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作 者:武晓朦[1] 宋晨曦 WU Xiao-meng;SONG Chen-xi(School of Electronic Engineering,Xi’an Shiyou University,Xi’an 710005,China;Shaanxi Key Laboratory of Oil and Gas Well Measurement and Control Technology,Xi’an 710065,China)
机构地区:[1]西安石油大学电子工程学院,陕西西安710005 [2]陕西省油气井测控技术重点实验室,陕西西安710065
出 处:《电工电气》2020年第3期32-35,共4页Electrotechnics Electric
摘 要:为了解决传统超短期负荷预算方法误差较大的问题,提出一种基于局部模糊推理的区域电力系统超短期负荷预算方法。使用局部模糊推理定义利用的电力系统负荷历史数据,使用序偶法处理负荷数据的模糊集,计算数据的模糊度,得出时点负荷的偏离程度。规定特征时间尺度,依据特征时间尺度的数量关系,预测超短期随机电荷分量,计算电荷分量的均值,形成新的负荷序列,平滑处理得到最终的超短期负荷预算表达式,完成对区域电力系统超短期负荷的预算。实验表明:与传统基于BP神经网络的短期负荷预算方法相比,基于局部模糊推理的区域电力系统超短期负荷预算方法误差率只有0.07%,误差更小,更适合预算区域电力系统的超短期负荷。In order to solve the problem of large errors in traditional ultra-short-term load budget method,a regional power system ultrashort-term load budget method based on local fuzzy reasoning is proposed.Local fuzzy reasoning is used to define the historical load data of the power system,and the fuzzy set of load data is processed using the method of sequence coupling.The sequential couple method is used to process the fuzzy sets of load data,calculate the fuzziness of the data,get the deviation degree of the load at the time point.By specifying the characteristic time scale and predicting the ultra-short-term random charge component according to the quantity relationship of the characteristic time scale,the average value of the charge component is calculated to form a new load sequence,and the smoothing process is used to obtain the final ultra-short-term load budget expression,thereby completing the regional budget for ultra short-term load of the power system.Experiments show that compared with the traditional short-term load budgeting method based on BP neural network,the ultra-short-term load budgeting method of regional power systems based on local fuzzy reasoning has an error rate of only 0.07%,and the error is smaller,which is more suitable for the ultra-short-term load of the budgeted regional power system.
分 类 号:TM715[电气工程—电力系统及自动化]
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