Low-carbon scheduling decision method for industrial park users considering production characteristics

Under the "dual-carbon" goals and the construction of new power systems, industrial parks-as concentrations of energy-intensive enterprises-face significant challenges in achieving low-carbon and clean operation, which is critical for China to meet its national carbon targets. To address the low-carbon regulation requirements of industrial park users, a low-carbon scheduling decision method for industrial park users considering production characteristics is proposed. Firstly, we establish typical demand response regulation scenarios and operational frameworks for industrial parks. Considering the production processes of different industrial sectors, we develop an industrial user classification and screening method for multi-timescale response regulation. Subsequently, incorporating carbon emission reduction benefits into the optimization objectives, we formulate a demand response low-carbon scheduling decision model aiming at maximizing load aggregators' revenues. The model is solved using a modified whale optimization algorithm. Case studies demonstrate that the proposed method can effectively support load aggregators in formulating response regulation incentive schemes for industrial parks, achieving approximately 10% carbon emission reduction while maintaining aggregators' profitability.