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 2 Issue 3 August - October 2014

Research Paper

Role of Power Converters for DFIG based Wind Energy Conversion Systems

Venkatasubramanian. R* , Raghavendiran. T. A**

* Research Schalor, Sathyabama University, Chennai, India.

** Principal, Anand Institute of Higher Technology, Chennai, India.

Venkatasubramanian, R., and Raghavendiran, T. A. (2014). Role of Power Converters for DFIG Based Wind Energy Conversion Systems. i-manager’s Journal on Power Systems Engineering, 2(3), 1-5. https://doi.org/10.26634/jps.2.3.3032

Abstract

This paper explains different converter topologies with different induction generators used for wind energy conversion system. In this focused area of renewable energy resources, wind energy conversion system is more popular than the other conversion systems. Four main types of induction generator used in wind energy conversion system (WECS) are Squirrel Cage Induction Generator (SCIG), Permanent Magnet Synchronous Generator (PMSG), Doubly Fed Induction Generator (DFIG), and Wound Field Synchronous Generator (WFSG). Presently, Doubly-Fed Induction Generator (DFIG) is widely employed in modern wind power industries. The maximum electrical power can be obtained in both wind speeds of above and below synchronous speed using DFIG. Also, it reduces the power rating of the converter. This paper mainly explains the study concepts of Power converter topologies used with Doubly Fed Induction Generator (DFIG) connected wind energy conversion system.

References

[1]. Muller, S., M. Deicke, and R. W. De Doncker, (2002). “Doubly fed induction generator systems for wind turbines," IEEE Ind. Appl. Mag., Vol. 8, No. 3, 26{33.

[2]. Frede Blaabjerg, Marco Liserre and KeMa, (2012). Member “Power Electronics Converters for Wind Turbine Systems” IEEE Transaction on Industry Application, Vol. 48, No. 2, March/April.

[3]. G. Sherestha, H. Polinder, D-J. Bang, J. Ferreira, (2010). “Structural flexibility - A solution for weigh reduction for large direct-driven wind-turbine generators”, IEEE Transaction Energy Conversion Vol.25No. (3), pp.732-740.

[4]. F. Khater, (2012). “Development of wind energy technology: An update”, in: Proceedings of 11th WSEAS International Conference on Instrumentation, Measurements, Circuits & Systems (IMCAS'12), Rovaniemi, Finland, Apr. 18-20, pp. 98-105.

[5]. Asynchronous Generators [Online]. Available: http://www.windturbines.net.

[6]. R.S. Pena, J.C. Clare, and G.M. Asher, (1996). “Vector control of a variable speed doubly-fed induction machine for wind generation system, EPEJ” Vol.6, No 3-4, pp.60-67, Dec.

[7]. R. Pena, J.C. Clare, G.M. Asher, (1996). “Double fed Induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation”. Electric Power Applications, IEE Proceedings. Vol.143 No.(3), pp.231-241.

[8]. W.C. Xu. (1995). “Torque and reactive power control of a Doubly-Fed induction machine by Position sensor less scheme”. IEEE Trans. Industrial Applications, Vol.31 No.(3), pp.636-642.

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Research Paper

Multilevel Inverter With Variable AmplitudeMulticarrier PWM Techniques

P.Suresh Pandiarajan* , S. P. Natarajan, C. R. Balamurugan*

* Department of ECE, P.S.R. Rengasamy College of Engineering for Women, Sivakasi, Tamilnadu, India.

Department of EIE, Annamalai University, Chidambaram, Tamilnadu, India.

* Department of EEE, Arunai Engineering College, Tiruvannamalai, Tamilnadu, India.

Pandiarajan, P. S., Natarajan, S. P., and Balamurugan, C. R. (2014). Multilevel Inverter With Variable Amplitude Multicarrier Pwm Techniques. i-manager’s Journal on Power Systems Engineering, 2(3), 6-10. https://doi.org/10.26634/jps.2.3.3031

Abstract

This paper deals with Single Phase Five level Inverter using Multi Carrier Based Pulse Width Modulation Technique. The voltage quality of conventional two level inverter is poor due to the presence of harmonics and hence produces power loss which reduces the efficiency of the system. The multilevel inverter is used to improve the voltage quality by reducing the harmonics. As the number of voltage levels of multilevel inverter is increased, the harmonics are reduced and hence losses are minimized significantly. The simulation of single phase cascaded five level multilevel is done using Multicarrier PWM technique and compared with sine wave. Here the authors compared conventional PD and variable PD and simulated outputs were given.

