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碳感知最优潮流
Carbon-Aware Optimal Power Flow
| 作者 | Xin Chen · Andy Sun · Wenbo Shi · Na Li |
| 期刊 | IEEE Transactions on Power Systems |
| 出版日期 | 2024年12月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 电力系统脱碳 碳感知最优潮流 碳排放流方程 储能系统碳足迹模型 数值模拟 |
语言:
中文摘要
为有效促进电力系统脱碳,本文提出一种通用的碳感知最优潮流(C-OPF)方法,通过主动管理电网碳足迹来支持电力系统决策。该模型在传统最优潮流基础上,融合碳排放流方程与约束及碳相关目标,协同优化电能与碳排放流动。本文严格建立了碳排放流方程可行性和解唯一性的条件,并提出处理功率流向不确定问题的重构方法。此外,构建了两种新型储能系统碳足迹模型并纳入C-OPF框架。数值仿真验证了该方法相较于传统OPF在碳管理方面的有效性与特性优势。
English Abstract
To facilitate effective decarbonization of the electric energy sector, this paper introduces a generic Carbon-aware Optimal Power Flow (C-OPF) methodology for power system decision-making that considers the active management of the grid's carbon footprints. Built upon conventional Optimal Power Flow (OPF) models, the proposed C-OPF model further integrates carbon emission flow equations and constraints, as well as carbon-related objectives, to co-optimize electric power flow and carbon emission flow across the power grid. Essentially, the proposed C-OPF can be viewed as a carbon-aware generalization of OPF. Moreover, this paper rigorously establishes the conditions that guarantee the feasibility and solution uniqueness of the carbon emission flow equations, and it proposes a reformulation technique to address the critical issue of undetermined power flow directions in the C-OPF model. Furthermore, two novel carbon footprint models for energy storage systems are developed and incorporated into the C-OPF method. Numerical simulations demonstrate the characteristics and effectiveness of the C-OPF method, in comparison with conventional OPF solutions.
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SunView 深度解读
该碳感知最优潮流技术对阳光电源PowerTitan储能系统和iSolarCloud云平台具有重要应用价值。C-OPF模型可集成到ST系列储能变流器的能量管理系统中,通过碳排放流方程实时优化充放电策略,在电网低碳时段充电、高碳时段放电,降低系统整体碳足迹。储能碳足迹建模方法可嵌入iSolarCloud平台,为光储一体化项目提供碳排放追踪与优化调度功能,支持碳交易市场参与。该技术还可应用于虚拟电厂VPP场景,协同优化SG光伏逆变器出力、储能充放电和充电桩负荷,实现源网荷储碳感知协调控制,提升阳光电源综合能源解决方案的低碳竞争力和ESG价值。