Abstract: The development of a new power system with a high proportion of renewable energy sources presents new requirements for the flexibility of the power system. In order to fully tap into the flexible load resources on the demand side, some provinces have released demand response programs to encourage electricity users to participate in peak demand reduction. High-energy-consuming industrial loads have advantages such as large individual capacities and strong power controllability. However, their participation in demand response is limited by normal production needs and a lack of strategies to maximize response benefits. Therefore, this paper proposes a power control strategy for high-energy-consuming loads, using electrolytic copper as an example, in a demand-side market response plan. Initially, the feasibility of power adjustment in the electrolytic copper process is analyzed and a power control model is established. A resource task network (RTN) model is established for the electrolytic copper process to describe production states within the load production cycle and power control boundaries are determined based on material quantities. Based on the demand response implementation plan in Sichuan Province, the mechanism is clarified for calculating load response benefits and constraints. Considering additional costs incurred by power control, a method is proposed to calculate the cost of load participation in response. A power control strategy maximizing load response benefits while considering additional costs, production safety and effective response constraints is proposed. Finally, simulations are conducted under different scenarios, demonstrating that the power control strategy in this paper can increase response benefits by over 16% compared to meeting only the contracted response demand. Additionally, it effectively meets response demand over longer time scales, validating the effectiveness of the proposed power control strategy and providing a feasible solution for industrial load participation in demand response.