基于Sigmoid函数的负荷-温度模型及灵敏度分析方法

随着以空调、电暖器等为代表的温度敏感负荷的大量新增，温度与用电负荷的相关性关系愈加复杂。通过实例说明温度累积效应对负荷变化的影响，并在此基础上考虑待分析日当日及其前 2 日温度对当日负荷的影响，提出了考虑温度累积效应的修正温度模型。基于 Sigmoid 曲线将日期类型和日期序号量化，建立了负荷-温度拟合数学模型。对于2个模型中的待定系数分别以负荷-温度相关性最高及整体拟合 误 差 最 小 为 目 标 函 数 ，采 用 模 拟 退 火 法（simulatedannealing，SA）进行求解。采用部分地市实际负荷与温度数据进行测试验证，结果证明负荷-温度拟合模型能在全温度区间内具有较好的拟合精度，且采用修正温度后，拟合误差大大减小。通过负荷-温度拟合模型分别得到了采用实际温度与修正温度下温度对负荷变化的灵敏度曲线，其中采用修正温度的灵敏度曲线更全面地量化了相邻历史2日内温度变化对负荷的影响。研究结果为更精细、更准确地量化温度变化对负荷变化的影响提供了充分的理论依据。

Load-temperature model and sensitivity analysis method based on Sigmoid function

With the increasing number of temperature sensitive load such as air conditioning, electric heaters has become available, the relationship between temperature and power load is more and more significant and complex. An example is given to illustrate the effect of temperature accumulation effect on load change. On this basis, the influence of temperature on load on the day to be analyzed and its premier two days is also considered, and a modified temperature model considering temperature accumulation effect is proposed. Based on Sigmoid curve and quantization of date type, date serial number, a load-temperature fitting mathematical model is established. The undetermined coefficients in the two models are solved by simulated annealing with the maximum load-temperature similarity and the minimum global fitting error as the objective functions. The actual load and temperature data of some cities in a province are used for testing and verification. The results prove that the load - temperature fitting model proposed can have good fitting accuracy in the whole temperature range, and the fitting error is further reduced after the modified temperature is adopted. Sensitivity curve of temperature to load change has been obtained respectively through the load-temperature fitting model using the actual temperature and the corrected temperature, including the sensitivity of the modified temperature curve for more comprehensive quantitative history two adjacent temperature change on the influence of load, research results for more sophisticated,more accurate quantitative temperature change on the influence of load change provides a sufficient theoretical basis.