中国电力2025，Vol.58Issue(8)：118-129,12.DOI:10.11930/j.issn.1004-9649.202503038
计及最大需量基于改进RTN模型的短流程钢铁企业双层优化调峰策略
Bi-level Optimization Peak-shaving Strategy for Short-process Steel Enterprises Considering Maximum Demand Based on an Improved RTN Model
摘要
Abstract
As large energy users,the short-process steel enterprises have great potential for peak-shaving,which provides an important resource for improving the peak-shaving state of the power grid.However,their production processes are closely linked and orders fluctuate greatly,resulting in irregular electricity consumption,which makes it difficult for steel enterprises to participate in power grid peak-shaving.To this end,this paper proposes a bi-level optimization peak-shaving strategy for short-process steel enterprises considering maximum demand based on the improved resource-task network(RTN)model,so as to help short-process steel enterprises participate in power grid peak shaving.Firstly,an improved RTN with time window nodes was designed to accurately characterize the coupling relationships of materials and temporal resources between devices within a single production line when processing different types of orders,ensuring the feasibility of order allocation and scheduling strategies.Secondly,enterprise orders were allocated based on the actual multi-production-line scenarios,and a supply-demand interaction bi-level optimization peak-shaving model considering maximum demand was proposed,which was solved using a hybrid algorithm combining adaptive particle swarm optimization(APSO)and the Cplex solver.Finally,according to the data from an actual short-process steel enterprise,three simulation scenarios were set up to verify the proposed scheduling strategy.The results show that the proposed strategy can effectively smooth the load curve while reducing the enterprise's electricity costs.关键词
短流程钢铁企业/双层优化/最大需量/订单分配/调峰策略/时间窗节点Key words
short-process steel enterprises/bi-level optimization/maximum demand/order allocation/peak-shaving strategy/time window node引用本文复制引用
刘航,申皓,纪陵,钟永洁,陈嘉瑞,余洋..计及最大需量基于改进RTN模型的短流程钢铁企业双层优化调峰策略[J].中国电力,2025,58(8):118-129,12.基金项目
国网河北省电力有限公司科技项目(工业负荷灵活资源动态聚合互动响应与协同调控关键技术研究与应用,kj2023-029). This work is supported by Science and Technology Project of State Grid Hebei Electric Power Co.,Ltd.(Research and Application of Key Technologies for Dynamic Aggregation Interactive Response and Co-regulation of Industrial Load Flexible Resources,No.kj2023-029). （工业负荷灵活资源动态聚合互动响应与协同调控关键技术研究与应用,kj2023-029）
