LSTN：面向需求响应的工业生产过程线性模型
LSTN: A Linear Model of Industrial Production Process for Demand Response
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中文总结 AI 辅助
该研究针对传统工业生产建模在大规模需求响应应用中计算不可行的问题，提出LSTN线性模型，平衡了计算复杂度与建模精度，数值结果表明其准确性高且计算效率显著优于对比方法。
中文摘要 AI 辅助
工业生产建模为参与需求响应（DR）项目的工业用户提供运行约束。传统生产过程建模引入二元变量来模拟工业设备的离散运行点，在大规模DR应用中会导致计算不可行。为在平衡计算复杂度与建模精度的同时合理模拟工业用户运行约束，我们开发了用于评估DR应用的工业生产过程线性模型。数值结果验证了该模型的准确性，且相较于对比方法其计算效率有显著提升。
英文摘要
Industrial production modeling provides operational constraints for industrial users participating in demand response (DR) programs. Conventional modeling of the production process introduces binary variables to model the discrete operating points of industrial equipment, which can be computationally infeasible in large-scale DR applications. To reasonably model industrial users' operational constraints while balancing computational complexity and modeling accuracy, we developed a linear model of the industrial production process for evaluating DR applications. Numerical results verify the accuracy of the proposed model and its great improvement in computational efficiency over competing approaches.