References

[1]. Jie Zhang, Yunping Zon, Xian Zhang and Kai Ding, (2001). Study on a Modified Multilevel Cascaded Inverter with Hybrid Modulation, IEEE Power Electronics Drives System, Rec: 0-7803-7233-6/01, pp.379-383.

[2]. Keith A. Corzine, Mike W. Wielebski, Fang Z. Peng and Jin Wan, (2004). Control of Cascaded Multilevel Inverter, IEEE Trans. on Power Electro., Vol.19, No.3, pp.732-738.

[3]. Mr. G. Pandian and Dr. S. Rama Reddy. (2008). Implementation of Multilevel Inverter-Fed Induction Motor Drive. Journal of industrial technology, Vol. 24.

[4]. Yang Han, Lin Xu, Gang Yao, Li-Dan Zhou, Mansoor and Chen Chen. (2009). Operation Principles and Control Strategies of Cascaded H-bridge Multilevel Active Power Filter. Electronics and Electrical Engineering, ISSN 1392 - 1215 2009. 3(91).

[5]. S. Mohamed Yousuf, P. Vijayadeepan and S. Latha. (2012). The Analysis of Multi-Carrier PWM Control Techniques for Neutral Clamped Multilevel Z-Source Inverter. International Conference on Computing and Control Engineering (ICCCE 2012), 12 and 13 April.

[6]. E. Sambath, S.P. Natarajan and C.R. Balamurugan. (2012). Performance Evaluation of Multi Carrier Based PWM Techniques for Single Phase Five Level HBridge Type FCMLI. IOSR Journal of Engineering (IOSRJEN) ISSN: 2250- 3021. Vol.2 No.(7): pp.82-90.

[7]. S. Malathy and U. Shajith Ali. Performance Analysis of Multi-Carrier PWM Based Cascaded Multilevel Inverter. GJPAST | MAR - APR 2012 ISSN: 2249- 7188.

[8]. Muhammad H Rashid. (1996). Power Electronics Circuits Devices and Applications. 2nd Ed. PHI, New Delhi, India. pp. 566-572.

[9]. Leon M. Tolbert, IEEE, Fang Zheng Peng. (2000). IEEE and Thomas G. Habetler. IEEE Multilevel PWM Methods at Low Modulation Indices IEEE Transactions on Power Electronics. Vol.15 No.(4), July.

[10]. G. Mahesh, Manivanna Kumar and S. Rama Reddy. (2011). Simulation and Experimental Results of 7-Level Inverter System, Research Journal of Applied Sciences, Engineering and Technology. Vol.3 No.(2): pp.88-95, ISSN: 2040-7467.

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Research Paper

Approximate System Reliability Analysis of Power System networks using Cutsets

D. Ravi Kumar* , V.Sankar**

* Assistant Professor, EEE Department, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, India.

** Professor, EEE Department, Jawaharlal Nehru Technological University, Anantapur, India.

Kumar, D. R., and Sankar, V. (2014). Approximate System Reliability Analysis of Power System networks using Cutset. i-manager’s Journal on Power Systems Engineering, 2(3), 11-21. https://doi.org/10.26634/jps.2.3.3039

Abstract

A system is a collection of components arranged to a specific design in order to achieve desired functions with acceptable performance and reliability. Reliability engineers often need to work with systems having elements connected in series and parallel, and to calculate their reliability. To this end, when a system consist of combination of series and parallel segments, engineers often apply very convoluted block reliability formulae and use software calculation packages. As the underlying statistical theory behind the formulae is not always well understood, errors or misapplications may occur. In this paper, exponentially distributed failure rate of the components will be considered for unit or component redundancies and evaluation of basic probability indices for various system configurations like series parallel, series-parallel, parallel-series configurations and complex systems have been dealt with deriving generalized expressions for ‘n’ component repairable systems. A computer program has been developed to apply generalized expressions for various systems. Application of the derived formulae is used to obtain basic probability indices of load point and for the Power System network.

