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Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach

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  • Sonal,
  • Ghosh, Debomita

Abstract

The planning and operation of distribution systems have significantly changed due to the extensive osmosis of ICT (information and communication technologies) into power systems. Load growth, together with increased power quality expectations by the customers, has transformed the conventional distribution network to active distribution network (ADN), with penetration of distributed energy resources (DERs). This has imposed the necessity to analyze resilient performance of ADN subjected to the boon of ICT for enhanced situational awareness (SA). This paper focuses on a detailed multi-level hierarchy framework using linguistic scale based multi-criteria decision-making (MCDM) approach for SA oriented resilience level estimation of ADN, considering different high impact low frequency (HILF) events. The rapidly changing environmental conditions and ambiguity in interaction of network parameters lead to non-deterministic resilience (NDR), thus, affecting the operational resilience of ADN on a daily basis. To analyze the uncertain ADN availability due to NDR, hybrid MCDM-dynamic Bayesian network (DBN) approach is used. For better decision-making, the operational performance of ADN, to withstand critical loads due to NDR is analyzed in terms of load not served (LNS) index. The proposed framework is tested on IEEE 33-bus distribution network.

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  • Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003957
    DOI: 10.1016/j.ress.2022.108772
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    4. Khaledi, Arian & Saifoddin, Amirali, 2023. "Three-stage resilience-oriented active distribution systems operation after natural disasters," Energy, Elsevier, vol. 282(C).

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