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 5 Issue 2 May - July 2017

Research Paper

Modelling of Integrated Recycle Heat Exchangers

David D. Biruk* , Chiu Choi, John Kang*

* Manager, Electric Production Reliability Engineering, Northside Generating Station, JEA, Jacksonville, Florida, USA.

Professor, Electrical Engineering Program, University of North Florida, Jacksonville, Florida, USA.

* Manager, Reliability Engineering (Retired), Northside Generating Station, JEA, Jacksonville, Florida, USA.

Biruk, D. D., Choi, C., and Kang, J. (2017). Modelling of Integrated Recycle Heat Exchangers. i-manager’s Journal on Power Systems Engineering, 5(2), 1-9. https://doi.org/10.26634/jps.5.2.13617

Abstract

This paper describes the mathematical modelling of an Integrated Recycle Heat Exchanger in a 300 MW Circulating Fluidized Bed Boiler currently in operation in the Northside Power Generation Plant of JEA. Numerical data were collected from the operation. The data were used in the development and training of regression and neural network models for the Integrated Recycle Heat Exchanger. The performance of the regression and neural network models were compared using five different criteria. The findings were described in this paper. Minor differences between the performances of these models were also discussed.

References

[1]. Biruk, D. D. (2013). Neural Network Based Control of Integrated Recycle Heat Exchanger Superheaters in Circulating Fluidized Bed Boilers. (M.S. thesis, School of Eng., University of North Florida, Jacksonville, Florida).

[2]. Gallant, S. I. (1993). Neural Network Learning and Expert Systems. Cambridge: MIT press.

[3]. Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feed for ward networks are universal approximators. Neural Networks, 2(5), 359-366.

[4]. Kang, J., & F. Thomas, F. (2011). JEA increases power output through CFB improvements. Power, 155(10), 18- 18.

[5]. Kang, J., Beverly, R., Porter, D., & Leach, B. (2012). Reducing Ash Agglomeration in JEA's CFB Boilers. Power, 156(10), 52-57.

[6]. Krusienski, D. J., & Jenkins, W. K. (2005). Design and performance of adaptive systems based on structured stochastic optimization strategies. IEEE Circuits and Systems Magazine, 5(1), 8-20.

[7]. Leverington, D. (2009). A basic introduction to feedforward backpropagation neural networks. Neural Network Basics. Retrieved from http://www.webpages. ttu.edu/dleverin/neural_network/neural_networks.html

[8]. Montgomery, D. C., Rugner, G. C., & Hubele, N. F. (2004). Engineering Statistics. New York: John Wiley & Sons.

[9]. No, C. A. (2005). JEA Large-Scale CFB Combustion Demonstration Project (No. 22.2003). The US Department of Energy and JEA, Report. Retrieved from http://www.netl.doe.gov/publications/press/2005/jea_fin al_technical_report.pdf

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Research Paper

A Two Stage Optimal Sitting and Sizing of Multiple Distributed Generators byImproved Teaching and Learning Optimization Algorithm

G. Balakrishna*

*Professor, Department of Electrical and Electronics Engineering, Sreenivasa Ramanujan Institute of Technology, Anantapuramu, India.

Balakrishna, G. (2017). A Two Stage Optimal Sitting and Sizing of Multiple Distributed Generators by Improved Teaching and Learning Optimization Algorithm i-manager’s Journal on Power Systems Engineering, 5(2), 10-18. https://doi.org/10.26634/jps.5.2.13618

Abstract

The quality of power in terms of inbound and constant voltages available at various consumers' terminals is expected to be good whenever the distribution system to which these consumers are connected is correctly planned and designed. But, it is becoming challenging due to the continuous increase in the electrical power demand that leads to go for using Distributed Generators (DG). In this work, a two stage optimal sitting and sizing of Distributed Generators is proposed in which at first stage, the optimal locations of these DG units are obtained by sensitivity analysis and in the latter stage, optimal sizes of these units are obtained by an improved Teaching and Learning optimization algorithm by considering the multiple objective functions like minimization of power loss, cost function, and emission produced. The proposed algorithm is tested on a 69-bus radial distribution test system with two substations based on the three objectives and the results are presented. Simulation results show that the proposed method has given better solution than the existing algorithm.