References

[1]. R. Billinton, S. Kumar, N. Chowdhury, K. Chu, K. Debnath, L. Goel, E.Khan, P. Kos, G. Nourbaksh,, J. Oteng- Adjei, (1989). “A Reliability Test System For Educational Purposes – Basic Data”, IEEE Transactions on Power Systems, Vol. 4, No. 3, August.

[2]. Y. Massim, A. Zeblah, (2004). “Optimal Design and Reliability Evaluation of Multi-State Series- Parallel Power Systems,” Springer-Non linear Dynamics, Volume 40, Issue 4, pp 309-321.

[3]. Amir Azaron, Hideki Katagiri, Kosuke Kato, (2005). “Reliability evaluation and optimization of dissimilar component cold-stand by redundant systems”, Journal of the Operation research, Society of Japan, Vol. 48, No. 1, pp.71-88.

[4]. Kolowrocki Krzysztof, (2007). “Reliability modeling of complex systems - Part 1”, Summer Safety and Reliability Seminars, July 22-29, pp. 219-230.

[5]. Kolowrocki Krzysztof, (2007). “Reliability modeling of complex systems - Part 2”, Summer Safety and Reliability Seminars, July 22-29, pp. 231-242.

[6]. Ammar M. Sarhan, L. Tadj, A. Al-khedhairi and A. Mustafa, (2008). “Equivalence factors of a parallel-series system,” Applied Sciences, Vol.10, pp. 219-230.

[7]. V. Sankar, (1992). Some aspects of Power System Network Reliability studies, Ph.D thesis, IIT Delhi.

[8]. R. Billinton, R. N. Allan, (2007). Reliability Evaluation of Engineering Systems, Plenum Press, New York, Springer Publication, reprinted in India by B.S. Publications.

[9]. Charles E. Ebeling, (2009). An Introduction to Reliability and Maintainability Engineering, Waveland Pr Inc.

[10]. E. Balagurusamy, (2010). Reliability Engineering, Tata McGraw-Hill Publishing Company, Limited.

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Research Paper

Observability Analysis, State Estimation & Bad DataDetection For Power System Using Measured Data

Manjula S. Sureban* , Shekhappa G. Ankaliki **

* P.G. Scholar, Department of Electrical and Electronics Engineering, SDM College of Engineering & Tech, Dharwad, India.

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

Sureban, S. M., and Ankaliki, S. G. (2014). Observability Analysis, State Estimation & Bad Data Detection For Power System Using Measured Data. i-manager’s Journal on Power Systems Engineering, 2(3), 22-27. https://doi.org/10.26634/jps.2.3.3030

Abstract

This paper presents a simple algorithm for the Static State Estimation of a Power System. The proposed algorithm makes use of the Weighted Least Square Estimation techniques to estimate the Static State of Power System and hence to analyse the observability of the power system network. Concept of Chi-square test is used to detect the presence of bad measurements in the available data. Developed algorithm is demonstrated for sample 2 bus system.

References

[1]. Monticelli, A. ; UNICAMP, Sao Paulo, Brazil, (2000). Electric power system state estimation Proceedings of the IEEE, Vol.88, No.2, ISSN: 0018-9219 INSPEC Accession Number: 6502802. Page(s): 262 - 282.

[2]. Alsac, O.; PCA Corp., Meza, AZ, USA; Vempati, N.; Stott, B.; Monticelli, A. (1998). Generalized state estimation Power Systems, IEEE Transactions Vol.13, No.3, ISSN: 0885-8950 INSPEC Accession Number: 6002923. Page(s): 1069 - 1075.

[3]. Shivakumar, N.R.; Power Syst. Res. Center, Int. Inst. of Inf. Technol. (IIIT), Hyderabad; Jain, A. (2008). A Review of Power System Dynamic State Estimation Techniques. Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. E-ISBN: 978-1- 4244-1762-9, INSPEC Accession Number:10456092.

[4]. Er. Gyanendra Singh, RITM, Lucknow (U.P.) India, (2013). An algorithm for Observability determination in Bus- System State Estimation using Matlab Simulation. International Journal of Scientific & Engineering Research, Vol.4, No.10, October-2013, ISSN 2229-5518.

