i-manager Publications

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

Current Issue Vol. 12 Issue 1

Thermodynamic and Exergoeconomic Operation Optimization and Simulation of Steam Generation Solar Power Plant
Topology Transformation Approach for Optimal PMU Placement for Monitoring and Control of Power System
Performance Evaluation of Power System with HVDC Integration: Impact of SSSC and STATCOM on Power System Efficiency and Stability
Photovoltaic Systems: A Pollination-Based Optimization Approach for Critical Industrial Applications
Design of a Robust Controller for the Load Frequency Control of Interconnected Power System

Most Cited

Volume 5 Issue 1 February - April 2017

Research Paper

Effect of System Topology on Wind Generators Penetration Maximizationwith TCSCs Insertion

Almoataz Y. Abdelaziz* , Metwally A. El-Sharkawy, Mahmoud Abdallah Attia*

* Professor, Department of Electrical Power Engineering, Ain Shams University, Cairo, Egypt.

Emeritus Professor, Department of Electric Power Engineering, Ain Shams University Cairo, Egypt.

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

Abdelaziz, Y. A., El-Sharkawy, A. M., and Attia, A. M. (2017). Effect of System Topology on Wind Generators Penetration Maximization with TCSCs Insertion. i-manager’s Journal on Power Systems Engineering, 5(1), 1-9. https://doi.org/10.26634/jps.5.1.13532

Abstract

Wind generation penetration maximizing is an important issue in power systems. These increasing in wind penetration may badly affect the power system stability. In this paper, Thyristor-Controlled Series Compensation (TCSCs) devices are used to help wind penetration maximizing and also for studying the effect of system topology in that. Cases studied are carried out on modified IEEE 39 bus system with variable speed wind generator penetration increases by 50%, 100%, 150% and 170%. In each case of wind penetration increases, three cases in the system are tried, system without change, system with reduction of the impedance of the lines connected to wind generator by 50%, and change the location of wind generator to another location has more interconnection. Another case study is carried out on modified IEEE 39 bus system with fixed speed wind generator penetration increases by 50%, 100% and 150% respective of its generation. The system suffers from some violation in its parameters. Results found that series TCSCs devices in certain range are able to maximize wind penetration in power systems without violation in its indices.

References

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[2]. Abdelaziz, A. Y., El-Sharkawy, M. A., & Attia, M. A. (2013). Comparison of series and shunt FACTS to improve the performance of power system with wind penetration. International Journal of Advances in Power Systems, 1(2), 2335-1772.

[3]. Abdelaziz, A. Y., El-Sharkawy, M. A., & Attia, M. A. (2014, December). Optimal Location of FACTS Devices to Reduce Wind Variation Effect on Power System. Proceedings of the Sixteenth International Middle East Power Systems Conference, Ain Shams University, Cairo, Egypt, (MEPCON'14).

[4]. Abdelaziz, A. Y., El-Sharkawy, M. A., & Attia, M. A. (2015). Optimal location of thyristor-controlled series compensation and static VAR compensator to enhance steady-state performance of power system with wind penetration. Electric Power Components and Systems, 43(18), 1999-2009.

[5]. Abdelaziz, A. Y., El-Sharkawy, M. A., Attia, M. A., & El- Saadany, E. F. (2014, July). Optimal location of series FACTS to improve the performance of power system with wind penetration. In PES General Meeting| Conference & Exposition, 2014 IEEE (pp. 1-5). IEEE.

[6]. Abdelaziz, A. Y., El-Sharkawy, M. A., Attia, M. A., & Panigrahi, B. K. (2012, December). Genetic algorithm based approach for optimal allocation of TCSC for power system loadability enhancement. In International Conference on Swarm, Evolutionary, and Memetic Computing (pp. 548-557). Springer, Berlin, Heidelberg.

[7]. Adamczyk, A., Teodorescu, R., Mukerjee, R. N., & Rodriguez, P. (2010, July). Overview of FACTS devices for wind power plants directly connected to the transmission network. In Industrial Electronics (ISIE), 2010 IEEE International Symposium on (pp. 3742-3748). IEEE.

[8]. Altin, M., Göksu, Ö., Teodorescu, R., Rodriguez, P., Jensen, B. B., & Helle, L. (2010, May). Overview of recent grid codes for wind power integration. In Optimization of th Electrical and Electronic Equipment (OPTIM), 2010 12 International Conference on (pp. 1152-1160). IEEE.