References

[1]. Agalgaonkar, A. P., Kulkarni, S. V., Khaparde, S. A., & Soman, S. A. (2004). Placement and penetration of distributed generation under standard market design. International Journal of Emerging Electric Power Systems, 1(1), 1-16.

[2]. Ahmadigorji, M., Abbaspour, A., Rajabi-Ghahnavieh, A., & Fotuhi-Firuzabad, M. (2009). Optimal DG placement in distribution systems using cost/worth analysis. World Academy of Science, Engineering and Technology, 49, 746-753.

[3]. Asakura, T., Yura, T., Hayashi, N., & Fukuyama, Y. (2000). Long-term distribution network expansion planning considering multiple construction plans. In Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on (Vol. 2, pp. 1101- 1106). IEEE.

[4]. Celli, G., Ghiani, E., Mocci, S., & Pilo, F. (2005). A multiobjective evolutionary algorithm for the sizing and siting of distributed generation. IEEE Transactions on Power Systems, 20(2), 750-757.

[5]. Connolly, D., Lund, H., Mathiesen, B. V., & Leahy, M. (2010). A review of computer tools for analysing the integration of renewable energy into various energy systems. Applied Energy, 87(4), 1059-1082.

[6]. Das, D. (2006). A fuzzy multiobjective approach for network reconfiguration of distribution systems. IEEE Transactions on Power Delivery, 21(1), 202-209.

[7]. Dugan, R. C., McDermott, T. E., & Ball, G. J. (2001). Planning for distributed generation. IEEE Industry Applications Magazine, 7(2), 80-88.

[8]. El-Khattam, W., Bhattacharya, K., Hegazy, Y., & Salama, M. M. A. (2004). Optimal investment planning for distributed generation in a competitive electricity market. IEEE Transactions on Power Systems, 19(3), 1674-1684.

[9]. El-Khattam, W., Hegazy, Y. G., & Salama, M. M. A. (2005). An integrated distributed generation optimization model for distribution system planning. IEEE Transactions on Power Systems, 20(2), 1158-1165.

[10]. Favuzza, S., Graditi, G., Ippolito, M. G., & Sanseverino, E. R. (2007). Optimal electrical distribution systems reinforcement planning using gas micro turbines by dynamic ant colony search algorithm. IEEE Transactions on Power Systems, 22(2), 580-587.

[11]. Hedayati, H., Nabaviniaki, S. A., & Akbarimajd, A. (2008). A method for placement of DG units in distribution networks. IEEE Transactions on Power Delivery, 23(3), 1620- 1628.

[12]. Jurado, F., & Cano, A. (2006). Optimal placement of biomass fuelled gas turbines for reduced losses. Energy Conversion and Management, 47(15), 2673-2681.

[13]. Kim, J. O., Nam, S. W., Park, S. K., & Singh, C. (1998). Dispersed generation planning using improved Hereford ranch algorithm. Electric Power Systems Research, 47(1), 47-55.

[14]. Lam, H. L., Varbanov, P. S., & Klemeš, J. J. (2011). Regional renewable energy and resource planning. Applied Energy, 88(2), 545-550.

[15]. Manfren, M., Caputo, P., & Costa, G. (2011). Paradigm shift in urban energy systems through distributed generation: Methods and models. Applied Energy, 88(4), 1032-1048.

[16]. Nara, K., Hayashi, Y., Ikeda, K., & Ashizawa, T. (2001). Application of tabu search to optimal placement of distributed generators. In Power Engineering Society Winter Meeting, 2001. IEEE (Vol. 2, pp. 918-923). IEEE.

[17]. Philipson, L. (2000). Distributed and dispersed generation: Addressing the spectrum of consumer needs. In Power Engineering Society Summer Meeting, 2000. IEEE (Vol. 3, pp. 1663-1665). IEEE.

[18]. Prakash, K., & Sydulu, M. (2007, June). Particle Swarm Optimization based capacitor placement on radial distribution systems. In Power Engineering Society General Meeting, 2007. IEEE (pp. 1-5). IEEE.

[19]. Rau, N.S., Wan, Y.H. Optimal location of resources in distributed planning. IEEE Transactions on Power Systems, 9(4), 2014-2020.

[20]. Sedighizadeh, M., & Rezazadeh, A. (2008). Using genetic algorithm for distributed generation allocation to reduce losses and improve voltage profile. World Academy of Science, Engineering and Technology, 37(1), 251-256.

