Journal of Energy Management and Technology

Journal of Energy Management and Technology

Analysis of operational risks of electricity distribution network based on the fuzzy cognitive map approach

Document Type : Original Article

Authors
Elham Fallah Baghemoortini 1
Davood Shishebori 1
Majid Alimohammadi Ardakani 2
1 Department of Industrial Engineering, Yazd University, Yazd, Iran
2 Industrial Engineering Department, Faculty of Engineering, Ardakan University, Ardakan, Iran
10.22109/jemt.2024.423829.1474
Abstract
One of the most essential development factors in any country is the quality of electricity supply and distribution. Energy consumers seek electricity supply at a very high safety level. Considering the sensitivity of electronic devices and the dependence of most activities on electricity, providing sustainable energy in urban systems is critical. Unscheduled shutdowns are the leading cause of disruption in the continuity of electricity supply and reduce the quality of power delivered to customers. Operational risks are potential events that result in unplanned outages in the network. In the current research, the fuzzy cognitive map (FCM) method has been used to investigate the relationships between risks and to reach a comprehensive solution for the simultaneous control and management of several risks. Accordingly, extracting the effect of operational risks on each other and how to draw them in the form of a FCM is analyzed and represented. The results emphasize that adverse weather conditions are the most influential with the highest degree of output and equipment failure is the most influential with the highest degree of input in operational risks. The highest value of the sum of input and output degrees (centrality) is the breakdown in the transformer, which has the highest value. The analysis of managerial and practical perspectives shows that the operators, by focusing on forecasting weather conditions and retrofitting network structures and technical management of transformers, reach a convergent and sustainable solution to manage operational risks and ultimately reduce unplanned shutdowns.
Keywords
Operational risk
power distribution network
unplanned outage
fuzzy cognitive map

Subjects

[1]. H. Mubarak et al., “Operational Cost Minimization of Electrical Distribution Network during Switching for Sustainable Operation,” Sustainability, vol. 14, no. 7, p. 4196, Apr. 2022.
[2]. M. Jayachandran, K. P. Rao, R. K. Gatla, C. Kalaivani, C. Kalaiarasy, and C. Logasabarirajan, “Operational concerns and solutions in smart electricity distribution systems,” Util. Policy, vol. 74, p. 101329, Feb. 2022.
[3]. N.-O. Hohenstein, “Supply chain risk management in the COVID-19 pandemic: strategies and empirical lessons for improving global logistics service providers’ performance,” Int. J. Logist. Manag., vol. 33, no. 4, pp. 1336–1365, Oct. 2022.
[4]. M. Yuan, Z. Li, X. Li, and X. Luo, “Managing stakeholder-associated risks and their interactions in the life cycle of prefabricated building projects: A social network analysis approach,” J. Clean. Prod., vol. 323, p. 129102, Nov. 2021.
[5]. M. Jahangoshai Rezaee, S. Yousefi, M. Valipour, and M. M. Dehdar, “Risk analysis of sequential processes in food industry integrating multi-stage fuzzy cognitive map and process failure mode and effects analysis,” Comput. Ind. Eng., vol. 123, pp. 325–337, 2018.
[6]. G. Nápoles, I. Grau, L. Concepción, L. Koutsoviti Koumeri, and J. P. Papa, “Modeling implicit bias with fuzzy cognitive maps,” Neurocomputing, vol. 481, pp. 33–45, Apr. 2022.
[7]. T. Ozgen Genc and A. Ekici, “A new lens to the understanding and reduction of household food waste: A fuzzy cognitive map approach,” Sustain. Prod. Consum., vol. 33, pp. 389–411, Sep. 2022,
[8]. Sangbor, M.A., Safi, M.R. and Azar, A., 2019. Application of Fuzzy Cognitive Maps (FCM’s) to analysis and design the causal structure of sustainable supply chain management enabler’s in the petrochemical industry. Public Management Researches, 12(43), pp.5-29.
[9]. K. Mostafaee, A. Azar, and  abbas Moghbel, “Identification and Analysis of Operational Risks: A Fuzzy Cognitive Map Approach,” J. Asset Manag. Financ., vol. 6, no. 4, pp. 1–18, 2018.
[10]. U. Özesmi and S. L. Özesmi, “Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach,” Ecol. Modell., vol. 176, no. 1, pp. 43–64, 2004.
[11]. M. J. Rezaee, S. Yousefi, and M. Babaei, “Multi-stage cognitive map for failures assessment of production processes: An extension in structure and algorithm,” Neurocomputing, vol. 232, pp. 69–82, Apr. 2017.
[12]. S. Asadzadeh, “Optimal Modeling and Forecasting of Equipment Failure Rate for the Electricity Distribution Network  TT  - Modeling and optimal prediction of failure rate of power distribution network equipment,” ieijqp, vol. 8, no. 1, pp. 53–61, Sep. 2019.
[13]. A. Akbari; "Optimum rearrangement of distribution networks with the aim of reducing losses, increasing reliability and improving voltage profile using wild mouse colony algorithm", New research in electricity, vol. 9, no. 1, 2020.
[14]. A. Karim Abadi, M. E. Haji Abadi, and E. Kamyab, “A review of the maintenance and equipment failure of transmission and Super distribution substations TT  - An overview of the repairs and breakdowns of transmission and super distribution substation equipment,” iaud-jeps, vol. 5, no. 2, pp. 20–31, Mar. 2017.
[15]. L. Souto, J. Meléndez, and S. Herraiz, “Monitoring of low voltage grids with multilayer principal component analysis,” Int. J. Electr. Power Energy Syst., vol. 125, p. 106471, Feb. 2021.
[16]. Alajmi, Bader N., M. F. AlHajri, Nabil A. Ahmed, Ibrahim Abdelsalam, and Mostafa I. Marei. "Multi‐objective Optimization of Optimal Placement and Sizing of Distributed Generators in Distribution Networks." IEEJ Transactions on Electrical and Electronic Engineering (2023).
[17]. N. Elamin and M. Fukushige, “Modeling and forecasting hourly electricity demand by SARIMAX with interactions,” Energy, vol. 165, pp. 257–268, Dec. 2018.
[18]. Xu, Xiaomin, Dongxiao Niu, Luyao Peng, Shipeng Zheng, and Jinpeng Qiu. "Hierarchical multi-objective optimal planning model of active distribution network considering distributed generation and demand-side response." Sustainable Energy Technologies and Assessments 53 (2022): 102438.
[19]. B. Kosko, “Fuzzy cognitive maps,” Int. J. Man. Mach. Stud.,
vol. 24, no. 1, pp. 65–75, 1986.
[20]. Enjavimadar, MohammadHosein, and Mohammad Rastegar.
"Optimal reliability-centered maintenance strategy based on the failure modes and effect analysis in power distribution systems." Electric Power Systems Research 203 (2022): 107647.
[21]. Abdollahzadeh, Sohrab, and Jamileh Hayati. "Development of a multi-stage fuzzy cognitive map for an uncertainty environment: methods and introduction." Neural Computing and Applications 35, no. 6 (2023): 4499-4517.
[22]. Khajeh, Fatemeh, and Hamid Shahbandarzadeh. "Modeling factors affecting the interests of the container terminal using fuzzy cognitive map and fuzzy DEMATEL." Journal of Modelling in Management ahead-of-print (2022).
Journal of Energy Management and Technology
Volume 8, Issue 4
Autumn 2024
Pages 360-368

  • Receive Date 21 November 2023
  • Revise Date 11 August 2024
  • Accept Date 27 September 2024