[9]. Bagnall, T., Ritter, C., Ronner, B., Maibach, P., Butcher, N., & Thurnherr, T. (2009). PCS6000 STATCOM ancillary functions: Wind park resonance damping. EWEC 2009.

[10]. Baran, M. E., Teleke, S., Anderson, L., Huang, A., Bhattacharya, S., & Atcitty, S. (2008, July). STATCOM with energy storage for smoothing intermittent wind farm power. In Power and Energy Society General Meetingwind Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE (pp. 1-6). IEEE.

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[15]. Han, C., Huang, A. Q., Baran, M. E., Bhattacharya, S., Litzenberger, W., Anderson, L., et al. (2008). STATCOM impact study on the integration of a large wind farm into a weak loop power system. IEEE Transactions on Energy Conversion, 23(1), 226-233.

[16]. Jayam, A. P., & Chowdhury, B. H. (2009, March). Improving the dynamic performance of wind farms with STATCOM. In Power Systems Conference and Exposition, 2009. PSCE'09. IEEE/PES (pp. 1-8). IEEE.

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[18]. Meikandasivam, S., Nema, R. K., & Jain, S. K. (2008). Behavioral Study of TCSC Device–A MATLAB/Simulink Implementation. World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, 2(9), 1958-1963.

[19]. Panda, R., Kumar Satpathy, P., & Paul, S. (2011). Application of SVC to mitigate voltage instability in a Wind system connected with GRID. International Journal of Power System Operation and Energy Management (IJPSOEM), 1, 90-96.

[20]. Qi, L., Langston, J., & Steurer, M. (2008, July). Applying a STATCOM for stability improvement to an existing wind farm with fixed-speed induction generators. In Power and Energy Society General Meetingst Conversion and Delivery of Electrical Energy in the 21 Century, 2008 IEEE (pp. 1-6). IEEE.

[21]. Qiao, W., Harley, R. G., & Venayagamoorthy, G. K. (2009a). Coordinated reactive power control of a large wind farm and a STATCOM using heuristic dynamic programming. IEEE Transactions on Energy Conversion, 24(2), 493-503.

[22]. Qiao, W., Venayagamoorthy, G. K., & Harley, R. G. (2009b). Real-time implementation of a STATCOM on a wind farm equipped with doubly fed induction generators. IEEE Transactions on Industry Applications, 45(1), 98-107.

[23]. Saravanan, M., Slochanal, S. M. R., Venkatesh, P., & Abraham, J. P. S. (2007). Application of particle swarm optimization technique for optimal location of FACTS devices considering cost of installation and system loadability. Electric Power Systems Research, 77(3), 276- 283.

[24]. Visiers, M., Mendoza, J., Búnez, J., González, F., Contreras, A., Molina, S., & Agudo, A. (2007, September). WINDFACT®, a solution for the grid code compliance of the windfarms in operation. In Power Electronics and Applications, 2007 European Conference on (pp. 1-9). IEEE.

[25]. Zhang, X. P., Rehtanz, C., & Pal, B. (2006). Flexible AC Transmission Systems: Modelling and Control. Springer Science & Business Media.

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Research Paper

A Novel Loss Distribution Strategy after Removing Slack Bus using ImprovedKinetic Gas Molecules Optimization Algorithm

D. Srilatha* , Sivanagaraju Sirigiri**

* Associate Professor, Department of Electrical and Electronics Engineering, Prakasam Engineering College, Kandukur, A.P., India.

** Professor, Department of Electrical and Electronics Engineering, University College of Engineering, JNTU Kakinada, Kakinada, A.P., India.

Srilatha, D., and Sivanagaraju, S. (2017). A Novel Loss Distribution Strategy after Removing Slack Bus using Improved Kinetic Gas Molecules Optimization Algorithm. i-manager’s Journal on Power Systems Engineering, 5(1), 10-25. https://doi.org/10.26634/jps.5.1.13533

Abstract

The modern power system analysis, operation and control use pneumatic solution methodologies to solve more realistic power system problems to enhance the operational aspects of power systems. The conventional load flow methods work independent of economic and environmental aspects and allocates total power losses to slack bus which increases the burden on this generator. In this paper, a novel methodology to remove extra generation by the slack and to optimize the system operation in economic and environmental aspects is presented. Further, a new hybrid optimization algorithm namely Improved Kinetic Gas Molecules Optimization (IKGMO) is presented to solve Optimal Power Flow (OPF) problem while satisfying system equality and inequality constraints. The effectiveness of optimization over the conventional load flow in loss allocation is tested on standard IEEE-14 bus and IEEE-30 bus test systems with supporting numerical and graphical results.

