An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales
Joint Authors
Jiang, Ping
Zhou, Qingping
Jiang, Haiyan
Dong, Yao
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-03
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
With rapid economic growth, electricity demand is clearly increasing.
It is difficult to store electricity for future use; thus, the electricity demand forecast, especially the electricity consumption forecast, is crucial for planning and operating a power system.
Due to various unstable factors, it is challenging to forecast electricity consumption.
Therefore, it is necessary to establish new models for accurate forecasts.
This study proposes a hybrid model, which includes data selection, an abnormality analysis, a feasibility test, and an optimized grey model to forecast electricity consumption.
First, the original electricity consumption data are selected to construct different schemes (Scheme 1: short-term selection and Scheme 2: long-term selection); next, the iterative algorithm (IA) and cuckoo search algorithm (CS) are employed to select the best parameter of GM(1,1).
The forecasted day is then divided into several smooth parts because the grey model is highly accurate in the smooth rise and drop phases; thus, the best scheme for each part is determined using the grey correlation coefficient.
Finally, the experimental results indicate that the GM(1,1) optimized using CS has the highest forecasting accuracy compared with the GM(1,1) and the GM(1,1) optimized using the IA and the autoregressive integrated moving average (ARIMA) model.
American Psychological Association (APA)
Jiang, Ping& Zhou, Qingping& Jiang, Haiyan& Dong, Yao. 2014. An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1013434
Modern Language Association (MLA)
Jiang, Ping…[et al.]. An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales. Abstract and Applied Analysis No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-1013434
American Medical Association (AMA)
Jiang, Ping& Zhou, Qingping& Jiang, Haiyan& Dong, Yao. An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-1013434
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1013434