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发明公开
CN105678426A 一种基线预测中相似日最优天数组合的选取方法 无效 - 驳回

一种基线预测中相似日最优天数组合的选取方法
摘要：
本发明公开了一种基线预测中相似日最优天数组合的选取方法，步骤一：相似日的预筛选和相似日天数组合选取；步骤二：相似日组合矩阵进行基线负荷的预测；步骤三：相似日组合矩阵中最优相似日天数组合选取。本发明提供的一种基线预测中相似日最优天数组合的选取方法，充分、合理和有效地利用了历史日数据库，充分挖掘非需求响应因素，量化历史日相似度并排序，通过不同天数组合的误差对比最终确定了相似日最优选取天数组合，其中采用了灰色关联法、综合加权法、多元线性回归法、MRE误差评价等方法的优点，极大地提高了需求响应基线预测的经济性和准确性，为需求响应技术提供了科学理论支持。
摘要（英）：

The invention discloses a method for selecting the optimal day number combination of similar days in baseline prediction, and the method comprises the steps: 1, carrying out the pre-screening of similar days and the selection of a similar day number combination; 2, carrying out the baseline load prediction of a similar day number combination matrix; 3, carrying out the selection of an optimal similar day number combination in the similar day number combination matrix. The method provided by the invention makes full, reasonable and effective use of a historical day number database, fully excavates non-demand response factor, quantifies the historical data similarity, carries out the ordering, and finally determines the optimal similar day number combination through the error comparison of different day number combinations. The method employs the advantages of a gray correlation method, a comprehensive weighting method, an MLR (Multiple Linear Regression) method, and an MRE error evaluation method, greatly improves the economic performance and accuracy of demand response baseline prediction, and provides a scientific theoretical support for the technology of demand response.

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