International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 10, No. 3, 8 May 2018
Cover page and Table of Contents: PDF (size: 1086KB)
Simulation of Electric Power Plant Performance Using Excel®-VBA
Full Text (PDF, 1086KB), PP.8-14
Views: 0 Downloads: 0
Author(s)
Index Terms
Simulation, Random Number, Turbo Alternator, Excel® - VBA, Reliability, Power Station
Abstract
This paper presents the failure and repair simulation for electric power house with N Turbo-alternator, where N may be up to 32. The program employs a pseudo-random number generator for individual power plant that can be described by exponential probability density functions. The resulting sequences of failure and repair events are then combined for the plants to give scenarios for different time horizons. The implementation in Excel®-VBA includes an appropriately designed userform containing the macro Active-X control for input of relevant information. The result shows that as the number of samples increased the behavior of the random events better represented the desired form with a correlation of almost 99% for 25 trials. This corresponds to a confidence interval of better than 95% and hence should be used as the median for practical applications. The results were tested and the distributions of the events were found to be close approximation of the target exponential distributions.
Cite This Paper
Blessing O. Abisoye, Opeyemi A. Abisoye, "Simulation of Electric Power Plant Performance Using Excel®-VBA", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.10, No.3, pp. 8-14, 2018. DOI:10.5815/ijieeb.2018.03.02
Reference
[1]Sara Bengtsson, (2011): Modelling of a Power System in a Combined Cycle Power Plant, Chap. 2, Pg 9. ISSN: 1650-8300, UPTEC ES11 009
[2]Okolobah, Victor, and Zuhaimy Ismail. "On the issues, challenges and prospects of electrical power sector in Nigeria." International Journal of Economy, Management and Social Sciences 2.6 (2013): 410-418
[3]Sardou, I. G., Ameli, M. T., Sepasian, M. S., & Ahmadian, M. (2013). A novel genetic-based optimization for transmission constrained generation expansion planning. International Journal of Intelligent Systems and Applications, 6(1), 73.
[4]Frank, S., Steponavice, I., & Rebennack, S. (2012). Optimal power flow: a bibliographic survey I. Energy Systems, 3(3), 221-258.
[5]Chandrasekaran, B. (1990). Design problem solving: A task analysis. AI magazine, 11(4), 59.
[6]Ören, T. (2011). The many facets of simulation through a collection of about 100 definitions. SCS M&S Magazine, 2(2), 82-92.
[7]Zeigler, B. P., Praehofer, H., & Kim, T. G. (2000). Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems. Academic press
[8]Sokolowski, J. A., & Banks, C. M. (2009). Modeling and simulation for analyzing global events. John Wiley & Sons.
[9]Banks, J., Carson J., Nelson B.L. and Nicol, D. (2005): Discrete-event system Simulation (4th Ed.). Upper Saddle River, NJ: Pearson Prentice Hall. ISBN 978-0-13-088702-3
[10]Aldrich, C. (2005). Learning by doing: A comprehensive guide to simulations, computer games, and pedagogy in e-learning and other educational experiences. John Wiley & Sons.
[11]Kitano, H. (2002). Systems biology: a brief overview. Science, 295(5560), 1662-1664.
[12]Fujimoto, R. M. (2000). Parallel and distributed simulation systems (Vol. 300). New York: Wiley.
[13]Luo, L., Gao, L., & Fu, H. (2011). The control and modeling of diesel generator set in electric propulsion ship. International Journal of Information Technology and Computer Science (IJITCS), 3(2), 31.
[14]Eromon, D. (2006). Voltage Regulation Making use of Distributed Energy Resources (DER). The International Journal of Modern Engineering, 6(2), 52.
[15]Allan, R. N. (2013). Reliability evaluation of power systems. Springer Science & Business Media.
[16]Wang, H., Liserre, M., & Blaabjerg, F. (2013). Toward reliable power electronics: Challenges, design tools, and opportunities. IEEE Industrial Electronics Magazine, 7(2), 17-26.
[17]Goševa-Popstojanova, K., & Trivedi, K. (2000). Stochastic modeling formalisms for dependability, performance and performability. Performance Evaluation: Origins and Directions, 403-422.
[18]Colombo, A.G. and Sáiz de Bustamante, Amalio, (1988): Systems reliability assessment – Proceedings of the Ispra Course held at the Escuela Tecnical Superior de Ingenieros Navales, Madrid, Spain, in collaboration with Universidad Politecnica de Madrid.