International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 11, No. 1, 8 Jan. 2019
Cover page and Table of Contents: PDF (size: 1698KB)
Optimized Controller Design Using an Adaptive Bacterial Foraging Algorithm for Voltage Control and Reactive Power Management in Off-Grid Hybrid Power System
Full Text (PDF, 1698KB), PP.33-43
Views: 0 Downloads: 0
Author(s)
Index Terms
Bacterial foraging Algorithm, voltage regulation, Off-grid hybrid power system
Abstract
This paper investigates the application of adaptive Bacteria Forging Algorithm (BFA) to design optimal controllers for voltage stability of off-grid hybrid power system (OGHPS).Voltage fluctuations will have great impact on the quality of power supply. Voltage rise/drop depends on the surplus / shortage of reactive power in the system, hence it has become extremely important to manage the reactive power balance for voltage control in the off-grid hybrid power system. The off -grid hybrid power system considered in this work as a test system, consist of an Induction generator (IG) for wind power systems, Photo-Voltaic (PV) system with inverter, Synchronous generator (SG) for diesel power generation and composite load. The Over-rated PV inverter has ample amount of reactive power capacity while sourcing PV real power. Two control structures are incorporated, to regulate system voltage. The first control structure is for the reactive power compensation of the system by inverter, by controlling the magnitude of inverter output voltage and the second control structure is for controlling the SG excitation by an automatic voltage regulator (AVR) and hence the load voltage. Both control structures have proportional-integral (PI) controller. Both control loops are coordinated by tuning their parameters optimally and simultaneously using an adaptive Bacterial forging optimization algorithm. Small signal model of all components of OGHPS is simulated in SIMULINK, tested for reactive load disturbance and /or wind power input disturbance of different magnitudes to investigate voltage stability.
Cite This Paper
Harsha Anantwar, B.R. Lakshmikantha, Shanmukha Sundar, "Optimized Controller Design Using an Adaptive Bacterial Foraging Algorithm for Voltage Control and Reactive Power Management in Off-Grid Hybrid Power System", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.1, pp. 33-43, 2019. DOI: 10.5815/ijigsp.2019.01.04
Reference
[1]J. Kaldellis et al, Stand-Alone and Hybrid Wind Energy Systems Technology, energy storage and applications, Woodhead Publishing Limited
[2]M. R. Patel, Wind and solar power system: Design, Analysis, and operation ,2nd Edition, CRC Press, Boca Raton, FL, USA, 2005
[3]HI. Mickal, “100 kW Photovoltaic Power Plant for Kythnos Island”, Proc. Of Fifth EC Photovoltaic Conference, Oct. 1983 pp. 490-494.
[4]R. C. Bansal, “Automatic Reactive-Power Control of Isolated Wind–Diesel Hybrid Power Systems”, IEEE Transactions on Industrial Electronics, VOL. 53, NO. 4, August 2006
[5]Sharma, P., Saxena, N. K., and Bhatti, T. S., “Study of autonomous hybrid power system using SVC and STATCOM,” Proceedings of ICPS 2009, Kharagpur, India, 27–29 December 2009.
[6]Jinning Liu,Li Zhang,Man Cao , “ Power management and synchronization control of renewable energy microgrid based on STATCOM ”, IEEE Conference and Expo on Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), 2014
[7]D. Menniti,A. Pinnarelli, N. Sorrentino, “ An hybrid PV-wind supply system with D-Statcom interface for a water-lift station ”, International Symposium on Power Electronics Electrical Drives Automation and Motion (SPEEDAM),June 2010
[8]Saxena Nitin K, Kumar Ashwani, “ Analytical comparison of static and dynamic reactive power compensation in isolated wind diesel system using dynamic load interaction model”, Electric Power Compon Syst 2014;53(5):508–19
[9]Vachirasricirikul, S., Ngamroo, I., Kaitwanidvilai, S, “Coordinated SVC and AVR for robust voltage control in a hybrid wind-diesel system”, Energy Convers. Manage., 2010, 51, (12), pp. 2383–2393
[10]Ahmed M. Kassem & Almoataz Y. Abdelaziz, “Functional Predictive Control for Voltage Stability Improvements of Autonomous Hybrid Wind–Diesel Power System”, Electric Power Components and Systems,42:8, pp 831-844, Harsha Anantwar, B R Lakshmikantha and Shanmukha Sundar,“Fuzzy self tuning PI controller based inverter control for voltage regulation in off-grid hybrid power system”, Elsevier ,Energy Procedia volume 117, 2017, pp 409- 416.
