Dynamic Economic Dispatch Considering Adaptive Look-ahead Time Scale
Basic Research|更新时间:2025-06-16
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Dynamic Economic Dispatch Considering Adaptive Look-ahead Time Scale
Automation of Electric Power SystemsVol. 49, Issue 9, Pages: 107-113(2025)
作者机构:
1.电网智能化调度与控制教育部重点实验室(山东大学),山东省济南市 250061
2.国网河南省电力公司焦作供电公司,河南省焦作市 454150
3.新能源电力系统全国重点实验室(华北电力大学),北京市 102206
作者简介:
基金信息:
National Key R&D Program of China(2022YFB2403000);State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(LAPS23012);National Natural Science Foundation of China(52107110)
GUO Junshao,WANG Mingqiang,HAN Xueshan,et al.Dynamic Economic Dispatch Considering Adaptive Look-ahead Time Scale[J].Automation of Electric Power Systems,2025,49(9):107-113.
GUO Junshao,WANG Mingqiang,HAN Xueshan,et al.Dynamic Economic Dispatch Considering Adaptive Look-ahead Time Scale[J].Automation of Electric Power Systems,2025,49(9):107-113. DOI: 10.7500/AEPS20240709005.
Dynamic Economic Dispatch Considering Adaptive Look-ahead Time Scale
with the increasing scale of power system operation
the contradiction between the model scale and computational efficiency in dynamic economic dispatch has become increasingly pronounced. Enhancing computational efficiency is crucial for dynamic economic dispatch. From a temporal perspective
this paper proposes a time scale decoupling model for dynamic economic dispatch. The model analyzes the influence mechanism between the feasible region of the single-period static optimization model at the current moment and the first future decision-making moment
and multiple constraining factors. Then
it analytically expresses the look-ahead time required for dynamic economic dispatch to ensure that the dispatch achieves a globally optimal solution at the first future decision-making moment. The complete dynamic economic dispatch problem is equivalently decoupled into dynamic economic dispatch problems with multiple shortened time scales
which improves computational efficiency while ensuring the solution optimality. Finally
the effectiveness and superiority of the proposed model are validated by multiple cases.
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