Pramod Yelam
Department of Applied Sciences, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India.

Amit Kumar
Department of Applied Sciences, Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India.

DOI https://doi.org/10.33889/IJMEMS.2026.11.3.050

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Abstract

The human factor plays a decisive role in the safe and reliable functioning of modern smart grids, where increasing automation and system complexity impose greater cognitive load on operators. This paper presents a hybrid approach that combines the Fuzzy Analytic Hierarchy Process (FAHP) and Bayesian Network (BN) to assess the probability of human error under uncertain conditions. Triangular fuzzy numbers are used to express expert judgments and are processed through FAHP to obtain the relative significance of key performance shaping factors (PSFs). The normalized weight of each subfactor is calculated and converted into fuzzy possibility scores (FPSs), which are further transformed into fuzzy failure probabilities (FFPs). These probabilities are incorporated into a BN model built in GeNIe to evaluate the effects of individual and grouped factors on human reliability. The model indicates a high level of operator reliability while highlighting the need for improvement in critical situations. The findings suggest that training and knowledge sharing programs, alarm design and management, cognitive load, and shift management are among the most influential subfactors. A case study from the smart grid power distribution sector was conducted to demonstrate the applicability of the proposed framework. Expert opinions from experienced power system engineers and grid operators were collected using purposive sampling to evaluate human reliability factors. The hybrid framework provides a clear understanding of how different conditions affect operator reliability and supports utilities in improving training, communication processes, and control room design. The proposed FAHP BN framework offers a systematic and flexible method for analyzing human reliability in the smart grid environment and serves as a practical tool for identifying critical factors and guiding actions that enhance the safety and reliability of smart grid operations.

Keywords- Human reliability, Fuzzy set theory, Fuzzy AHP, Bayesian network, Smart grid.

Citation

Yelam, P., & Kumar, A. (2026). Hybrid Fuzzy Analytic Hierarchy Process-Bayesian Network Framework for Human Reliability Analysis in Smart Grid Systems. International Journal of Mathematical, Engineering and Management Sciences, 11(3), 1202-1226. https://doi.org/10.33889/IJMEMS.2026.11.3.050.