[21]. Senjyu, T., Miyazato, Y., Yona, A., Urasaki, N., & Funabashi, T. (2008). Optimal distribution voltage control and coordination with distributed generation. IEEE Transactions on Power Delivery, 23(2), 1236-1242.

[22]. Sweet, W. (2001). Networking assets [distributed generation]. IEEE Spectrum, 38(1), 84-86.

[23]. Thomas, A., Anderson, G., Soder, L. (2003). Distributed generation: A definition. Electric Power Systems Research, 57(3), 195-204.

[24]. Teng, J. H., Liu, Y. H., Chen, C. Y., & Chen, C. F. (2007). Value-based distributed generator placements for service quality improvements. International Journal of Electrical Power & Energy Systems, 29(3), 268-274.

[25]. Wang, C., & 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.

[26]. Zhou, Y., Wang, L., & McCalley, J. D. (2011). Designing effective and efficient incentive policies for renewable energy in generation expansion planning. Applied Energy, 88(6), 2201-2209.

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Research Paper

Need for Reactive Power Optimization in Deregulated Power System

Varaprasad Janamala* , K. Chandra Sekhar**

* Assistant Professor, Department of Electrical and Electronics Engineering, Faculty of Engineering, Christ University, Karnataka, India.

** Professor and Head, Department of Electrical and Electronics Engineering, RVR & JC College of Engineering, Andhra Pradesh, India.

Janamala, V., and Koritala, C. S. (2017). Need for Reactive Power Optimization in Deregulated Power System. i-manager’s Journal on Power Systems Engineering, 5(2), 19-25. https://doi.org/10.26634/jps.5.2.13619

Abstract

The application of competitive market principles to the operation of power systems has resulted in stability margins being reduced to responding market pressures, which demand greater attention to reduced operating costs. As the overall stability limits can be closely associated with the voltage stability of the network, the incorporation of voltage collapse criteria and tools in the operation of power systems is becoming an essential part of new energy management systems. The possibility of uncertainties incidence in power system operation cannot be avoided in security studies. The load withdrawals and generation schedule are unpredictable in the market environment. In addition, the contingencies cause to reduce security margins further. In this paper, with the help of an illustrative example, the generation schedule, the importance of proper generator excitation, and how it will impact on reactive power control from a source is explored.

References

[1]. Ajjarapu, V., Lau, P. L., & Battula, S. (1994). An optimal reactive power planning strategy against voltage collapse. IEEE Transactions on Power Systems, 9(2), 906- 917.

[2]. Arabi, S., & Kundur, P. (1996). A versatile facts device model for powerflow and stability simulations. IEEE Transactions on Power Systems, 11(4), 1944-1950.

[3]. Chen, Y. L. (1996). Weak bus-oriented optimal multiobjective VAR planning. IEEE Transactions on Power Systems, 11(4), 1885-1890.

[4]. Federal Energy Regulatory Commission. Retrieved from www.ferc.gov

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[6]. Gomez, T., Perez-Arriaga, I. J., Lumbreras, J., & Parra, V. M. (1991). A security-constrained decomposition approach to optimal reactive power planning. IEEE Transactions on Power Systems, 6(3), 1069-1076.

[7]. Gotham, D. J., & Heydt, G. T. (1998). Power flow control and power flow studies for systems with FACTS devices. IEEE Transactions on Power Systems, 13(1), 60-65.

[8]. Granville, S., & Lima, M. A. (1994). Application of decomposition techniques to VAr planning: Methodological and computational aspects. IEEE Transactions on Power Systems, 9(4), 1780-1787.

[9]. Mansour, Y., Xu, W., Alvarado, F., & Rinzin, C. (1993, May). SVC placement using critical modes of voltage instability. In Power Industry Computer Application Conference, 1993. Conference Proceedings (pp. 131- 137). IEEE.

[10]. Miller, T. J. E. (1982). Reactive Power Control in Electric Systems. Wiley.

[11]. Mínguez, R., Milano, F., Zárate-Miñano, R., & Conejo, A. J. (2007). Optimal network placement of SVC devices. IEEE Transactions on Power Systems, 22(4), 1851- 1860.

[12]. Overbye, T. J., & De Marco, C. L. (1991). Voltage security enhancement using energy based sensitivities. IEEE Transactions on Power Systems, 6(3), 1196-1202.

