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面向双碳目标的电力系统规划方案量化归因分析方法 被引量:7

Quantitative Attribution Analysis Method of Power System Planning Scheme for Carbon Emission Peak and Carbon Neutrality Goals
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摘要 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-6bus test system and Northwest China power system for carbon neutrality goals, where the results confirm the feasibility and effectiveness of the proposed method.
作者 卓振宇 张宁 康重庆 蒋维勇 王智冬 ZHUO Zhenyu;ZHANG Ning;KANG Chongqing;JIANG Weiyong;WANG Zhidong(National Key Laboratory of New Power System Operation and Control,Tsinghua University,Beijing 100084,China;State Grid Economic and Technological Research Institute Co.,Ltd.,Beijing 102209,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2023年第2期1-14,共14页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(52130702) 国家电网公司科技项目(5100-202256029A-1-1-ZN)。
关键词 双碳 量化归因 电力系统规划 储能 可再生能源 carbon emission peak and carbon neutrality quantitative attribution power system planning energy storage renewable energy
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