Next-Day Load Curve Forecasting Using Neural Network Based on Similarity

Authors: Senjyu, Tomonobu; Sakihara, Hirokazu; Tamaki, Yoshinori; Uezato, Katsumi

Source: Electric Power Components and Systems, Volume 29, Number 10, 1 October 2001 , pp. 939-948(10)

Publisher: Taylor and Francis Ltd

Buy & download fulltext article:

OR

Price: $61.16 plus tax (Refund Policy)

Abstract:

In this paper, we propose a neural network approach for next day load curve forecasting based on similarity. The proposed method has the advantage of dealing with not only the nonlinear part of load curve but also with weekend and special day features. The proposed neural network is used to modify the load curve of a similar day by using temperature information. The suitability of the proposed approach is illustrated through an application to actual load data of Okinawa Electric Power Company in Japan.

Keywords: ANNUAL LOAD GROWTH AMOUNT; NEURAL NETWORK; SIMILAR DAY

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/15325000152646541

Publication date: October 1, 2001

More about this publication?
Related content

Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content

Text size:

A | A | A | A
Share this item with others: These icons link to social bookmarking sites where readers can share and discover new web pages. print icon Print this page