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Development of the Power Supply System's Resilience Model (Case Study: Khusestan Province Electrical Grid)

Mombeni, Navid | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53796 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Saboohi, Yadollah
  7. Abstract:
  8. The purpose of the current study is developing an evaluation model for the electrical grid. Resilience is an approach toward risk management against disorders and protecting the system during critical conditions. The importance of resilience assessment, especially in crucial infrastructures, has always been at the center of attention. Nonetheless, previous studies in this field were mostly limited to micro-scales, meaning that only a limited part of the system was evaluated. Therefore, such studies rely on technical data and system details. This issue renders macro-scale assessments challenging. Some of the models, which are based on analytical-statistical methods, examine the systems at larger scales so they can evaluate the resilience of the system with a short-term approach. The primary downside of such methods is that little are they under the influence of future technological improvements. Their independent nature from the technological advancements results in their lack of generalizability. To overcome the pre-mentioned challenges, in the current study, an analytical-statistical method based on the Bayesian network is introduced. The presented method is applied for the Khuzestan electrical grid, and then the method is evaluated according to the jamming scenario. In the next step, by enhancing system reliance on the system's technical details instead of historical data, a system is developed, which is capable of analyzing intricate systems with a straightforward approach. At the same time, it maintains its sensitivity to future technological enhancements.In an attempt to examine the proposed model, a power failure was imposed on the Khuzestan central grid. The results from studying the effects of this failure on the northeastern region of Khuzestan province showed that the grid's resilience in this area is 94%. The reason behind such a high resilience level is the concentration of hydroelectric power plants in this specific region and its independence from downhill. The developed model underwent a sensitivity analysis for variances in system recovery and the severity of the failure. In the initial stage, recovery took place at a rapid pace and less time which means system performance increases. However, the difficulty of the recovery process gradually increases and reaching the initial stage would be difficult. On the other hand, by elevating the intensity of failure, the system degradation rate sees an increase; therefore, at a fixed recovery period, the system resilience decreases. In conclusion, the length of the recovery period is profoundly dependent on the maximum reduction in performance, and by increasing failure intensity, the length of the recovery period would increase. In reality, however, the technical and economic limitations of the system affect the decisions in the recovery process and dictate the maximum recovery. Finally, the generalized model algorithm and the results of the conducted research are elaborated in detail
  9. Keywords:
  10. Bayesian Network ; Network Resiliance ; Electricity Distribution Network ; Integrated System ; Resilience Enhancement ; Risk Management

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