[11]Yuan Liao, Wen Fan, Aaron Cramer, Paul Dolloff, Zongming Fei, Meikang Qui, Siddhartha Bhattacharyya, Larry Holloway, Bob Gregory “, Voltage and Var Control to Enable High Penetration of Distributed Photovoltaic Systems”, North American Power Symposium (NAPS), 9-11 Sept.2012
[12]Wang Y, Shao H. Optimal tuning for PI controller. Automatica 2000;36:147–52.
[13]Zhuang, M., and D. P. Atherton Tuning of PID controllers with integral performance criteria. Proceedings of lEE Control '91, No.332, vol. 1, pp. 481-486. (1991a).
[14]Chopra Vikram, Singla Sunil K, Dewan Lillie“, Comparative analysis of tuning a PID controller using intelligent methods”. Acta Polytechnica Hungarica 2014;11 (8):pp. 235–49
[15]Jieming Ma , Ziqiang Bi, Tiew On Ting, Shiyuan Hao, Wanjun Hao, “Comparative performance on photovoltaic model parameter identification via bio-inspired algorithms”, Solar Energy, Volume 132, July 2016, pp 606-616
[16]ChenYu-Peng, LiYing, Wang Gang, ZhengYue-Feng, XuQian, FanJia-Hao, CuiXue-Ting, “A novel bacterial foraging optimization algorithm for feature selection”, Expert Systems with Applications ,Volume 83, 15 October 2017, pp 1-17.
[17]IEEE Task Force on load representation for dynamic performance, “Load Representation for Dynamic Performance Analysis,” IEEE Trans. On Power Systems, vol. 8, pp. 472-482, May 1993.
[18]Stojanovi Dobrivoje P, Korunovi Lidija M, Milanovi JV. Dynamic load modeling based on measurements in medium voltage distribution network. Electric Power Syst Res 2008;78:228–38.
[19]Kosterev D, Meklin A. Load modeling in WECC. Power Systems Conference and Exposition, 2006, 576– 581.
[20]Parveen Tania, 2009. Composite Load Model Decomposition: Induction Motor Contribution, Ph.D. Dissertation. Faculty of Built Environment and Engineering, School of Engineering Systems, Queensland University of Technology
[21]Fahmy, O.M., Attia, A.S., Badr, M.A.L., 2007. A novel analytical model for electrical loads comprising static and dynamic components. Electrical Power Syst. Res. 77, 1249–1256.
[22]Kim Byoung Ho, Kim Hongrae, Lee Byoungjun. Parameter estimation for the composite load model. Journal of International Council on Electrical Engineering,2:2,215-218.
[23]Krause P C, Wasynczuk O, Sudhoff S D. Analysis of Electric Machinery and Drive Systems, 2nd Ed. New York: John Wiley & Sons Publication-IEEE Press, 2002
[24]Kothari, D.P., Nagrath, I.J., 2006. Electric Machines. Tata-McGraw-Hill, India D.S.
[25]Carrasco & M.E. Salgado, “Optimal multivariable controller design using an ITSE performance index”, International Journal of Control Vol. 83, No. 11, November 2010, 2340–2353, ISSN 0020–7179 print/ Taylor & Francis, DOI: 10.1080/00207179.2010.520033
[26]ChenYu-Peng, LiYing, Wang Gang, ZhengYue-Feng, XuQian, FanJia-Hao, CuiXue-Ting, “A novel bacterial foraging optimization algorithm for feature selection”, Expert Systems with Applications,Volume 83, 15 October 2017, Pages 1-17
[27]Passino, K. M. , “ Biomimicry of bacterial foraging for distributed optimization and contro”, IEEE Control Systems Magazine, June 2002, pp. 52 – 67
[28]Guang-Yu Zhu, Wei-Bo Zhang, Optimal foraging algorithm for global optimization”, Applied Soft Computing, Volume 51, February 2017, Pages 294-313
[29]S. Mishra, “A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation,” IEEE Transactions on Evolutionary Computation, vol. 9, no. 1, pp. 61–73, 2005.
[30]Om Prakash Verma; Rishi Raj Chopra; Abhinav Gupta, “An Adaptive Bacterial Foraging Algorithm for color image enhancement,” IEEE Conference on Information Science and Systems (CISS), NJ, USA 16-18 March 2016, pp: 1 - 6