clock Power Wastage By Using Conditional Pulse Enhancement Scheme

A. Saisudheer* , V. Muralipraveen**

* M.Tech, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

** Assistant Professor, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

Saisudheer, A. and Muralipraveen, V. (2013). Reducing Clock Power Wastage By Using Conditional Pulse Enhancement Scheme. i-manager’s Journal on Circuits and Systems, 1(1), 16-21. https://doi.org/10.26634/jcir.1.1.2195

Abstract

In this paper, a low-power pulse-triggered flip-flop (FF) designed and a simple two-transistor AND gate is designed to reduce the circuit complexity. Second, a conditional pulse-enhancement technique is devised to speed up the discharge along the critical path only when needed. As a result, transistor sizes in delay inverter and pulse-generation circuit can be reduced for power saving. Various post layout simulation results based on UMC CMOS 50-nm technology reveal that the proposed design features the best power-delay-product performance in several FF designs under comparison. Its maximum power saving against rival designs is up to 18.2% and the average leakage power consumption is also reduced by a factor of 1.52

References

[1]. Yin-Tsung Hwang, Jin-Fa Lin, and Ming- Hwasheu, yin-Tsung Hwang, Jin-Fa Lin, And Ming-Hwasheu Manuscript “Low power pulse triggered flip flop design with conditional pulse enhancement scheme” received April 24,2010; revised August12,2010 and November 13, 2010; accepted November 16, 2010.Date of publication January 06, 2011; date of current version January 18, 2012.

[2]. H. Mahmoodi, V. Tirumalashetty, M. Cooke, and K. Roy, “Ultra low power clocking scheme using energy recovery and clock gating,” IEEE Trans. Very Large Scale Integer. (VLSI) Syst., Vol. 17, pp. 33–44, Jan.2009.

[3]. C. K. Teh, M. Hamada, T. Fujita, H. Hara, N. Ikumi, and Y. Oowaki, “Conditional data mapping flip-flops for low power and high-performance systems,” IEEE Trans. Very Large Scale Integer. (VLSI) Systems, Vol.14, pp.1379–1383, Dec. 2006.

[4]. Y.-H.Shu, S. Tenqchen, M.C.Sun, and W.-S.Feng, “XNOR-based double-edge-triggered flip-flop for two-phase pipelines,” IEEE Trans. Circuits Syst. II, Exp. Briefs, Vol. 53, No. 2, pp. 138–142, Feb. 2006.

[5]. S. H. Rasouli, A. Khademzadeh, A. Afzali-Kusha, and M. Nourani,“ Low power single- and double-edge-triggered flip-flops for high speed applications,” Proc. Inst. Electr. Eng.—Circuits Devices Syst., vol. 152, no. 2, pp. 118–122, Apr. 2005.

[6]. P. Zhao, T. Darwish, and M. Bayoumi, “High-performance and low power conditional discharge flip-flop,” IEEE Trans. Very Large Scale Integer. (VLSI) Syst., Vol. 12, No. 5, pp. 477–484, May 2004.

[7]. V. G. Oklobdzija, “Clocking and clocked storage elements in a multigiga-hertz environment,” IBM J. Res. Devel., Vol. 47, pp. 567–584, Sep.2003.

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Research Paper

Power Quality Improvement In Grid Connected Windenergy System Using Statcom

S. Rajesh Rajan*

Assistant Professor, Lord Jegannath College of Engineering and Technology, Ramanathichanputhur.

Rajan, S. R. (2013). Power Quality Improvement In Grid Connected Windenergy System Using STATCOM. i-manager’s Journal on Circuits and Systems, 1(1), 22-26. https://doi.org/10.26634/jcir.1.1.2196

Abstract

Injection of the wind power into an electric grid affects the power quality. The performance of the wind turbine and thereby power quality are determined on the basis of measurements and the norms followed according to the guideline speci?ed in International Electro-technical Commission standard, IEC-61400.This paper demonstrates the power quality problem due to installation of wind turbine with the grid. In this proposed scheme Static Compensator (STATCOM) is connected at a point of common coupling with a battery energy storage system (BESS) to mitigate the power quality issues. The battery energy storage is integrated to sustain the real power source under ?uctuating wind power. The STATCOM control scheme for the grid connected wind energy generation system for power quality improvement is simulated using MATLAB/SIMULINK in power system block set. The effectiveness of the proposed scheme relives the main supply source from the reactive power demand of the load and the induction generator. The development of the grid co-ordination rule and the scheme for improvement in power quality norms as the grid has been presented

References

[1]. A. Sannino, (2004).“Global power systems for sustainable development,” in IEEE General Meeting, Denver, CO, Jun.

