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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/37744

Title: Applying Innovative Models for Forecasting Small-Area Peak Electricity Loads
Authors: Fung-Fei Chen
Seng-Cho Chou
Tai-Ken Lu
Contributors: 國立臺灣海洋大學:電機工程學系
Keywords: End-User Method
Least Square (LS)
Load Forecasting
Regression Tree
Date: 2013-01
Issue Date: 2016-05-02T07:52:12Z
Publisher: Applied Mechanics and Materials
Abstract: Abstract:the number of Distributed generators is currently increasing, and the electrical industry is trending toward regional supply-and-demand and resource integration. Thus, a model that can forecast small-area peak electrical loads is an indispensable part of power infrastructures. This study constructs innovative model for forecasting small-area peak electrical loads. The main aspects considered were the accuracy of the forecasting model and the convenience of follow-up maintenance and management of the model and data. This study used yearly peak load value and total power data from substations to construct regression tree models. These acted as models for the small-region peak electrical load of substation districts in the Taipower distribution systems. The errors of these forecasting models were substantially smaller than those of the least squares model originally used by Taipower to forecast peak load. The addition of exogenous factors was unnecessary. Additionally, our results were superior regardless of whether once or incremental models were adopted for the data. This confirms the usability of our models.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/37744
Appears in Collections:[電機工程學系] 期刊論文

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