袁铁江, 张文达, 田雪沁, 毛雅铃. 电夹点——完全能量目标下弃电最小的电源规划方法研究[J]. 中国电机工程学报, 2025, 45(8): 2925-2935. DOI: 10.13334/j.0258-8013.pcsee.232319
引用本文: 袁铁江, 张文达, 田雪沁, 毛雅铃. 电夹点——完全能量目标下弃电最小的电源规划方法研究[J]. 中国电机工程学报, 2025, 45(8): 2925-2935. DOI: 10.13334/j.0258-8013.pcsee.232319
YUAN Tiejiang, ZHANG Wenda, TIAN Xueqin, MAO Yaling. Electrical Pinch Point——Study on the Power Planning Method for Minimizing Power Abandonment Under Complete Energy Objective[J]. Proceedings of the CSEE, 2025, 45(8): 2925-2935. DOI: 10.13334/j.0258-8013.pcsee.232319
Citation: YUAN Tiejiang, ZHANG Wenda, TIAN Xueqin, MAO Yaling. Electrical Pinch Point——Study on the Power Planning Method for Minimizing Power Abandonment Under Complete Energy Objective[J]. Proceedings of the CSEE, 2025, 45(8): 2925-2935. DOI: 10.13334/j.0258-8013.pcsee.232319

电夹点——完全能量目标下弃电最小的电源规划方法研究

Electrical Pinch Point——Study on the Power Planning Method for Minimizing Power Abandonment Under Complete Energy Objective

  • 摘要: 新能源的时序波动特性是新型电力系统建设过程中面临的重大难题,以电能供需平衡的完全能量目标有望在保障系统安全可靠运行方面发挥重要作用。为此,提出一种全新电源规划方法——电夹点分析法。首先,考虑新能源出力及负荷的时序特性,提出以功率值和风险度作为电夹点分析中反映电力流量和电力品质的关键指标,用于描述新能源与负荷的匹配关系;其次,构建电夹点分析的电源规划模型,分别给出表格化和图形化计算步骤,求取规划方案解析解;最后,以甘肃电网实际数据进行算例分析。结果表明,所提方法在保证区域弃电最小的前提下,既能合理规划电源结构,又能确定灵活性火电装机规模,同时极大提高模型求解速度,为新型电力系统规划研究提供一种新的解决思路和参考。

     

    Abstract: The temporal variability of renewable energy poses significant challenges for new power system development. A complete energy framework for supply-demand balance is crucial for ensuring power system reliability. This paper proposes a novel planning method-electrical pinch analysis. First, considering the temporal characteristics of renewable output and load, we introduce power value and risk degree as key indicators in the pinch analysis, reflecting power flow and quality to characterize renewable-load matching. Second, we develop a graphical power planning model for pinch analysis, presenting both tabular and graphical calculation procedures. Finally, using actual Gansu grid data for case studies, results demonstrate this method can effectively optimize power structure and determine flexible thermal capacity while minimizing regional curtailment. The approach significantly enhances computational efficiency, offering new insights for power system planning research.

     

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