[2]. K.S. Hook, Y.Liu, and S. Atcitty, (2006). ”Mitigation of the wind generation integration related power quality issues by energy storage,” EPQU J., Vol. XII, No. 2.

[3]. J. Manel, (2006). “Power electronic system for grid integration of renewable energy source: A survey,”IEEE Trans. Ind. Electron., Vol. 53, No. 4,pp. 1002-1014,2006, Carrasco.

[4]. M. Tsili and S. Papathanassiou, (2009). ” A review of grid code technology requirements for wind turbine,” Proc. IET Renew.power gen., Vol. 3, pp. 308-332.

[5]. A.E. Hammad, (1995). Comparing the Voltage source capability of Present and future Var Compensation Techniques in Transmission System, IEEE Trans, on Power Delivery. Vol. 1. No.1 Jan.

[6]. G.Yalienkaya, M.H.J Bollen, P.A. Crossley, (1999). “Characterization of Voltage Sags in Industrial Distribution System”, IEEE transactions on industry applications, Vol. 34, No. 4, July/August, PP.682- 688, 1999.

[7]. Haque, M.H., (2001). “Compensation of Distribution Systems Voltage sags by DVR and D-STATCOM”, Power Tech Proceedings, 2001 IEEE Porto, Vol. 1, PP.10-13, September.

[8]. Anaya-Lara O, Acha E., (2002). “Modeling and Analysis Of Custom Power Systems by PSCAD/EMTDC”, IEEE Transactions on Power Delivery, Vol. 17, Issue: 2002, Pages: 266-272.

[9]. Bollen, M.H.J., (2001). ”Voltage sags in Three Phase Systems”, Power Engineering Review, IEEE, Vol. 21, Issue: 9, September 2001, PP: 11-15.

[10]. V.Kumar and J.Karpagam, (2007). ” Control Techniques for Multilevel Voltage Source Inverters, IPEC” Vol. 5, pp.978-981.

[11]. K.Malarvizhi and K.Baskaran, (2010). ” Enhancement of Voltage Stability in Fixed Speed Wind Energy Conversion Systems using FACTS Controller”, International Journal of Engineering Science and Technology, Vol. 2, No. 4, pp.1800-1810, 2010.

[12]. Fu.S Pai and S.I Hung, (2009). ” Design and operation of converter for micro Turbine Powered distributed generator with capacity expansion capability”, IEEE Transactions on Energy Conversion., col. 3, No. 1, pp. 110–116.

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Review Paper

A Review on Control strategies for LFC in Deregulated Scenario

T. Anilkumar* , N. Venkata ramana**

* Associate Professor, EEE Department, ACE Engineering College, Ghatkesar, Hyderabad, AP, India.

** Professor and Head of Deportment, EEE Department, JNTU Mantini, AP, India.

Kumar, T. A., and Ramana, N., (2013). A Review On Control Strategies For LFC In Deregulated Scenario. i-manager’s Journal on Circuits and Systems, 1(1), 27-36. https://doi.org/10.26634/jcir.1.1.2197

Abstract

In power system studies, Load frequency control is an important issue to supply sufficient and reliable electric power with good quality. The main objective of LFC is to maintain load frequency and tie-line power flow within permissible limits by adjusting megawatt output of LFC generators, so as to accommodate fluctuating load demands. This paper presents a brief review of different control techniques to researchers on design of LFC controllers in deregulated environment. The overview of different control strategies are explained in brief, such as Classical and Modern feedback controllers, Adaptive, Intelligent and Robust control strategies along with their relative advantages and disadvantages. Finally, incorporating Facts devices and Energy storage devices in the investigation of LFC problem have also been discussed.

References

[1]. Vaibhav Donde, M., Pai, A., & Hiskens. (2001). Simulation and Optimization in an AGC System after Deregulation, IEEE Transactions on power systems, Vol. 16, No.3.

[2]. Liu, F., Song Y. H., J. Ma., S. Mei., & Q. Lu. (2003). Optimal load-frequency control in restructured power systems, Generation, Transmission and Distribution, IEEE Proceedings, 2003. Vol. 150.

[3]. Sadeh, J., & Rakhshani, E. (2008). Multi-area load frequency control in a deregulated power system using optimal output feedback method, Electricity Market, 2008. 5th International Conference on European.

