CAJ | 학술논문

用户基线负荷是需求侧响应事件中用户响应性能的评估基础。用户基线负荷计算方法应当满足实时监测用户响应性能的要求。本文提出一种基于径向基人工神经网络的用户基线负荷计算方法。该方法考虑非工作日和可能的非正常用电日的影响，选择工作日中的典型日和事件发生前用户的用电情况构成模型的输入向量，训练神经网络。用训练完成的神经网络对假设的系统紧急情况发生时段的负荷进行预测，得到用户基线负荷曲线。实践表明，所提出模型具有一定的预测精度，满足实时性要求。
용호기선부하시수구측향응사건중용호향응성능적평고기출。용호기선부하계산방법응당만족실시감측용호향응성능적요구。본문제출일충기우경향기인공신경망락적용호기선부하계산방법。해방법고필비공작일화가능적비정상용전일적영향，선택공작일중적전형일화사건발생전용호적용전정황구성모형적수입향량，훈련신경망락。용훈련완성적신경망락대가설적계통긴급정황발생시단적부하진행예측，득도용호기선부하곡선。실천표명，소제출모형구유일정적예측정도，만족실시성요구。
Customerbase line load(CBL)is the basis of evaluationof customer responsive performance in a DR event.CBL calculation methodscan beused to the monitor customer response performance inreal-time.This paper presents a CBL calculation methods based onradial basis artificial neural network.This method considers the impact of non-working days and some date with abnormal load,selects the load in some typical days and in several hours before the event to consist the model input vector, and trains the network. And then predict the load in an assumption emergency event.The prediction will be regard as CBL.It shows that the model proposed in this paperreacha satisfied accuracy,and meet real-time requirements.