[5]. Kumar, R.; Electr. Eng., SBCET Jaipur, Jaipur, India; Prasad, D. (2012). Effect of bad measurements on state estimation in power system Power India Conference, 2012 IEEE Fifth Print ISBN: 978-1-4673-0763-5 INSPEC Accession No.13384250.

[6]. D P Kothari, Vice Chancellor,VIT University I J Nagrath, Adjunct Professor, and Former Deputy Director, Modern power system Analysis, Third Edition Birla Ins1i1y7" of Technologt and Science, Pilani Tata.

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Research Paper

Optimal Multi-Objective Hybrid Measurement Placement Using NSGA-II

Basetti Vedik* , Ashwani Kumar Chandel**

* Research Scholar, Department ot Electrical Engineering, NIT-Hamirpur, H.P, India.

** Professor, Department of Electrical Engineering, NIT-Hamirpur, H.P, India.

Vedik, B., and Chandel, A. K. (2014). Optimal Multi-Objective Hybrid Measurement Placement Using Nsga-II. i-manager’s Journal on Power Systems Engineering, 2(3), 28-43. https://doi.org/10.26634/jps.2.3.3033

Abstract

In this paper, non-dominated sorting genetic algorithm-II(NSGA-II) is proposed for optimal placement of hybrid, i.e. PMUs and conventional meters. The hybrid measurement placement problem has been solved by simultaneously optimizing the two conflicting objectives, viz, Maximizing the measurement redundancy and the other, minimizing the installation cost ensuring full network observability. The Pareto optimal solutions are obtained using the non-dominated sorting and crowding distance criterion. Subsequently, a decision making procedure based on VIKOR method is employed to determine the best conciliation solution from the set of Pareto-optimal front. The effectiveness and flexibility of the proposed algorithm has been tested on IEEE 14-bus, IEEE-30 bus, and IEEE 57-bus systems respectively

References

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[2]. Ahmadi, A., Alinejad-Beromi, Y., & Moradi, M. (2011). Optimal PMU placement for power system observability using binary particle swarm optimization and considering measurement redundancy. Expert Systems with Applications, Vol.38, No.6, pp.7263-7269.

[3]. Aminifar, F., Lucas, C., Khodaei, A., & Fotuhi- Firuzabad, M. (2009). Optimal placement of phasor measurement units using immunity genetic algorithm. Power Delivery, IEEE Transactions, Vol.24, No.3, pp.1014- 1020.

[4]. Aminifar, F., Khodaei, A., Fotuhi-Firuzabad, M., & Shahidehpour, M. (2010). Contingency-constrained PMU placement in power networks. Power Systems, IEEE Transactions, Vol.25, No.1, pp.516-523.

[5]. Baldwin, T. L., Mili, L., BoisenJr, M. B., & Adapa, R. (1993). Power system observability with minimal phasor measurement placement. Power Systems, IEEE Transactions, Vol.8, No.2, pp.707-715.

[6]. Basu, M. (2008). Dynamic economic emission dispatch using nondominated sorting genetic algorithm- II. International Journal of Electrical Power & Energy Systems, Vol.30, No.2, pp.140-149.

[7]. Chakrabarti, S., & Kyriakides, E. (2008). Optimal placement of phasor measurement units for power system observability. Power Systems, IEEE Transactions, Vol.23, No.3, pp.1433-1440.

[8]. Chakrabarti, S., Venayagamoorthy, G. K., & Kyriakides, E. (2008, December). PMU placement for power system observability using binary particle swarm optimization. In Power Engineering Conference, 2008. AUPEC'08. Australasian Universities. pp. 1-5). IEEE.

[9]. Chakrabarti, S., Kyriakides, E., &Eliades, D. G. (2009). Placement of synchronized measurements for power system observability. Power Delivery, IEEE Transactions, Vol.24, No.1, pp.12-19.

[10]. Chang, C. L. (2010). A modified VIKOR method for multiple criteria analysis. Environmental monitoring and assessment, Vol.168, pp.1-4, pp.339-344.

[11]. Christie, R. (1999). Power System Test Archive, Aug.

[12]. Chunhua, P., & Xuesong, X. (2008, April). A hybrid algorithm based on immune BPSO and N-1 principle for PMU multi-objective optimization placement. In Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference, pp. 610-614, IEEE.

