Abstract
The estimation of losses of distribution feeders plays a crucial guiding role for the planning, design, and operation of a distribution system. This paper proposes a novel estimation method of statistical line loss of distribution feeders using the feeder cluster technique and modified eXtreme Gradient Boosting (XGBoost) algorithm that is based on the characteristic data of feeders that are collected in the smart power distribution and utilization system. In order to enhance the applicability and accuracy of the estimation model, k-medoids algorithm with weighting distance for clustering distribution feeders is proposed. Meanwhile, a variable selection method for clustering distribution feeders is discussed, considering the correlation and validity of variables. This paper next modifies the XGBoost algorithm by adding a penalty function in consideration of the effect of the theoretical value to the loss function for the estimation of statistical line loss of distribution feeders. The validity of the proposed methodology is verified by 762 distribution feeders in the Shanghai distribution system. The results show that the XGBoost method has higher accuracy than decision tree, neural network, and random forests by comparison of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Absolute Percentage Error (APE) indexes. In particular, the theoretical value can significantly improve the reasonability of estimated results.
Highlights
Line loss rate is a comprehensive technical and economic index, which reflects the level of planning, design, and operation of power system
The statistical line loss of distribution feeders and its related data mainly comes from production management system (PMS) and customer management system (CMS)
The principal novelty of the estimation model proposed is to enhance the reasonability of estimated results of statistical line loss by considering the auxiliary function of the theoretical line loss
Summary
Line loss rate is a comprehensive technical and economic index, which reflects the level of planning, design, and operation of power system. It plays a crucial guiding role for optimization of power network structure and saving energy. The loss of 10 kV medium voltage distribution networks accounted for 24.7% of total losses of the power grids, according to the measured result provided by. The earliest research on loss estimation of a distribution system primarily concentrated on the methods based on load curves and load profile: percent loading [2], statistical features of daily load curves (DLC) [3], and improved statistical representation of the influence of DLCs on power flow of radial distribution networks using average node voltages [4]. Reference [5] estimated the Energies 2017, 10, 2067; doi:10.3390/en10122067 www.mdpi.com/journal/energies
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