References

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[5]. Coelho, L. D. S., Bora, T. C., & Mariani, V. C. (2014). Differential evolution based on truncated Lévy-type flights and population diversity measure to solve economic load dispatch problems. International Journal of Electrical Power and Energy Systems, 57(1), 178-188.

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[13]. Moein, S., & Logeswaran, R. (2014). KGMO: A swarm optimization algorithm based on the kinetic energy of gas molecules. Information Sciences, 275, 127-144.

[14]. Niknam, T., Narimani, M. R., Aghaei, J., & Azizipanah-Abarghooee, R. (2012). Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index. IET Generation, Transmission & Distribution, 6(6), 515-527.

[15]. Niknam, T., Narimani, M. R., Jabbari, M., & Malekpour, A. R. (2011). A modified shuffle frog leaping algorithm for multi-objective optimal power flow. Energy, 36(11), 6420-6432.

[16]. Okamura, M., O-ura, Y., Hayashi, S., Uemura, K., & Ishiguro, F. (1975). A new power flow model and solution method?Including load and generator characteristics and effects of system control devices. IEEE Transactions on Power Apparatus and Systems, 94(3), 1042-1050.

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[20]. Shin, J. R., & Yim, H. S. (1993, October). An extended approach for NR load flow with power loss correction method. In TENCON'93 Proceedings. Computer, Communication, Control and Power Engineering. 1993 IEEE Region 10 Conference on (Vol. 5, pp. 402-405). IEEE.

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Research Paper

Optimization of Hybrid Renewable Energy Systems for Sustainable andEconomical Power Supply at SVCET Chittoor

Suresh Vendoti* , 0, R. Kiranmayi*

* Research Scholar, Department of Electrical and Electronics Engineering, SVCET, Chittoor, India.

Director and Professor, Department of Electrical and Electronics Engineering, SVCET, Chittoor, India.

* Professor and Head, Department of Electrical and Electronics Engineering, JNTUA, Anantapuramu, India.

Vendoti, S., Muralidhar, M. and Kiranmayi, R. (2017). Optimization of Hybrid Renewable Energy Systems for Sustainable and Economical Power Supply at SVCET Chittoor. i-manager’s Journal on Power Systems Engineering, 1(1), 26-34. https://doi.org/10.26634/jps.5.1.13534

Abstract

Nowadays, the rising energy demand and the limited reserves of the conventional sources have raised the concerns of the researchers all around the globe to look for alternative resources. In addition to the increasing demand concerns, the environmental concerns have led to the emergence of green power technologies in the energy sector. Green power technologies include the power generation from clean and inexhaustible sources of solar energy, wind energy, hydro, biomass, etc. The main point of consideration, while designing the hybrid system, is the sizing of different components.

In this paper, a methodology has been developed for optimal planning of hybrid PV-Wind system with some battery backup. The local solar radiation, wind data and components database from different manufacturers are analyzed and simulated in Hybrid Optimization Model for Electric Renewable (HOMER) to assess the technical and economic viability of the integrated system. The system architecture, includes SUKAM PV System 200 KW, 10 number of Generic 10 kW Wind Generators, POWERICA Diesel Generator 250 KW, Battery Trojan IND17-6V model (6 V, 7.61kwh), and Converter 30 KW. This paper gives the design idea of optimized PV-Solar and Wind Hybrid Energy System for Sri Venkateswara College of Engineering and Technology (SVCET) at Chittoor, Electrical load over conventional electrical grid system for a particular site in South India (Chittoor). For this hybrid system, the meteorological data of Solar Insolation, hourly wind speed, are taken for Chittoor -South India (Latitude 13ο16.3'N and Longitude 79ο7.1'E) and the pattern of load consumption of SVCET electrical load data are studied and suitably modeled for optimization of the hybrid energy system using HOMER Pro 3.8.5 Software. This system is more cost effective and environmental friendly over the conventional grid system.

References

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[2]. Fulzele, J. B., & Dutt, S. (2012). Optimium planning of hybrid renewable energy system using HOMER. International Journal of Electrical and Computer Engineering, 2(1), 68.

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Review Paper

Computation of Available Transfer Capability in ElectricalTransmission System - A Review

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

* Research Scholar, Department of Electrical and Electronics Engineering, Visvesvaraya Technological University, Belgaum, India.

