欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
负荷预测是电网规划的基础,是电力学科研究中经久不衰的课题。影响负荷动态变化的因素中含有大量不确定性信息,这些信息不能直接用定量的数值表示,使用常规的方法进行负荷预测得到的结果不尽合理。此文应用盲数理论对含有大量不确定性信息的负荷预测进行建模,把影响电力负荷变化的不确定性信息描述为指标因素,比较各个因素对负荷变化区间的影响并且用数值来定量表征,得到变化区间在各因素指标下的相对评价向量,构造出判断矩阵。求解判断矩阵的最大特征值及其对应的非零特征向量,并对非零特征向量进行归一化处理得到各负荷变化区间的可信度,取区间灰数的均值作为其白化值,以各负荷变化区间的可信度为权系数进行加权平均得到负荷预测值,从而将不确定信息量化。将该方法对昆明地区电网“九五”、“十五”的负荷数据进行校验,结果表明该方法有效。最后将该方法应用于昆明电网的“十一五”规划中。
英文摘要：
The load forecast is basis on which the electrical network plan is worked out, and also is a topic that has been discussed and studied for a lone time in the electric power discipline research. The factors which have influence on load dynamic change include large amount of uncertain information. These information cannot be directly represented by quantitative data and use of the traditional method to carry out load forecast leaves much to be desired. This paper applies the unascertained number theory to modelling of the load foresting which includes large amount of uncertain information to describe the uncertain information that has influence on power load variation by means of index factors and to compare the influence on the interval power load variation exerted by each factor and characterize them in value quantitatively. Thus the relative appraisal vector of interval variation under various factor indexes can be obtained and the judgement matrix can be modelled. Credibility of various interval power load variation can be obtained by solving the maximum characteristic value of the judgement matrix and its corresponding non - vanishing characteristic vector taking the ash number as white vector. Then the load forecast value can be obtained by taking the credibility of various interval load variation as a weight coefficient for weight averaging, thus the uncertain information can be quantitated. This method has been verified with the load data of Kunming regional power network in ＂the ninth - five year＂ and ＂the tenth - five year＂ periods. The method has proved effective and will be applied to planning of Kunming power network for ＂the eleventh - five year＂ period.
同期刊论文项目
同项目期刊论文
期刊信息
位置：