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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
郭俊劭(1999—),男,硕士研究生,主要研究方向:电力系统安全经济运行。E-mail:j_s_guo@163.com
王明强(1982—),男,通信作者,博士,副教授,博士生导师,主要研究方向:电力系统安全经济运行。E-mail:wang0367@sdu.edu.cn
韩学山(1959—),男,博士,教授,博士生导师,主要研究方向:电力系统运行分析与控制。E-mail:xshan@sdu.edu.cn
收稿:2024-07-09,
修回:2024-12-07,
网络出版:2025-01-26,
纸质出版:2025-05-10
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郭俊劭,王明强,韩学山等.考虑自适应前瞻时间尺度的动态经济调度[J].电力系统自动化,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.
郭俊劭,王明强,韩学山等.考虑自适应前瞻时间尺度的动态经济调度[J].电力系统自动化,2025,49(9):107-113. DOI: 10.7500/AEPS20240709005.
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.
近年来,随着电力系统运行规模的日益增大,动态经济调度中模型规模和计算效率之间的矛盾也日益加深,提升计算效率对于动态经济调度至关重要。从时间维度出发,文中提出一种动态经济调度的时间尺度解耦模型。该模型分析了当前时刻与未来第1个待决策时刻的单时段静态优化模型的可行域与多重牵制因素之间的影响机理,进而解析化表达了能保证未来第1个待决策时刻调度取到全局最优解的动态经济调度所需考虑的前瞻时间,将一个完整的动态经济调度问题等效解耦为多个时间尺度截短的动态经济调度问题,在保证解的最优性的同时,提升了计算效率。最后,基于多个算例验证了所提模型的有效性及优越性。
In recent years
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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