A Simulation-Assisted Fuzzy STENOZA Framework for Selecting Resilient Energy Configurations in the Steel Industry

Abstract

Electricity allocation constraints can interrupt steel production despite substantial annual design capacity. We combine chronological simulation with fuzzy STENOZA (STEvic NOvarlić ZAvadskas) to compare three electricity-supply renovations against the existing allocated feed of a cold rolling plant in Libya. Published capacity and product-mix information determine the production-linked electrical requirement. The simulation evaluates interruptions, summer allocation withdrawal and fuel replenishment over 5,000 annual replications, while four experts provide questionnaire judgements on criterion importance and implementation performance. The fuzzy calculation propagates nonlinear alpha cuts and recovers crisp STENOZA. The integrated photovoltaic–storage–backup configuration ranks first, followed by dispatchable backup, the existing feed and photovoltaic–storage. Relative to the baseline, the integrated option reduces expected annual lost production from 17,326 to 3,524 tonnes (79.66%) and severe-year tail loss by 75.80%. Expected net present cost increases by 203.18%, while operational carbon dioxide emissions fall by 18.24%. The integrated option ranks first in 95.66% of 5,000 random-weight scenarios. The baseline becomes preferred when its cost weight exceeds approximately 0.262. A4 also leads after deletion of the tail-loss criterion, although a mandatory summer production stop favours dispatchable backup. The results quantify the production protected by renovation and identify the operating conditions and preferences that change the investment choice.