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[14]. Rosehart, W. (2002). Optimal power flows incorporating network stability. In Power Engineering Society Winter Meeting, 2002. IEEE (Vol. 2, pp. 1100- 1104). IEEE.

[15]. Singh, A., Bapat, J., & Das, D. (2013, August). Vulnerability analysis of power grid network against failures by state classification. In Electrical Power & Energy Conference (EPEC), 2013 IEEE (pp. 1-6). IEEE.

[16]. Singh, J. G., Singh, S. N., & Srivastava, S. C. (2007). An approach for optimal placement of static VAr compensators based on reactive power spot price. IEEE Transactions on Power systems, 22(4), 2021-2029.

[17]. Taylor, C. W., Scott, G., & Hammad, A. (1994). Static VAr compensator models for power flow and dynamic performance simulation. IEEE Transactions on Power Systems, 9(1),229-240.

[18]. Vaahedi, E., Tamby, J., Mansour, Y., Li, W., & Sun, D. (1999). Large scale voltage stability constrained optimal VAr planning and voltage stability applications using existing OPF/optimal VAr planning tools. IEEE Transactions on Power Systems, 14(1), 65-74.

[19]. Wikipedia. Power Outage. Retrieved from https://en.wikipedia.org/wiki/Power_outage

[20]. Wood, A. J., & Wollenberg, B. F. (2012). Power Generation, Operation, and Control. John Wiley & Sons.

[21]. Yorino, N., El-Araby, E. E., Sasaki, H., & Harada, S. (2003). A new formulation for FACTS allocation for security enhancement against voltage collapse. IEEE Transactions on Power Systems, 18(1), 3-10.

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Research Paper

Determination of Maximum Loading Condition using Homotopy Continuation Method

Kiran Babu* , CH. Rambabu**

* PG Scholar, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India.

** Professor, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India.

Babu, K. K., and Ch. Rambabu. (2017). Determination of Maximum Loading Condition using Homotopy Continuation Method. i-manager’s Journal on Power Systems Engineering, 5(2), 26-34. https://doi.org/10.26634/jps.5.2.13621

Abstract

In this paper, a method for calculating the power systems' P-V curves, which denote the relation between the total load and the system voltage has been presented. The method used is Homotopy Continuation Method which does not use the traditional cut-and-try process and/or a rough approximation process. The load flow calculation process is based on the Newton-Raphson method, but does not suffer from the notorious numerical calculations. The critical load condition can be obtained by increasing the load/generation by parameter 't'. This parameter handles the change in the real and reactive power directly. Not only the critical loading point, but also the P-V curve can be obtained which provides visual information to the system planers and system operators [5].

References

[1]. Bourgin, F., Testud, G., Heilbronn, B., & Verseille, J. (1993). Present practices and trends on the French power system to prevent voltage collapse. IEEE Transactions on Power Systems, 8(3), 778-788.

[2]. Chiang, H. D., Flueck, A. J., Shah, K. S., & Balu, N. (1995). CPFLOW: A practical tool for tracing power system steady-state stationary behavior due to load and generation variations. IEEE Transactions on Power Systems, 10(2), 623-634.

[3]. DeMarco, C. L. (1986). A Large Deviations Model for Voltage Collapse in Electrical Power Systems. In Proc. of IEEE International Symposium on Circuits and Systems.

[4]. Ghiocel, S. G., & Chow, J. H. (2014). A power flow method using a new bus type for computing steady-state voltage stability margins. IEEE Transactions on Power Systems, 29(2), 958-965.

[5]. Iba, K., Suzuki, H., Egawa, M., & Watanabe, T. (1991). Calculation of critical loading condition with nose curve using homotopy continuation method. IEEE Transactions on Power Systems, 6(2), 584-593.

[6]. Kessel, P., & Glavitsch, H. (1986). Estimating the voltage stability of a power system. IEEE Transactions on Power Delivery, 1(3), 346-354.

[7]. Kothari, D. P., & Nagrath, I. J. (2011). Modern Power System Analysis. Tata McGraw-Hill Edition.

[8]. Powell, L. (2004). Power System Load Flow Analysis. Tata McGraw Hill Edition.

[9]. Saadat, H., (2002). Power System Analysis. Tata McGraw-Hill Edition.

[10]. Stott, B. (1974). Review of load-flow calculation methods. Proceedings of the IEEE, 62(7), 916-929.

