Risk-Aware Assessment Framework for Industrial Renewable Energy Integration Using ISO 50001, a Digital-Twin-Ready Architecture, and Conditional Value-at-Risk

Industrial energy transition has moved from pilot deployment to system integration, where renewable supply must be assessed together with process fit, organisational maturity, and uncertainty. This study proposes a risk-aware assessment framework integrating ISO 50001 energy-management maturity, ISO 31000 risk-management logic, a digital-twin-ready operational architecture, scenario simulation, Conditional Value-at-Risk (CVaR), and multi-criteria decision analysis. The study does not report a live plant-level digital twin or empirical survey validation. Instead, it specifies a five-layer implementation architecture, uses a synthetic survey-like dataset solely to demonstrate parameter recovery, and applies 350 Monte Carlo replications to an industrial energy hub comprising photovoltaic and wind generation, battery storage, and optional Power-to-H2-to-Power storage. The quantitative workflow is reported with explicit equations, input assumptions, random seed, CVaR estimator, TOPSIS weights, and weight-sensitivity analysis. Under the adopted assumptions, the PV–wind–battery configuration achieved the lowest mean cost and CVaR, whereas hydrogen storage substantially reduced curtailment but increased mean cost and tail risk without materially reducing grid purchases. These results are conditional on the stated model assumptions and should not be generalised as empirical evidence. The framework supports structured investment and operational assessment by linking technical performance, organisational readiness, and cost–risk–decarbonisation trade-offs.