A robust optimization framework for flexible industrial energy scheduling: Application to a cement plant with market participation

This study proposes a scenario based robust optimization framework for short term energy scheduling in electricity intensive industrial plants, addressing the limitations of deterministic models that fail to capture market volatility and risk exposure. The motivation lies in the need for risk-aware decision support in sectors such as cement manufacturing, where high electricity consumption and uncertain prices strongly affect cost efficiency. The framework is formulated as a two-stage mixed integer linear program and employs a hybrid scenario generation method combining Auto Regressive Integrated Moving Average forecasting, residual sampling, and clustering to represent day ahead price uncertainty. A convex objective balances expected and worst case costs through a tunable risk aversion parameter. Application to a Spanish cement plant shows that robust scheduling reduces expected baseline costs by nearly 70% compared with deterministic planning, while keeping worst case costs within 2% of the deterministic benchmark. With flexibility activation through battery storage and intraday trading, expected operating costs fall by up to 20%, demonstrating the coordinated value of industrial flexibility. The results confirm that the framework provides tractable, risk informed schedules that enhance cost stability and market participation, supporting robust energy management in energy intensive industries. Overall, these findings highlight the practical feasibility of robust optimization for cement plants, with lessons that can be extrapolated to other energy-intensive industries. • Scenario based robust optimization enhances short term industrial energy scheduling. • Framework balances cost efficiency with resilience under electricity price uncertainty. • Cement plant case study demonstrates improved robustness and reliable operation. • Coordinated use of battery storage and market participation mitigates extreme price risks. • Results provide actionable guidance for energy intensive industries in volatile markets.