[11]. Taylor, C. W. (1994). Power System Voltage Stability. McGraw-Hill.

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Research Paper

Reactive Power Compensation of Standalone Self Excited Induction GeneratorUsing DSTATCOM

K. Mahammad Rafi* , Anam Fatima, P.V.N. Prasad*

* Assistant Professor, Department of Electrical and Electronics Engineering, Muffakham Jah College of Engineering and Technology, Banjara Hills, Hyderabad, India.

PG Scholar, Department of Electrical and Electronics Engineering, Muffakham Jah College of Engineering and Technology, Banjara Hills, Hyderabad, India.

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

Rafi, K. M., Fatima, A., and Prasad, P. V. N. (2017). Reactive Power Compensation of Standalone Self Excited Induction Generator using DSTATCOM. i-manager’s Journal on Power Systems Engineering, 5(2), 35-42. https://doi.org/10.26634/jps.5.2.13623

Abstract

This paper presents the control of a self-excited Induction Generator using DSTATCOM. The performance of the DSTATCOM depends on the extraction of the reference source currents. For this purpose, the control strategy adopted is IRP theory, which is implemented using MATLAB/Simulink. Generation of the PWM pulses triggers the IGBT of the VSI based DSTATCOM. This is achieved using Arduino Due, a 32 bit ARM core microcontroller interfaced with MATLAB/Simulink. The performance of the SEIG is analyzed experimentally in a hardware prototype to evaluate the effect of DSTATCOM. It is observed that SEIG with DSTATCOM provides voltage sag mitigation, reactive power compensation, and power factor improvement.

References

[1]. Azmi, M. A. M., Daniyal, H., & Bakar, M. S. (2015). Realization of Three-Phase Voltage Source Inverter Controller using ARM Cortex-M3. International Journal of Energy and Power Engineering Research, 2(1), 1-5.

[2]. Ghosh, A., & Ledwich, G. (2012). Power Quality Enhancement using Custom Power Devices. Springer Science & Business Media.

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

[4]. Kasimvali. A., & Rao, J. S. (2012). Modeling and Simulation of SRF and P-Q based Control DSTATCOM. International Journal of Engineering Research and Development, 1(10), 65-71.

[5]. Kumar, C., & Mishra, M. K. (2015). Operation and control of an improved performance interactive DSTATCOM. IEEE Transactions on Industrial Electronics, 62(10), 6024-6034.

[6]. Mahyavanshi, A., Mulla, M. A., & Chudamani, R. (2012). Reactive power compensation by controlling the DSTATCOM. International Journal of Emerging Technology and Advanced Engineering, 2(11), 212-218.

[7]. Mrunalini, C., & Mahajan, S. S. (2016). Implementation of STATCOM-based Three Phase VSI Inverter for Voltage Regulation of Three Phase SEIG. International Journal of Innovative Research in Science, Engineering and Technology, 5(6), 9931-9939.

[8]. Singh, B., & Arya, S. R. (2012). Design and control of a DSTATCOM for power quality improvement using cross correlation function approach. International Journal of Engineering, Science and Technology, 4(1), 74-86.

[9]. Singh, B., & Solanki, J. (2009). A comparison of control algorithms for DSTATCOM. IEEE Transactions on Industrial Electronics, 56(7), 2738-2745.

[10]. Swapna, G., Bindu, H.V., Chakravarthy, M., & Sarma, P. M. (2013). Hardware Implementation of a Single Phase Inverter. International Journal of Engineering Trends and Technology (IJETT), 4(8), 3582-3585.

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Review Paper

A Review on MPPT Methods for ZSI based Photovoltaic Power Conversion System under Partial Shading Conditions

N. Satyavani* , N. Visali**

* Research Scholor, Department of Electrical and Electronics Engineering, MITS, Madanapalle, India.

** Vice Principal & Head, Department of Electrical and Electronics Engineering, JNTUCEP, Kalikiri, India.

Satyavani, N., and Visali, N. (2017). A Review on MPPT Methods for ZSI based Photovoltaic Power Conversion System under Partial Shading Conditions . i-manager’s Journal on Power Systems Engineering, 5(2), 43-52. https://doi.org/10.26634/jps.5.2.13624

Abstract

This paper communicates a comprehensive review of different Maximum Power Point Tracking (MPPT) methods of solar photovoltaic systems for Partial Shading Conditions (PSCs) when interconnected to the grids/micro-grids/AC loads through impedance source inverter and a brief survey on control methods of Z Source Inverter (ZSI) is discussed in detail. The proposed methods are compared with traditional methods like Perturb & Observation, Incremental Conductance (INC) methods under Partial Shading Conditions. The selected methods are classified as Modified Conventional methods, Soft Computing methods, and other MPPT methods. This comparison reveals that researchers are able to concentrate on shading conditions and enhance the performance of solar photovoltaic system for end users.

