摘要
针对智能电网需求响应为高耗能电力用户节约用电成本及参与电网调峰提供的新契机,在需求响应分时电价实现形式下,考虑最小化生产用电成本,建立热轧批量计划问题数学模型,提出一种面向经济负荷调度的热轧批量计划两阶段优化方法:第1阶段通过热轧批量计划编制确定轧制单元及生产负荷,第2阶段在此基础上根据电价实施分时电价下的负荷转移重调度,优化轧制单元生产加工次序,并合理安排生产时间进行避峰生产,基于遗传算法实现两阶段优化求解。研究结果表明:所提出方法可在保证生产前提下降低热轧生产用电成本,并通过响应电价促进电网调峰。
Smart grid demand response provides a new opportunity for energy intensive users to reduce electricity cost and participate peak load regulation of power grid, in the time-of-use（TOU） form of demand response, considering minimizing the electricity cost in production, a mathematical model of hot rolling batch scheduling problem was established, and a two-stage optimization approach was proposed for economic load dispatch. In the first stage, the rolling units were constructed and the corresponding power load was determined. In the second stage, load shift rescheduling was put into effect according to TOU tariffs to sequence the rolling units and arrange them into reasonable time periods to avoid on-peak load, and the implementation of two-stage optimization was based on genetic algorithms（GA）.The results show that the proposed approach can reduce electricity cost of hot rolling on the premise of ensuring the production and promote peak load regulation of power grid.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第10期3456-3462,共7页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61402391
61170191)
湖南省自然科学基金资助项目(14JJ2071)
湖南省教育厅资助科研项目(14C1070)~~
关键词
分时电价
热轧批量计划
经济负荷调度
遗传算法
time-of-use electricity tariffs
hot rolling batch scheduling
economic load dispatch
genetic algorithm
