In the industrial production process

each link is highly interdependent

and different types of industrial loads (such as continuous production

intermittent production

seasonal production

etc.) have different operating characteristics and flexibility potential. Due to the diversity and complexity of industrial loads

traditional scheduling methods are difficult to effectively cope with supply side fluctuations

leading to challenges in flexible load scheduling. To address this issue

a digital twin industrial load flexible scheduling optimization method based on load side potential elasticity is proposed. A virtual model of industrial load is constructed through digital twin technology to achieve real-time mapping and interaction between physical systems and virtual models

thereby accurately monitoring and predicting load status. Based on the theory of load side potential elasticity

analyze the flexibility potential of each sub-system in the industrial system

and develop flexible scheduling strategies to alleviate supply-demand contradictions and cope with supply side fluctuations. The experimental results show that the proposed method can effectively predict the offset of key load influencing factors. With 15 power outages

the system average interruption duration index(SAIDI) drops to 5.4 minutes

and the prediction accuracy reaches 0.95

verifying the practicality and effectiveness of the method.