[4]. Sadeh, J., & Rakhshani, E. (2008). Simulation of two-area AGC system in a competitive environment using reduced-order observer method, Electricity Market, EEM. 5th International Conference on European.

[5]. Sadeh, J., & Rakhshani, E. (2009). A Reduced- Order Estimator with Prescribed Degree of Stability for Two-Area LFC System in a Deregulated Environment, Power Systems Conference and Exposition, PSCE '09,IEEE/PES.

[6]. Sadeh, J., & Rakhshani, E. (2010). Practical viewpoints on load frequency control problem in a deregulated power system, Energy Conversion and Management, Volume 51, Issue 6, Pages 1148–1156.

[7]. Barjeev, Tyagi, & Srivastava, S.C. (2003). A fuzzy logic based load frequency controller in a competitive electricity environment, Power Engineering Society General Meeting, IEEE, Volume: 2.

[8]. Demiroren, A., & Zeynelgil, H. L. (2007). GA application to optimization of AGC in three-area power system after deregulation, Elsevier, International Journal of Electrical Power & Energy Systems, Volume 29, Issue 3, Pages 230–240.

[9]. Ali, E. S., & Abd Elazim, S. M. (2011). Bacteria foraging optimization algorithm based load requency controller for interconnected power system, Elsevier, International Journal of Electrical Power & Energy Systems. Volume 33, Issue 3, Pages 633–638.

[10]. Abedinia, O., Naderi, M. S., & Ghasemi. (2011). A Robust LFC in deregulated environment: Fuzzy PID using HBMO, 10th International Conference on Environment and Electrical Engineering (EEEIC), Publication Page(s): 1 – 4.

[11]. Abedinia, O., Amjady, N., & Naderi, M. S. (2012). Multi-stage Fuzzy PID Load Frequency Control via SPHBMO in deregulated environment, 11th International Conference on Environment and Electrical Engineering (EEEIC), Page(s): 473 – 478.

[12]. Debbarma. S., & Saikia. L. C. (2012). Bacterial foraging based FOPID controller in AGC of an interconnected two-area reheat thermal system under deregulated environment, Advances in Engineering, International Conference on Science and Management (ICAESM), Publication, Page(s): 303 – 308.

[13]. Le-Ren Chang-Chien Chien-Sheng Lo Ko- Shien Lee. (2005). Application of ANN-SCE Model on the Evaluation of Automatic Generation Control Performance, Proceeding (465) Energy and Power Systems.

[14]. Bevrani, Hassan., Hiyama, Takashi., Mitani, Yasunori., Tsuji, Kiichiro., Teshnehlab., & Mohammad. (2006). Load-frequency regulation under a bilateral LFC scheme using flexible neural networks. Engineering Intelligent Systems, 14(2), pp. 109-117.

[15]. Hosseini, S. H., & Etemadi, A. H. (2008). Adaptive neuro-fuzzy inference system based automatic generation control, Elsevier, Electric Power Systems Research 78 1230–1239.

[16]. Sabahi, K., Narimani, E., & Faramarzi, A. (2010). Dynamic neural network for AGC in restructure power system, IEEE International Conference on Power and Energy (PECon), Page(s): 594- 599.

[17]. Sathans, S., & Swarup, A. (2011). Intelligent Load Frequency Control of Two-Area Interconnected Power System and Comparative Analysis. 2011 International Conference on Communication Systems and Network Technologies (CSNT), Page(s): 360 – 365.

[18]. Srinivasa Rao, C. (2012). Adaptive Neuro Fuzzy based Load Frequency Control of multi area system under open market scenario. Science and Management (ICAESM), International Conference on Advances in Engineering, Page(s): 5 – 10.

[19]. Ali, Feliachi. (1996). On Load Frequency Control in a Deregulated Environment, Proceedings of the IEEE International Conference on Control Applications Dearborn, MI September 15-18; 437-441

[20]. Ali, Feliachi. (1997). Reduced H? Load Frequency Controller in a Deregulated Electric Power System Environment, Proceedings of the 36th Conference on Decision & Control San Diego, California USA*.

[21]. Bevrani, H. (1999). Robust load frequency controller in a deregulated environment: a ?- synthesis approach. Control Applications. Proceedings of the IEEE International Conference on control applications, Page(s): 616-621 Vol. 1.

[22]. Bevrani, H., Mitani, Y., & Tsuji, K. (2004). Robust decentralized AGC in a restructured power system, Elsevier, Energy Conversion and Management 45, 2297–2312.

