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1.新型电力系统运行与控制全国重点实验室,清华大学,北京市 100084
2.国网经济技术研究院有限公司,北京市 102209
Received:10 January 2022,
Revised:2022-06-15,
Published Online:22 November 2022,
Published:25 January 2023
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卓振宇,张宁,康重庆等.面向双碳目标的电力系统规划方案量化归因分析方法[J].电力系统自动化,2023,47(2):1-14.
ZHUO Zhenyu,ZHANG Ning,KANG Chongqing,et al.Quantitative Attribution Analysis Method of Power System Planning Scheme for Carbon Emission Peak and Carbon Neutrality Goals[J].Automation of Electric Power Systems,2023,47(2):1-14.
卓振宇,张宁,康重庆等.面向双碳目标的电力系统规划方案量化归因分析方法[J].电力系统自动化,2023,47(2):1-14. DOI: 10.7500/AEPS20220110006.
ZHUO Zhenyu,ZHANG Ning,KANG Chongqing,et al.Quantitative Attribution Analysis Method of Power System Planning Scheme for Carbon Emission Peak and Carbon Neutrality Goals[J].Automation of Electric Power Systems,2023,47(2):1-14. DOI: 10.7500/AEPS20220110006.
面向双碳目标的电力系统规划需要在众多新安全挑战与低碳技术耦合的背景下进行系统发展的决策分析。各项低碳技术在电力系统低碳转型方案中起到的作用尚不明确且无法量化。在此背景下,相比于仅求得最优的规划方案,进一步理解规划模型给出规划方案的原因并且明确其带来的效益对规划者十分重要。文中针对电力系统规划问题引入了量化归因的概念,并提出了基于路径积分的规划方案量化归因方法,用以对各项设备带来的潜在效益进行分析。应用该方法对Garver-6节点测试系统和中国西北电力系统的“碳中和”规划结果进行了量化归因分析,结果验证了所提方法的可行性与有效性。
Power system planning for carbon emission peak and carbon neutrality goals needs to make decisions on system development with the coupling of numerous new security challenges and low-carbon technologies. The roles of various low-carbon technologies in the low-carbon transition of the power system are unclear and cannot be quantified. In this context
it is critical for planners to further understand the reasons why the planning model gives the planning scheme and to clarify the benefits it brings
rather than only providing the optimal planning solution. This paper introduces the concept of quantitative attribution to the field of power system planning
and a quantitative attribution method based on path integral is proposed to analyze the potential benefits brought by various devices. The method is applied to the quantitative attribution analysis of the planning results for the Garver-6 bus test system and Northwest China power system for carbon neutrality goals
where the results confirm the feasibility and effectiveness of the proposed method.
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