Selecting an Appropriate Scenario for Implementing RCM and RCA to Reduce System Average Interruption Duration Index with Systems Dynamics Approach in Power Distribution Companies

Journal of Systems Thinking in Practice

مقاله 4، دوره 2، شماره 3 - شماره پیاپی 6، دی 2023، صفحه 72-96   

نوع مقاله: Research Article

شناسه دیجیتال (DOI): 10.22067/jstinp.2023.82070.1058

نویسندگان

Rouhollah Rad^{* 1}؛ Habib Rajabi Mashhadi²

¹Industrial Management, Faculty of Economics and Administrative sciences, Ferdowsi University of Mashhad, Mashhad, Iran.

²Electrical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.

چکیده

The mission of power companies is to provide standard and reliable electricity to their customers, and one of the threats of not fulfilling this mission is breakdowns and accidents in the electricity network equipment. The System Average Interruption Duration Index (SAIDI) is a critical indicator in the power distribution industry to determine network reliability; Reliability Centered Maintenance (RCM) and root cause analysis (RCA) of failures and applying the results of these two in two dimensions of network maintenance and design, are two effective measures in reducing SAIDI. This paper presents a model for the system and structure that creates SAIDI behavior, which can be simulated to achieve appropriate policies to determine the level of use of RCM and RCA and, thus, the optimal value to reduce the index value. The System simulation method has been used to simulate system behavior. After designing and simulating the cyclic causal model, various scenarios for determining RCM and RCA policies are proposed and reviewed, and the results are presented. The criterion for selecting the appropriate scenario in this article is to reduce the SAIDI index's value further. Based on the research findings, the policies selected have a suitable reducing effect on SAIDI. The model's validity was evaluated through behavior replication testing, extreme condition assessment, and sensitivity analysis. Since the organization's vision in 2026 is to reduce SAIDI to 14 minutes per year, the impact of RCM and RCA policies in different scenarios on the model variables was evaluated. The results showed that if the existing policies are not changed, the process of SAIDI changes will increase. Changing the system approach from non-implementation to implementing RCM and RCA under optimal conditions will decrease SAIDI from 26.73 minutes at the beginning of 2020 to 41.34 minutes by the end of 2026

کلیدواژه‌ها

System dynamics؛ System average interruption Duration index؛ Reliability centered maintenance؛ Root cause analysis؛ Power distribution companies

مراجع

Azar, A., Khosravani, F. & Jalali, R. 2013. Research in software operations: structuring approaches to problems, Tehran, Industrial Management Organization. 978-600-275-047-1/ISSN [In Persian].

Alimohammadi, M. and Behnamian, J., 2021. Preventive maintenance scheduling of electricity distribution network feeders to reduce undistributed energy: A case study in Iran. Electric Power Systems Research, 201, p.107509. https://doi.org/10.1016/j.epsr.2021.107509.

Anbiaei, M. S. 2004. Important factors increase the power outage time. 9th Conference on Electrical Power Distribution Networks. Iranian Association of Electrical &Electronics Engineers.

Bala, B.K., Arshad, F.M. and Noh, K.M., 2017. System dynamics. Modelling and Simulation, 274. Singapore, Springer. https://doi.org/10.1007/978-981-10-2045-2.

Ghasemianfard, E. and Moosavirad, S.H., 2017. Undelivered Electricity in North-Kerman Electricity Distribution Company: System Dynamics Analysis. Journal of Energy Planning And Policy Research, 3(3), pp.119-145. [In Persian].  Available at: http://epprjournal.ir/article-1-278-en.html.

Gord, E., Dashti, R., Najafi, M., Santos, A.Q. and Shaker, H.R., 2020. Determining an accurate fault location in electrical energy distribution networks in the presence of DGs using transient analysis. Measurement, 151, p.107270. https://doi.org/10.1016/j.measurement.2019.107270.

IEEE 2012. IEEE Guide for Electric Power Distribution Reliability Indices. IEEE Std 1366-2012 (Revision of IEEE Std 1366-2003). IEEE.null. http://dx.doi.org/10.1109/IEEESTD.2012.6209381.

Jasim Mohammad AL Shaheen, M. 2017. Improvement of reliability by reducing power outages in the 11kV power distrbution network of Fuhood city - Thi-qar province / Iraq. Master of Science in Electrical Engineering Thesis, Ferdowsi University of Mashhad-Department of Electrical Engineering. [In Persian].

Meadows, D., Richardson, J. and Bruckmann, G., 1982. Groping in the dark: the first decade of global modelling. John Wiley & Sons.

Mercado, G.A.G. and Sanchez, J.W.G., 2021. Optimization of reclosers placement in distribution networks to improve service quality indices. IEEE Latin America Transactions, 20(2), pp.241-249. https://doi.org/10.1109/TLA.2022.9661463.

Mohammadi, R. and Rajabi Mashhadi, H.R., 2019. A Game Theory Approach to Distribution System Reliability Improvement Based on Customer Requests. Iranian Journal of Electrical & Electronic Engineering, 15(1). http://dx.doi.org/10.22068/IJEEE.15.1.1.

Nourizadeh, H. and Niasati, M., 2020. Optimal Placement of Distribution substations with The Purpose of Reducing Losses and Energy Not Supplied by A Multi-Objective Function and Artificial Bee Colony (ABC) Optimization Algorithm. Computational Intelligence in Electrical Engineering, 11(4), pp.65-80. http://dx.doi.org/10.22108/isee.2020.121806.1339.

Quentara, L.T. and Suryani, E., 2017. System Dynamics Development Model for Operations Strategy in Power Generation System through Integrated Transmission and Distribution System. IPTEK Journal of Science, 2(1), pp.5-10. http://dx.doi.org/10.12962/j23378530.v2i1.a2253.

Sterman, J., 2000. Instructor's manual to accompany business dyanmics: systems thinking and modeling for a complex world. McGraw-Hill.

Tatietse, T.T., Villeneuve, P., Ndong, E.P.N. and Kenfack, F., 2002. Interruption modelling in medium voltage electrical networks. International journal of electrical power & energy systems, 24(10), pp.859-865. https://doi.org/10.1016/S0142-0615(02)00010-8.

Tavanir 2018. Instructions for calculating the reliability indicators of power distribution networks with limited information. Tehran: Tavanir Company, Distribution Coordination Deputy, Distribution Supervision Office.3136/274. [In Persian].

Thurlby, R., 2013. Managing the asset time bomb: a system dynamics approach. Proceedings of the Institution of Civil Engineers-Forensic Engineering, 166(3), pp.134-142. https://doi.org/10.1680/feng.12.00026.