Forecasting and Studies on Load Characteristics of Nanjing Center Area Power Network

doi:10.11930/j.issn.1004-9649.2016.02.067.06

Abstract

Abstract: Load characteristics and various contribution factors in city distribution network are analyzed. In order to overcome edge effect problems in Elman neural network of load forecasting method, a new short-term forecasting model is proposed by training strategy improvement. This model adopts multiple-hidden-layer networks and dynamic neural networks element as forecasting method, generating results by comparing different forecasting results of neural networks element. The testing results prove the adaptability and accuracy of proposed method under different conditions. It provides a feasible alternative for short-term forecasting of city central area power network.

Key words: load characteristics, short-term forecasting, Elman neural network, training strategy

CLC Number:

TM715

ZHU Bin, JIANG Ning, HUO Xuesong, WANG Yong, WU Haiwei, SUN Kaiqi, HU Shuang. Forecasting and Studies on Load Characteristics of Nanjing Center Area Power Network[J]. Electric Power, 2016, 49(2): 67-72.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.2016.02.067.06

https://www.electricpower.com.cn/EN/Y2016/V49/I2/67

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