The demand response potential in copper production

Demand response (DR) of large industrial electricity consumers is a promising option to balance the fluctuating supply by renewable energies in grid. Renewable energy technologies themselves depend on copper as key material. At same time, production power-intensive process but its DR potential has not yet been quantified detail via scheduling. Here, we analyze optimally scheduling batch and continuous tasks representative process. To determine optimal schedule, formulate mixed-integer linear program (MILP) based resource-task network (RTN) formulation approach. We first optimize volume define reference case then minimize costs under time-varying prices while retaining target. A sensitivity analysis evaluates impact task capacities potential. The results indicate significant potential, can reduce annual up 14.2% still producing maximum output schedule. electrolytic refining shows largest for reducing costs. Offgas handling, air separation, compression further show cost reduction potentials. These must material streams that are directly connected operating smelting tasks. Our model considering these interlinked one focuses DR. suggest economic without compromising goals. Further, shifts amounts demand responding prices, which enables flexibility side thus support integration into electric