大型钢铁企业能量流与制造流协同鲁棒优化方法研究

Due to the large energy demand of iron and steel enterprises and its manufacturing flexibility, iron and steel enterprises have a significant energy saving potential. However, the coordination and cooperation between energy and production flow make the optimization of energy saving operation extremely complicated. Coordination optimization may face the challenges such as coupling of energy and production flow, high uncertainties in energy production- consumption- storage, and high computational complexity. In this proposal, to address the challenges mentioned above, we will research the coordination optimization method of energy and production flow. Firstly, from the view of cyber-physical system (CPS)’s point, we will analyze the coupling relationship between energy and production flow. And then we will proposed the coupling model. Secondly, considering the uncertainties of energy supply, energy demand, and production conditions, we will build robust optimization model for iron and steel enterprises with coordination in energy and production flow by constructing nonanticipative constraints and all- scenario- feasibility constraints. Thirdly, we will put forward the judgment conditions to verifying the balance between energy supply and demand by analyzing the model structure. Aiming at the multi-stage time coupling constraints in the robust model, we will study the decoupling method and design solution algorithm that satisfies nonanticipative constraints and all- scenario- feasibility constraints. This algorithm can avoid the computational complexity of iterative algorithms. The research results will be demonstrated based on the manufacturing and energy management system for iron and steel enterprises. The project will contribute to establishing theoretic foundations and development practical methods for energy management of cyber-physical systems.

钢铁企业能耗巨大且制造流程柔性强，具有巨大的节能优化潜力。但其能源系统与生产制造流程相互关联和影响，使得钢铁企业节能运行优化问题异常复杂。本项目旨在从钢铁企业能量流与制造流间的复杂耦合关联特性、供需高不确定性、优化求解计算复杂性等挑战出发，研究钢铁企业能量流与制造流协同优化问题。以信息物理融合系统相关理论与方法为基础，分析能量流与制造流的耦合机理，提出能量流与制造流的耦合机理模型；考虑能源供需及生产工况等不确定性，构造非预期性及全场景可行性条件，建立能量流与制造流协同的全场景可行非预期鲁棒优化模型；提出不确定供需平衡判定条件，研究时间耦合约束的解耦方法，提出全场景可行非预期鲁棒优化模型的高效求解算法。基于实际钢铁企业生产制造与能源管理系统，验证项目研究成果。研究成果为信息物理深度融合的能源系统节能优化运行做出理论和方法上的贡献，具有良好的前瞻性。

本研究旨在从钢铁企业能量流与制造流间的复杂耦合关联特性、供需高不确定性、优化求解计算复杂性等挑战出发，研究钢铁企业能量流与制造流协同优化问题。以信息物理融合系统相关理论与方法为基础，分析能量流与制造流的耦合机理，提出能量流与制造流的耦合机理模型；针对包含V2G的企业随机能源管理问题，构建了相应的两阶段鲁棒整数优化模型，并提出了一种模型转换求解方法。本项目共发表论文8篇，其中SCI4篇，硕士研究生2名；申请发明专利2项，完成了项目预期指标。