Day ahead hourly load forecast of PJM electricity market and ISO New England market by using artificial neural network

Author

Sahay, Kishan Bhushan ; Tripathi, M.M.

Author_Institution

Dept. of Electr. Eng., Delhi Technol. Univ., New Delhi, India

fYear

2013

fDate

10-13 Nov. 2013

Firstpage

1

Lastpage

5

Abstract

Short-term load forecasting is an essential instrument in power system planning, operation, and control. Many operating decisions are based on load forecasts, such as dispatch scheduling of generating capacity, reliability analysis, and maintenance planning for the generators. This paper discusses significant role of artificial intelligence (AI) in short-term load forecasting (STLF), that is, the day-ahead hourly forecast of the power system load over two weeks. Neural network fitting tool is used to compute the forecasted load. The data to be used in the model are hourly historical data of the temperature and electricity load. The models are trained on hourly data from the ISO New England market and PJM Electricity Market from 2007 to 2011 and tested on out-of-sample data from 2012. The simulation results have shown highly accurate day-ahead forecasts with very small error in load forecasting.

Keywords

ISO standards; learning (artificial intelligence); load forecasting; neural nets; power engineering computing; power markets; AI; ISO New England market; PJM electricity market; STLF; artificial intelligence; artificial neural network fitting tool; day ahead hourly load forecasting; generating capacity dispatch scheduling; maintenance planning; power system control; power system planning; reliability analysis; short-term load forecasting; Artificial neural networks; Data models; Electricity; Electricity supply industry; Load forecasting; Load modeling; Mathematical model; Mean absolute percentage error (MAPE); neural network (NN); power system; short-term load forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovative Smart Grid Technologies - Asia (ISGT Asia), 2013 IEEE

Conference_Location

Bangalore

Print_ISBN

978-1-4799-1346-6

Type

conf

DOI

10.1109/ISGT-Asia.2013.6698744

Filename

6698744