计及生产特性的工业园区用户低碳调度决策方法OA
Low-carbon scheduling decision method for industrial park users considering production characteristics
在"双碳"目标和新型电力系统建设的背景下,工业园区作为高耗能企业的集中地,其低碳清洁的运行方式是目前中国实现双碳目标中面临的重大挑战.针对工业园区用户低碳调控需求,提出了一种计及生产特性的低碳调度决策方法.首先建立了工业园区需求响应调控典型场景与业务流程,并考虑不同工业行业的生产工艺,提出面向不同时间尺度响应调控的工业用户分类及筛选方法,随后将碳减排收益纳入考虑,并以负荷聚合商收益最大为目标,构建需求响应低碳调度决策模型,并采用改进鲸鱼优化算法进行模型求解.最后通过实际算例,验证了该方法能够有效支撑工业园区负荷聚合商制定响应调控激励方案,在保证聚合商收益的同时减少园区碳排放量约 10%.
Under the"dual-carbon"goals and the construction of new power systems,industrial parks-as concentrations of energy-intensive enterprises-face significant challenges in achieving low-carbon and clean operation,which is critical for China to meet its national carbon targets.To address the low-carbon regulation requirements of industrial park users,a low-carbon scheduling decision method for industrial park users considering production characteristics is proposed.Firstly,we establish typical demand response regulation scenarios and operational frameworks for industrial parks.Considering the production processes of different industrial sectors,we develop an industrial user classification and screening method for multi-timescale response regulation.Subsequently,incorporating carbon emission reduction benefits into the optimization objectives,we formulate a demand response low-carbon scheduling decision model aiming at maximizing load aggregators'revenues.The model is solved using a modified whale optimization algorithm.Case studies demonstrate that the proposed method can effectively support load aggregators in formulating response regulation incentive schemes for industrial parks,achieving approximately 10%carbon emission reduction while maintaining aggregators'profitability.
孔祥玉;杨振宇;刘子瑜;高碧轩;庄重;段梅梅
天津大学 智能电网教育部重点实验室,天津 南开 300072天津大学 智能电网教育部重点实验室,天津 南开 300072天津大学 智能电网教育部重点实验室,天津 南开 300072||国网大连供电公司,辽宁 大连 116001天津大学 智能电网教育部重点实验室,天津 南开 300072国网江苏省电力有限公司营销服务中心,江苏 南京 210019国网江苏省电力有限公司营销服务中心,江苏 南京 210019
工业园区生产特性低碳调度需求响应多时间尺度
industrial parkproduction characteristicslow-carbon schedulingdemand responsemultiple timescales
《中国电力》 2026 (3)
37-47,11
This work is supported by the Science and Technology Project of State Grid Corporation of China(No.5400-202418217A-1-1-ZN). 国家电网有限公司科技项目(5400-202418217A-1-1-ZN).
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