[23]. Bevrani, H., Mitani, Y., Tsuji, K. (2004). Pibased multi-objective load-frequency control in a restructured power system, SICE Annual Conference, Volume: 2 Page(s): 1745 – 1750.

[24]. Bevrani, H., Mitani, Y., & Tsuji, K., (2004). Robust Decentralized LFC Design In a Deregulated Environment, IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRPT2004), Hong Kong.

[25]. Shayeghi, H., Shayanfar, H. A., & Malik. O. P. (2007). Robust decentralized neural networks based LFC in a deregulated power system, Elsevier, Electric Power Systems Research, Volume 77, Issues 3–4, Pages 241– 251.

[26]. Rezvantalab, J., Kazemi, M. H., & Seddigh, A.K. (2009). Multi-area robust decentralized Load Frequency Controller design in a restructured power system using Quantitative Feedback Theory, Electric Power and Energy Conversion Systems, EPECS '09. International Conference on Publication, Page(s): 1 – 6.

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i-manager's Journal on Circuits and Systems (JCIR)

Current Issue Vol. 12 Issue 1

Most Read

Most Cited

Volume 1 Issue 1 December - February 2013

Wind Generator Allocation in Distribution Systems Considering Uncertainty In Generation And Time Varying Load Profile

K. Ravindra* , R. Srinivasa Rao**, SVL Narasimham***

K. Ravindra, R. Srinivasa Rao and SVL Narasimham (2013). Wind Generator Allocation In Distribution Systems Considering Uncertainty In Generation And Time Varying Load Profile. i-manager’s Journal on Circuits and Systems, 1(1), 1-9. https://doi.org/10.26634/jcir.1.1.2193

Abstract

References

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Fuzzy Logiccontrol Of Differential Protection For Large Power Transformer

S.Padmini* , Subransu Sekhar Dash**, S. Chandrasekhar***, Priyanka Vedula****

* Assistant Professor, SRM University. ** Professor and Head, Department of EEE, SRM University, Shruti. ***-**** B. Tech Student, SRM University.

Padmini, S., Dash, S. S., Chandrasekhar, S. and Vedula, P. (2013). Fuzzy Logiccontrol Of Differential Protection For Large Power Transformer. i-manager’s Journal on Circuits and Systems, 1(1), 10-15. https://doi.org/10.26634/jcir.1.1.2194

Abstract

References

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Reducing Clock Power Wastage By Using Conditional Pulse Enhancement Scheme

A. Saisudheer* , V. Muralipraveen**

* M.Tech, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India. ** Assistant Professor, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

Saisudheer, A. and Muralipraveen, V. (2013). Reducing Clock Power Wastage By Using Conditional Pulse Enhancement Scheme. i-manager’s Journal on Circuits and Systems, 1(1), 16-21. https://doi.org/10.26634/jcir.1.1.2195

Abstract

References

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Power Quality Improvement In Grid Connected Windenergy System Using Statcom

S. Rajesh Rajan*

Assistant Professor, Lord Jegannath College of Engineering and Technology, Ramanathichanputhur.

Rajan, S. R. (2013). Power Quality Improvement In Grid Connected Windenergy System Using STATCOM. i-manager’s Journal on Circuits and Systems, 1(1), 22-26. https://doi.org/10.26634/jcir.1.1.2196

Abstract

References

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A Review on Control strategies for LFC in Deregulated Scenario

T. Anilkumar* , N. Venkata ramana**

* Associate Professor, EEE Department, ACE Engineering College, Ghatkesar, Hyderabad, AP, India. ** Professor and Head of Deportment, EEE Department, JNTU Mantini, AP, India.

Kumar, T. A., and Ramana, N., (2013). A Review On Control Strategies For LFC In Deregulated Scenario. i-manager’s Journal on Circuits and Systems, 1(1), 27-36. https://doi.org/10.26634/jcir.1.1.2197

Abstract

References

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K. Ravindra* , R. Srinivasa Rao, SVL Narasimham*

S.Padmini* , Subransu Sekhar Dash, S. Chandrasekhar*, Priyanka Vedula****

* Assistant Professor, SRM University.

Professor and Head, Department of EEE, SRM University, Shruti.

*-**** B. Tech Student, SRM University.

* M.Tech, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

** Assistant Professor, Department of ECE, Chadalawada Ramanamma Engineering College, Tirupathi, India.

* Associate Professor, EEE Department, ACE Engineering College, Ghatkesar, Hyderabad, AP, India.

** Professor and Head of Deportment, EEE Department, JNTU Mantini, AP, India.