References

[1]. Ali, U. S., & Kamaraj, V. (2011, January). A novel space vector PWM for Z-Source Inverter. In Electrical Energy Systems (ICEES), 2011 1^st International Conference on (pp. 82-85). IEEE.

[2]. Chen, Z., Zhang, X., & Pan, J. (2007). An integrated inverter for a single-phase single-stage grid-connected PV system based on Z-Source. Bull. Pol. Ac.: Tech, 55(3), 263-272.

[3]. Erdinc, O., & Uzunoglu, M. (2012). Optimum design of hybrid renewable energy systems: Overview of different approaches. Renewable and Sustainable Energy Reviews, 16(3), 1412-1425.

[4]. Fermia, N., Granozio, D., Petrone, G., & Vitelli, M. (2007). Predictive & adaptive MPPT Perturb and Observe method. IEEE Transactions on Aerospace and Electronic Systems, 43(3), 934-950.

[5]. Liu, L. Q., Liu, C. X., & Wang, J. S. (2013). Deliberating on renewable and sustainable energy policies in China. Renewable and Sustainable Energy Reviews, 17(1), 191- 198.

[6]. Liu, L., Liu, C., Wang, J., & Kong, Y. (2015). Simulation and hardware implementation of a hill-climbing modified fuzzy-logic for maximum power point tracking with direct control method using boost converter. Journal of Vibration and Control, 21(2), 335-342.

[7]. Liu, Y., Ge, B., Abu-Rub, H., & Peng, F. Z. (2014). Overview of space vector modulations for three-phase ZSource/ Quasi-Z-Source Inverters. IEEE Transactions on Power Electronics, 29(4), 2098-2108.

[8]. Liu, Y., Ge, B., Ferreira, F. J., de Almeida, A. T., & Abu- Rub, H. (2011, October). Modeling and SVPWM control of quasi-Z-source inverter. In Electrical Power Quality and Utilisation (EPQU), 2011 11^th International Conference on (pp. 1-7). IEEE.

[9]. Manna, T. K., & Mahajan, S. M. (2007, May). Nanotechnology in the development of photovoltaic cells. In Clean Electrical Power, 2007. ICCEP'07. International Conference on (pp. 379-386). IEEE.

[10]. Miyatake, M., Veerachary, M., Toriumi, F., Fujii, N., & Ko, H. (2011). Maximum power point tracking of multiple photovoltaic arrays: A PSO approach. IEEE Transactions on Aerospace and Electronic Systems, 47(1), 367-380.

[11]. Patel, H., & Agarwal, V. (2008). Maximum Power Point Tracking scheme for PV systems operating under partially shaded conditions. IEEE Transactions on Industrial Electronics, 55(4), 1689-1698.

[12]. Peng, F. Z. (2003). Z-Source Inverter. IEEE Transactions on Industry Applications, 39(2), 504-510.

[13]. Peng, F. Z., Shen, M., & Qian, Z. (2005). Maximum boost control of the Z-source inverter. IEEE Transactions on Power Electronics, 20(4), 833-838.

[14]. Rostami, H., & Khaburi, D. A. (2009, November). Voltage gain comparison of different control methods of the Z-source inverter. In Electrical and Electronics Engineering, 2009. ELECO 2009. International Conference on (pp. I-268). IEEE.

[15]. Safari, A., & Mekhilef, S. (2011). Simulation and hardware implementation of incremental conductance MPPT with direct control method using cuk converter. IEEE Transactions on Industrial Electronics, 58(4), 1154-1161.

[16]. Singh, G. K. (2013). Solar power generation by PV (photovoltaic) technology: A review. Energy, 53, 1-13.

[17]. Tang, Y., Xie, S., & Ding, J. (2014). PulseWidth Modulation of Z-Source Inverters with minimum inductor current ripple. IEEE Transactions on Industrial Electronics, 61(1), 98-106.

