1.清华四川能源互联网研究院,四川省成都市 610213
2.清华大学电机工程与应用电子技术系,北京市 100084
3.清华大学低碳能源实验室,北京市 100084
4.华北电力大学新能源电力系统全国重点实验室,北京市 102206
杨皓天(1997—),男,硕士,工程师,主要研究方向:低碳电力系统规划与运行模拟、高比例可再生能源系统。E-mail:yanghaotian@tsinghua-eiri.org
王鹏(1992—),男,通信作者,博士,助理研究员,主要研究方向:电力系统低碳规划与运行模拟、分布式优化算法。E-mail:wangpeng2020@mail.tsinghua.edu.cn
杜尔顺(1992—),男,博士,副研究员,主要研究方向:低碳电力技术、电力系统规划与运行。E-mail:duershun@tsinghua.edu.cn
收稿:2025-08-28,
修回:2025-12-31,
网络首发:2026-03-03,
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杨皓天,王鹏,杜尔顺等.计及煤电机组电碳动态耦合特性的电力系统规划优化方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250828009.
YANG Haotian,WANG Peng,DU Ershun,et al.Optimization Method for Power System Planning Considering Dynamic Electricity-Carbon Coupling Characteristics of Coal-fired Power Units[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250828009.
杨皓天,王鹏,杜尔顺等.计及煤电机组电碳动态耦合特性的电力系统规划优化方法[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20250828009. DOI:
YANG Haotian,WANG Peng,DU Ershun,et al.Optimization Method for Power System Planning Considering Dynamic Electricity-Carbon Coupling Characteristics of Coal-fired Power Units[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20250828009. DOI:
在碳达峰碳中和战略目标下,中国电力系统正加速向高比例新能源为主体的新型形态演进,煤电机组逐渐由基荷电源向调峰电源转变。煤电机组的灵活运行虽提升了系统调节能力,但不同工况下碳排放强度差异显著,传统以常数表征的静态碳排放因子方法在高比例新能源电力系统中已难以适用。为此,文中提出了一种计及煤电机组电碳动态耦合特性的电力系统规划优化方法,以精确刻画不同工况下的碳排放差异。针对模型中引入的非凸、非线性电碳耦合约束,设计了基于泰勒展开的迭代求解方法,并在理论上证明了其收敛性与收敛速率;同时针对煤电机组线性碳排放表征方法,提出了无置信域约束的改进算法,进一步提升了求解效率。最后,通过Garver 6节点系统及中国某500 kV主干网区域算例进行验证,所提方法在求解效率与稳定性方面较二阶锥松弛、线性加速及商用求解器均具显著优势,兼具较高的计算效率与工程适用性。
Under the strategic objective of carbon emission peak and carbon neutrality
China’s power system is rapidly evolving toward a new paradigm dominated by high-proportion renewable energy
with coal-fired units gradually shifting from base-load to peak-shaving sources. Although the flexible operation of coal-fired power plants enhances system regulation capability
the carbon emission intensity varies significantly under different operating conditions. Consequently
the conventional static emission-factor approach
which assumes constant carbon intensity
becomes inadequate for high-renewable power systems. To address this issue
this paper proposes an optimization method for the power system planning considering the dynamic electricity-carbon coupling characteristics of coal-fired power units
accurately capturing carbon emission variations across operating states. To handle the introduced non-convex and nonlinear coupling constraints
a Taylor-expansion-based iterative algorithm is developed
whose convergence and rate are theoretically proven. Moreover
an improved algorithm without trust-region constraints is designed for the linear carbon-emission representation to further enhance computational efficiency. Case studies on the Garver 6-bus system and a practical 500 kV regional grid in China verify that the proposed method outperforms second-order cone relaxation
linear acceleration
and commercial solvers in both efficiency and stability
demonstrating high computational performance and engineering applicability.
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