Low-Carbon Economic Operation of Power System Considering Regulation of Industrial Loads

Industrial loads account for a large share of power consumption and possess significant regulation potential for achieving low-carbon economic operation in power systems. Among various industrial loads, the electric arc furnace (EAF) steel plant cluster is rapidly expanding and is characterized by large response capacity and strong price sensitivity. Consequently, it serves as an ideal flexible resource to participate in lowcarbon demand response (LCDR). To this end, this paper proposes a source-load coordinated optimization method considering the regulation of EAF steel plant cluster. First, a continuous resource-task network is employed to establish an EAF steel plant cluster model, which captures the couplings among material, equipment, and energy across the production stages of EAF steelmaking. Second, a bidirectional dynamic decisionmaking-based source-load coordinated optimization method is developed, in which a Wasserstein-based distributionally robust optimization model and a nodal carbon intensity-based LCDR model are formulated for source-side and load-side, respectively. The two models are iteratively coordinated to achieve low-carbon economic operation of the system. Next, to overcome the challenge of computation time exceeding the unit time slot, a warmstart technique is developed to improve computational efficiency. Finally, numerical results on an improved IEEE 39-bus test system demonstrate the effectiveness of the proposed method.