GAO Ronggang, YANG Yang, YUAN Tiejiang, et al. Data driven load partition for energy storage capacity configuration[J]. Thermal power generation, 2020, 49(8): 97-103.
GAO Ronggang, YANG Yang, YUAN Tiejiang, et al. Data driven load partition for energy storage capacity configuration[J]. Thermal power generation, 2020, 49(8): 97-103. DOI: 10.19666/j.rlfd.202002083.
面向储能容量配置数据驱动的负荷分区
摘要
针对负荷分布对储能应用目标和容量需求的影响
提出面向储能容量配置的负荷分区新方法。根据电网负荷与新能源出力的特点
将峰谷隶属度作为代表负荷特性的指标
将新能源反调峰与大波动性作为代表新能源出力的指标
用这2种指标进行模糊聚类得出负荷分区。最后
结合新疆新能源并网系统实际运行数据
对上述负荷分区方法进行仿真验证。结果显示
在储能容量配置时利用该分区方法为储能充放电功率控制模型提供准确的负荷分区
可以抑制新能源的反调峰和大波动性
并增加电网消纳新能源的能力。
Abstract
In view of the influence of load distribution on energy storage application target and capacity demand
a new load zoning method for energy storage capacity allocation is proposed. According to the characteristics of power grid load and new energy output
the peak valley subordination degree is taken as the index of load characteristics
and the new energy anti peak regulation and large fluctuation are taken as the indexes of new energy output. The fuzzy clustering of these two indexes is used to obtain the load partition. Finally
combined with the actual operation data of Xinjiang new energy grid connected system
the above load zoning method is simulated and verified. The results show that
when allocating the energy storage capacity
using this zoning method to provide accurate load zoning for the energy storage charging and discharging power control model can suppress the anti peak regulation and large wave dynamics of new energy sources
and increase the capacity of the power grid to absorb new energy.