Quantitative Analysis of the Relationship between Temperature and Power Load

Jian Liang Zhong; Bei Zhao; Da Zhang; Hai Bao

doi:10.4028/www.scientific.net/AMR.986-987.428

Paper Titles

Optimizing the Allocation of the Relay Setting Related to Power Grid and over Frequency Generator Tripping Scheme
p.404

Power Control of Microgrid with Rich Small Hydropower Stations
p.412

Power Distribution System Evaluation in Chemical Industry Park Using Subjective and Objective Comprehensive Weight Method
p.419

Power System Planning by Simulation
p.424

Quantitative Analysis of the Relationship between Temperature and Power Load
p.428

Reactive Compensation Research of HVAC Cables for Offshore Wind Farms
p.433

Reliability Evaluation Research of 10 kV Typical Configuration Feeder Based on the FMEA
p.439

Research and Simulation of Reasonable Distribution of Energy Saving Design Model in Rural Residential
p.445

Research for Smart Micro-Grid System of Optimal Operation on the Island
p.449

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 986-987Quantitative Analysis of the Relationship between...

Quantitative Analysis of the Relationship between Temperature and Power Load

Abstract:

This paper presents the results of a study regarding the relationship between temperature and power load of the electric power system. Weather-influenced load part is picked up from original load series data with the conclusion that the lagged effect of temperature on load is within 12 hours. Furthermore, decision tree and step regression methods are employed to get a group of decision trees and corresponding regression equations which are able to quantitatively describe the relationship between load and temperature. A short-term load forecasting algorithm is then developed and its practical implementation shows this quatitative analysis method could reliably reflect the influence of the temperature changes on the load and effectively improve the accuracy of short-term load forecasting.

You might also be interested in these eBooks

Energy Research and Power Engineering 2014

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 986-987)

Pages:

428-432

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.986-987.428

Citation:

Cite this paper

Online since:

July 2014

Authors:

Jian Liang Zhong*, Bei Zhao, Da Zhang, Hai Bao

Keywords:

Decision, Forecasting, Load, Tree Step Regression

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Palacio, D.R. Simple model for load forecast weather sensitive Electricity Distribution, 2001. Part 1: Contributions[C]. CIRED. 16th International Conference and Exhibition (IEE Conf. Publ No. 482) , Volume: 4 , 18-21 June 2001 Page(s): 3 pp. vol. 4.

DOI: 10.1049/cp:20010861

Google Scholar

[2] Sforna M. Searching for the Electric-Load Weather Temperature Function By Using the Group Method of Data Handling. Electric Power Systems Research, 1995: 32 (1) 1-9.

DOI: 10.1016/0378-7796(94)00891-7

Google Scholar

[3] Kang Chongqing Cheng Xu Xia Qing shen Yu. A New Unified Approach to Short-Term Load Forecasting Considering Correlated Factors[J]. Automation of Electrical Power Systems, 1999: 23(18) 32-35.

Google Scholar

[4] Khotanzad A, Afkhami-Rohani R, Maratukulam D. ANNSTLF-artificial neural network short-term load forecaster generation three[J]. Power Systems, IEEE Transactions on, 1998: 13(4): 1413-1422.

DOI: 10.1109/59.736285

Google Scholar

[5] Chow T W S, Leung C T. Neural network based short-term load forecasting using weather compensation[J]. Power Systems, IEEE Transactions on, 1996: 11(4): 1736-1742.

DOI: 10.1109/59.544636

Google Scholar

[6] Hyde O, Hondnett PF. Modelling the effect of weather in short-term electricity load forecasting. MATHEMATICAL ENGINEERING IN INDUSTRY, 1997: 6 (2): 155-169.

Google Scholar