【摘要】：針對電力負(fù)荷密度預(yù)測中收集大量有效數(shù)據(jù)樣本困難以及專家一次性評判難以獲得合理結(jié)果的問題,提出了一種以方案比較沖突度為度量指標(biāo)的交互式專家語言評判電力負(fù)荷密度預(yù)測法。該方法在采用語言評判方式評價城市小區(qū)不同類型指標(biāo)時,以方案比較沖突度來度量專家在評判小區(qū)某指標(biāo)更優(yōu)(更劣)時的沖突程度,從中選取沖突較大的小區(qū),以一致度標(biāo)準(zhǔn)修改其評價信息和專家權(quán)重,實現(xiàn)專家之間的交互式評判,并在預(yù)測時,將交互后的評價信息經(jīng)信息集成算子集成后同負(fù)荷密度代入BP神經(jīng)網(wǎng)絡(luò)中訓(xùn)練,以訓(xùn)練后的結(jié)構(gòu)預(yù)測城市各小區(qū)的負(fù)荷密度。算例表明,該方法不僅能有效解決缺乏數(shù)據(jù)的問題,同時能克服交互式?jīng)Q策中僅從整體角度考慮專家一致性問題的局限性,具有很好的實踐意義。
[Abstract]:In order to solve the problem that it is difficult to collect a large number of effective data samples in power load density forecasting and it is difficult for experts to obtain reasonable results in one-off evaluation, An interactive expert language evaluation method for power load density forecasting based on the conflict degree of scheme comparison is proposed in this paper. When the language evaluation method is used to evaluate different types of indicators in urban residential areas, the conflict degree of experts is measured when a certain index is better (worse), and the community with greater conflict is selected from the conflict degree. The evaluation information and expert weight are modified by consistency standard to realize the interactive evaluation among experts. In the prediction, the interactive evaluation information is integrated by information integration operator and the same load density is replaced into BP neural network for training. The structure after training is used to predict the load density of each district in the city. Numerical examples show that this method can not only effectively solve the problem of lack of data, but also overcome the limitation of considering the consistency of experts only from the whole point of view in interactive decision-making, which has a good practical significance.
【作者單位】： 智能電網(wǎng)運行與控制湖南省重點實驗室(長沙理工大學(xué));國網(wǎng)湖南省電力公司;
【基金】：國家自然科學(xué)基金資助項目(51277016,71331001)
【分類號】：TM715

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