考虑碳流约束的电力系统能碳安全域模型与计算方法OA北大核心CSTPCD
Model and Calculation Method of Energy-Carbon Security Region for Power System Considering Carbon Flow Constraints
针对当前电力系统碳减排任务与安全稳定运行需求,研究电力系统低碳安全运行技术.现有的能量流安全域模型使电力系统安全监视与控制更加科学有效,但忽略了系统运行过程中可能存在的"高碳"风险.文中提出了一种考虑碳流约束的电力系统能碳耦合安全域(简称能碳安全域)模型与计算方法,旨在保证系统安全性的同时减排提效.为完整刻画电力系统的低碳运行能力极限,分别从负荷端和源端角度提出了考虑碳流约束的系统最大供电能力曲线及最大消纳能力曲线模型.基于系统最大供电能力工作点,提出了能碳安全边界仿真拟合计算方法,实现了能碳安全域的降维观测.最后,结合算例验证了所提模型的有效性.
Aiming at the current carbon emission reduction tasks and the safe and stable operation requirements of the power system,the low-carbon safe operation technology of the power system is studied.The existing energy flow security region model makes security monitoring and control more scientific and effective,but it ignores the potential"high carbon"risk during system operation.Based on this,a model and calculation method for the energy and carbon coupled security region(referred to as the energy-carbon security region)considering carbon flow constraints are proposed,aiming to ensure system security while reducing emissions and improving efficiency.To fully characterize the low-carbon operation capability limit of the power system,the total supply capability curve and total accommodation capability curve models of the power system considering carbon flow constraints are proposed from the perspectives of load and source ends,respectively.Based on the working point of the total supply capability,the simulation fitting calculation method of the energy-carbon safety boundary is proposed,and the dimension reduction observation of the energy-carbon security region is realized.Finally,the validity of the proposed model is verified by combining the cases.
刘浩;王丹;肖峻;贾宏杰;林溪桥;何承瑜
智能电网教育部重点实验室(天津大学),天津市 300072智能电网教育部重点实验室(天津大学),天津市 300072||天津市智慧能源与信息技术重点实验室(天津大学),天津市 300072广西电网有限责任公司,广西壮族自治区 南宁市 530023
低碳电力技术碳约束安全域最大供电能力曲线最大消纳能力曲线
low-carbon electricity technologycarbon constraintsecurity regiontotal supply capability curvetotal accommodation capability curve
《电力系统自动化》 2024 (003)
10-21 / 12
国家自然科学基金资助项目(51977141);国家重点研发计划资助项目(2018YFB0905000);国家电网公司总部科技项目(SGTJDK00DWJS1800232). This work is supported by National Natural Science Foundation of China(No.51977141),National Key R&D Program of China(No.2018YFB0905000),and State Grid Corporation of China(No.SGTJDK00DWJS1800232).
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