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

Sureban, S. M., and Ankaliki, S. G. (2017). Computation of Available Transfer Capability in Electrical Transmission System - A Review. i-manager’s Journal on Power Systems Engineering, 5(1), 35-39. https://doi.org/10.26634/jps.5.1.13535

Abstract

The increasing demand for electricity in the recent decades had resulted in several problems in the normal operation of the power system. The transmission lines are forced to operate near their limits; critical components are going out of service and also the efficiency of transmission lines is reducing. To address all these issues, evaluation of transfer capability of transmission lines is important. Many deterministic and probabilistic methods are available for evaluation of transfer capability of transmission lines. On computing the available transfer capability of power system, the efficiency of the transmission lines can be evaluated and congestion management in the system is also possible. By knowing the efficiency of existing transmission lines, necessary steps can be initiated to improve the same and hence to operate the entire system more reliably and economically. This paper aims at discussing the fundamentals of ATC computation and reviewing various technical papers related to the same.

References

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[3]. Ejebe, G. C., Waight, J. G., Sanots-Nieto, M., & Tinney, W. F. (2000). Fast calculation of linear Available Transfer Capability. IEEE Transactions on Power Systems, 15(3), 1112-1116.

[4]. Gao, Y., Zhou, M., & Yang, J. (2010, June). Available T r a n s f e r C a p a b i l i t y c a l c u l a t i o n b a s e d o n contingencyselection. In Industrial Electronics and Applications (ICIEA), 2010 the 5 IEEE Conference on (pp. 868-873). IEEE.

[5]. Hamoud, G. (2000). Assessment of available transfer capability of transmission systems. IEEE Transactions on Power Systems, 15(1), 27-32.

[6]. Hojabri, M., & Hizam, H. (2011). Available Transfer Capability Calculation. In Applications of MATLAB in Science and Engineering. InTech.

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[8]. Li, G., Sun, Y., & Li, X. (2009, April). Available Transfer Capability calculation considering amended thermal limits. In Sustainable Power Generation and Supply, 2009. SUPERGEN'09. International Conference on (pp. 1-7). IEEE.

[9]. Manohar, J. N., & Amarnath, J. (2012). Statistical analysis of power system on enhancement of available transfer capability-applying FACTS. Int. J. Multidiscip. Sci. Eng, 3(7), 33-37.

[10]. Ou, Y., & Singh, C. (2002). Assessment of available transfer capability and margins. IEEE Transactions on Power Systems, 17(2), 463-468.

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Survey Paper

A Survey on Demand Side Management In Electrical Power Systems

Ahmed M. Ibrahim* , Mahmoud Abdallah Attia, Mahmoud M. Othman*, Almoataz Y. Abdelaziz****

* Electrical Design Engineer, Engineering Consultants Group, Cairo, Egypt.

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

* Assistant Professor, Department of Electrical Power Engineering, Ain Shams University, Cairo, Egypt.

**** Professor, Department of Electrical Power Engineering, Ain Shams University, Cairo, Egypt.

Ibrahim, M. A., Attia, A. M., Othman, M. M., and Abdelaziz, Y. A. (2017). A Survey on Demand Side Management In Electrical Power Systems. i-manager’s Journal on Power Systems Engineering, 5(1), 40-50. https://doi.org/10.26634/jps.5.1.13536

Abstract

This paper presents a survey on Demand Side Management techniques used to reduce the energy waste, postpone the construction of new plants, reduce costs or electricity bill, and reduce total power demand during peak demand periods. One of the major goals of DSM is reducing consumption during peak hours and shifting load to off-peak hours. Several algorithms and techniques for load shifting have been reported in researches. Different approaches have been suggested to solve the demand response problem using linear and dynamic programming techniques. There are different types of optimization techniques as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Evolutionary Algorithm (EA), Game theoretic techniques and others. Researches are performed on different optimization techniques to reduce peak load demand, reduce operational cost, reduce PAR (Peak to Average Ratio), and reduce the discrepancy between power supply and demand.

References

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[4]. Awais, M., Javaid, N., Shaheen, N., Iqbal, Z., Rehman, G., Muhammad, K., & Ahmad, I. (2015, September). An efficient genetic algorithm based demand side management scheme for smart grid. In Network-Based Information Systems (NBiS), 2015 18 International Conference on (pp. 351-356). IEEE.

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