[13]. de Almeida, M. C., Garcia, A. V., & Asada, E. N. (2012). Regularized least squares power system state estimation. Power Systems, IEEE Transactions, Vol.27, No.1, pp.290-297.

[14]. Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. Evolutionary Computation, IEEE Transactions, Vol.6, No.2, pp.182-197.

[15]. Do CouttoFilho, M. B., da Silva, A. L., Cantera, J. C., & da Silva, R. A. (1989, May). Information debugging for real-time power systems monitoring. In IEE Proceedings C (Generation, Transmission and Distribution), Vol. 136, No. 3, pp. 145-152. IET Digital Library.

[16]. Enshaee, A., Hooshmand, R. A., & Fesharaki, F. H. (2012). A new method for optimal placement of phasor measurement units to maintain full network observability under various contingencies. Electric Power Systems Research, Vol.89, pp.1-10.

[17]. Firouzjah, K. G., Sheikholeslami, A., & Barforoushi, T. (2012). Multi-objective allocation of measuring system based on binary particle swarm optimization. Frontiers of Electrical and Electronic Engineering, Vol.7, No.4, pp.399-415.

[18]. Gou, B. (2008). Optimal placement of PMUs by integer linear programming. IEEE Transactions on power systems, Vol.23, No.3, pp.1525-1526.

[19]. Hajian, M., Ranjbar, A. M., Amraee, T., & Shirani, A. R. (2007, November). Optimal placement of phasor measurement units: particle swarm optimization approach. In Intelligent Systems Applications to Power Systems, 2007. ISAP 2007. International Conference, pp. 1-6. IEEE.

[20]. Jamuna, K., & Swarup, K. S. (2012). Multi-objective biogeography based optimization for optimal PMU placement. Applied Soft Computing, Vol.12, No.5, pp.1503-1510.

[21]. Kavasseri, R., & Srinivasan, S. K. (2011). Joint placement of phasor and power flow measurements for observability of power systems. Power Systems, IEEE Transactions, Vol.26, No.4, pp.1929-1936.

[22]. Khiabani, V., Yadav, O. P., & Kavasseri, R. (2011). Reliability-based placement of phasor measurement units in power systems. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 1748006X11417959.

[23]. Khiabani, V., Kavasseri, R., & Farahmand, K. (2012). A Reliability Based Multi-Objective Formulation for Optimal PMU Placement. International Review on Modelling & Simulations, Vol.5, No.4.

[24]. Khiabani, V., Erdem, E., Farahmand, K., & Nygard, K. (2013, August). Genetic algorithm for instrument placement in smart grid. In Nature and Biologically Inspired Computing (NaBIC), 2013 World Congress, pp. 214-219, IEEE.

[25]. Korkali, M., & Abur, A. (2009, July). Placement of PMUs with channel limits. In Power & Energy Society General Meeting, 2009.PES'09. IEEE, pp. 1-4, IEEE.

[26]. Koutsoukis, N. C., Manousakis, N. M., Georgilakis, P. S., & Korres, G. N. (2013). Numerical observability method for optimal phasor measurement units placement using recursive Tabu search method. Generation, Transmission & Distribution, IET, Vol.7, No.4, pp.347-356.

[27]. Li, D. H., Cao, Y. J., Jiang, Q. Y., & Zhan, Z. B. (2005). Optimal Placement of Phasor Measurement Unit Based on Multi-Objective Evolutionary Algorithm [J].Power System Technology, Vol.22, 013.

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[29]. Mahari, A., & Seyedi, H. (2013). Optimal PMU placement for power system observability using BICA, considering measurement redundancy. Electric Power Systems Research, Vol.103, pp.78-85.

[30]. Manousakis, N. M., Korres, G. N., & Georgilakis, P. S. (2012). Taxonomy of PMU placement methodologies. Power Systems, IEEE Transactions, 27, No.2, pp.1070- 1077.

[31]. Manousakis, N. M., &Korres, G. N. (2013). A Weighted Least Squares Algorithm for Optimal PMU Placement. Power Systems, IEEE Transactions, Vol.28, No.3, pp.3499-3500.