[18]. Tyagi, V. V., Rahim, N. A., Rahim, N. A., Jeyraj, A., & Selvaraj, L. (2013). Progress in solar PV technology: Research and achievement. Renewable and Sustainable Energy Reviews, 20, 443-461.

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

Current Issue Vol. 11 Issue 3

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Volume 5 Issue 2 May - July 2017

Modelling of Integrated Recycle Heat Exchangers

David D. Biruk* , Chiu Choi**, John Kang***

Biruk, D. D., Choi, C., and Kang, J. (2017). Modelling of Integrated Recycle Heat Exchangers. i-manager’s Journal on Power Systems Engineering, 5(2), 1-9. https://doi.org/10.26634/jps.5.2.13617

Abstract

References

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A Two Stage Optimal Sitting and Sizing of Multiple Distributed Generators byImproved Teaching and Learning Optimization Algorithm

G. Balakrishna*

*Professor, Department of Electrical and Electronics Engineering, Sreenivasa Ramanujan Institute of Technology, Anantapuramu, India.

Balakrishna, G. (2017). A Two Stage Optimal Sitting and Sizing of Multiple Distributed Generators by Improved Teaching and Learning Optimization Algorithm i-manager’s Journal on Power Systems Engineering, 5(2), 10-18. https://doi.org/10.26634/jps.5.2.13618

Abstract

References

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Need for Reactive Power Optimization in Deregulated Power System

Varaprasad Janamala* , K. Chandra Sekhar**

* Assistant Professor, Department of Electrical and Electronics Engineering, Faculty of Engineering, Christ University, Karnataka, India. ** Professor and Head, Department of Electrical and Electronics Engineering, RVR & JC College of Engineering, Andhra Pradesh, India.

Janamala, V., and Koritala, C. S. (2017). Need for Reactive Power Optimization in Deregulated Power System. i-manager’s Journal on Power Systems Engineering, 5(2), 19-25. https://doi.org/10.26634/jps.5.2.13619

Abstract

References

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Determination of Maximum Loading Condition using Homotopy Continuation Method

Kiran Babu* , CH. Rambabu**

* PG Scholar, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India. ** Professor, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India.

Babu, K. K., and Ch. Rambabu. (2017). Determination of Maximum Loading Condition using Homotopy Continuation Method. i-manager’s Journal on Power Systems Engineering, 5(2), 26-34. https://doi.org/10.26634/jps.5.2.13621

Abstract

References

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Reactive Power Compensation of Standalone Self Excited Induction GeneratorUsing DSTATCOM

K. Mahammad Rafi* , Anam Fatima**, P.V.N. Prasad***

Rafi, K. M., Fatima, A., and Prasad, P. V. N. (2017). Reactive Power Compensation of Standalone Self Excited Induction Generator using DSTATCOM. i-manager’s Journal on Power Systems Engineering, 5(2), 35-42. https://doi.org/10.26634/jps.5.2.13623

Abstract

References

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A Review on MPPT Methods for ZSI based Photovoltaic Power Conversion System under Partial Shading Conditions

N. Satyavani* , N. Visali**

* Research Scholor, Department of Electrical and Electronics Engineering, MITS, Madanapalle, India. ** Vice Principal & Head, Department of Electrical and Electronics Engineering, JNTUCEP, Kalikiri, India.

Satyavani, N., and Visali, N. (2017). A Review on MPPT Methods for ZSI based Photovoltaic Power Conversion System under Partial Shading Conditions . i-manager’s Journal on Power Systems Engineering, 5(2), 43-52. https://doi.org/10.26634/jps.5.2.13624

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David D. Biruk* , Chiu Choi, John Kang*

* Assistant Professor, Department of Electrical and Electronics Engineering, Faculty of Engineering, Christ University, Karnataka, India.

** Professor and Head, Department of Electrical and Electronics Engineering, RVR & JC College of Engineering, Andhra Pradesh, India.

* PG Scholar, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India.

** Professor, Department of Electrical & Electronics Engineering, Sri Vasavi Engineering College, Andhra Pradesh, India.

K. Mahammad Rafi* , Anam Fatima, P.V.N. Prasad*

* Research Scholor, Department of Electrical and Electronics Engineering, MITS, Madanapalle, India.

** Vice Principal & Head, Department of Electrical and Electronics Engineering, JNTUCEP, Kalikiri, India.