Electrical system load forecasting with polynomial neural networks (based on combinatorial algorithm)

A polynomial neural network model for short term electrical load forecasting (STLF) is developed. Several models use past weekly and monthly system loads to forecast future electrical demands. All models are validated with actual system load data from the Azerbaijani Power Company. Combinatorial alg...

Full description

Saved in:
Bibliographic Details
Main Authors: Huseynov, A. F., Yusifbeyli, N. A., Hashimov, A. M.
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
combinatorial algorithm
Forecasting
Load forecasting
Load modeling
Mathematical model
polynomial neural model
Polynomials
short-term load forecasting (STLF)
time series
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A polynomial neural network model for short term electrical load forecasting (STLF) is developed. Several models use past weekly and monthly system loads to forecast future electrical demands. All models are validated with actual system load data from the Azerbaijani Power Company. Combinatorial algorithm is elaborated to find efficiently the coefficients of regression type model. The paper presents the results, conclusions and points out some directions for future work.