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

Current Issue Vol. 11 Issue 3

Most Read

Most Cited

Volume 2 Issue 3 August - October 2014

Role of Power Converters for DFIG based Wind Energy Conversion Systems

Venkatasubramanian. R* , Raghavendiran. T. A**

* Research Schalor, Sathyabama University, Chennai, India. ** Principal, Anand Institute of Higher Technology, Chennai, India.

Venkatasubramanian, R., and Raghavendiran, T. A. (2014). Role of Power Converters for DFIG Based Wind Energy Conversion Systems. i-manager’s Journal on Power Systems Engineering, 2(3), 1-5. https://doi.org/10.26634/jps.2.3.3032

Abstract

References

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Multilevel Inverter With Variable AmplitudeMulticarrier PWM Techniques

P.Suresh Pandiarajan* , S. P. Natarajan**, C. R. Balamurugan***

* Department of ECE, P.S.R. Rengasamy College of Engineering for Women, Sivakasi, Tamilnadu, India. ** Department of EIE, Annamalai University, Chidambaram, Tamilnadu, India. *** Department of EEE, Arunai Engineering College, Tiruvannamalai, Tamilnadu, India.

Pandiarajan, P. S., Natarajan, S. P., and Balamurugan, C. R. (2014). Multilevel Inverter With Variable Amplitude Multicarrier Pwm Techniques. i-manager’s Journal on Power Systems Engineering, 2(3), 6-10. https://doi.org/10.26634/jps.2.3.3031

Abstract

References

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Approximate System Reliability Analysis of Power System networks using Cutsets

D. Ravi Kumar* , V.Sankar**

* Assistant Professor, EEE Department, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, India. ** Professor, EEE Department, Jawaharlal Nehru Technological University, Anantapur, India.

Kumar, D. R., and Sankar, V. (2014). Approximate System Reliability Analysis of Power System networks using Cutset. i-manager’s Journal on Power Systems Engineering, 2(3), 11-21. https://doi.org/10.26634/jps.2.3.3039

Abstract

References

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Observability Analysis, State Estimation & Bad DataDetection For Power System Using Measured Data

Manjula S. Sureban* , Shekhappa G. Ankaliki **

* P.G. Scholar, Department of Electrical and Electronics Engineering, SDM College of Engineering & Tech, Dharwad, India. ** Professor, Department of Electrical and Electronics Engineering, SDM College of Engineering & Tech, Dharwad, India.

Sureban, S. M., and Ankaliki, S. G. (2014). Observability Analysis, State Estimation & Bad Data Detection For Power System Using Measured Data. i-manager’s Journal on Power Systems Engineering, 2(3), 22-27. https://doi.org/10.26634/jps.2.3.3030

Abstract

References

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Optimal Multi-Objective Hybrid Measurement Placement Using NSGA-II

Basetti Vedik* , Ashwani Kumar Chandel**

* Research Scholar, Department ot Electrical Engineering, NIT-Hamirpur, H.P, India. ** Professor, Department of Electrical Engineering, NIT-Hamirpur, H.P, India.

Vedik, B., and Chandel, A. K. (2014). Optimal Multi-Objective Hybrid Measurement Placement Using Nsga-II. i-manager’s Journal on Power Systems Engineering, 2(3), 28-43. https://doi.org/10.26634/jps.2.3.3033

Abstract

References

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* Research Schalor, Sathyabama University, Chennai, India.

** Principal, Anand Institute of Higher Technology, Chennai, India.

P.Suresh Pandiarajan* , S. P. Natarajan, C. R. Balamurugan*

* Department of ECE, P.S.R. Rengasamy College of Engineering for Women, Sivakasi, Tamilnadu, India.

Department of EIE, Annamalai University, Chidambaram, Tamilnadu, India.

* Department of EEE, Arunai Engineering College, Tiruvannamalai, Tamilnadu, India.

* Assistant Professor, EEE Department, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, India.

** Professor, EEE Department, Jawaharlal Nehru Technological University, Anantapur, India.

* P.G. Scholar, Department of Electrical and Electronics Engineering, SDM College of Engineering & Tech, Dharwad, India.

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

* Research Scholar, Department ot Electrical Engineering, NIT-Hamirpur, H.P, India.

** Professor, Department of Electrical Engineering, NIT-Hamirpur, H.P, India.