Research of non-intrusive grid load profile based on big data of renewable energy - CUI Shuchun; LI Haitao; YANG Yongbiao (Diance yu yibiao)
Grid expansion planning is a key issue of the construction of current smart grid. Considering the characteristics of grid expansion planning problem, a scheme for non-intrusive grid load profile modeling considering big data of regional renewable energy is proposed. Based on autoregressive model reflecting temporal linear relations, this method depicts the load at the user end. Furthermore, considering the mass introduction of renewable energy including photovoltaic units and wind power generator in future grid expansion, the meteorological characteristics is integrated into the calculation of load profile. Experimental results on real world data indicate the validity of the proposed model for the representation of load profile, and the reference value for grid expansion planning.