王正龙, 王可宏, 王映丹. 一种考虑风-光-电负荷不确定集与线性化的综合能源系统优化调度[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0420
引用本文: 王正龙, 王可宏, 王映丹. 一种考虑风-光-电负荷不确定集与线性化的综合能源系统优化调度[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0420
WANG Zhenglong, WANG Kehong, WANG Yingdan. An Integrated Energy System Optimal Scheduling Considering Wind-Light-Electricity Load Uncertainty Set and Linearization[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0420
Citation: WANG Zhenglong, WANG Kehong, WANG Yingdan. An Integrated Energy System Optimal Scheduling Considering Wind-Light-Electricity Load Uncertainty Set and Linearization[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0420

一种考虑风-光-电负荷不确定集与线性化的综合能源系统优化调度

An Integrated Energy System Optimal Scheduling Considering Wind-Light-Electricity Load Uncertainty Set and Linearization

  • 摘要: 为促进风-光-电负荷功率不确定的综合能源系统的风、光功率消纳,降低碳排放,首先,考虑风、光波动性和弃风、弃光现象构建风、光功率不确定集,考虑电价波动性和负荷需求响应弹性系数构建电负荷的价格型需求响应不确定集;其次,进一步提出排序截断分摊法,将风、光、电负荷功率不确定集转化为可线性求解的线性对应式;第三,建立热电联产机组-碳捕集系统联合运行系统,并推导系统整体模型,该整体模型只关注系统对外能量交互情况;第四,构建风、光、电负荷功率不确定的IES优化模型,并在多场景下分析其风、光功率消纳和碳排放。最后,利用算例证明了所提方法的有效性。

     

    Abstract: To promote wind and light power consumption of wind-light-electric load power uncertainty in the integrated energy system and reduce carbon emissions, firstly, a wind and light power uncertainty set was constructed considering the wind and light volatility and the phenomenon of wind and light abandonment; a price-based demand response uncertainty set of the electric load was constructed considering electricity price volatility and load demand response elasticity coefficient. Secondly, a sorting truncated apportionment method was proposed to convert an uncertain set of wind, light, and electricity load power into a linear corresponding formula that can be solved linearly. Thirdly, a combined heat and power (abbr. CHP) unit-carbon capture system was established, and derived an overall model of the system, which only focuses on the external energy interaction of the system. Fourthly, an integrated energy system (abbr. IES) optimization model for wind, light, and electric load power uncertainty was constructed, and their wind and light power consumption and carbon emissions in multiple scenarios were analyzed. Finally, the effectiveness of the proposed method is demonstrated using arithmetic examples.

     

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