Load Estimation for Electric Power Distribution Networks

Authors: Chiebuka Eyisi, Saeed Lotfifard

Presented at the 46th Power Sources Conference 2014 15.3

Abstract: Distribution Load Estimation (DLE) is a key function of Distribution Management System (DMS). In this paper a novel method for presenting historical load data in the form of Representative Load Curves (RLC) is presented. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is used in this regard to estimate the RLC. Accurate RLCs provide better pseudo-measurements for real-time load estimation in distribution networks. The performance of the proposed method is demonstrated on an 11kV radial distribution network with the aid of the MATLAB software. The mean absolute percent error (MAPE) criterion is used to quantify the accuracy of the estimated RLC.

Submitted to arXiv on 20 Sep. 2021

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.