Forecasting price of electricity emphasizing prices jumps using combination of neural and fuzzy network with particle swarm optimization

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NAZEMI ALI; MAMIPOUR SIAB; RAHIMI SALMAN

Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Advances in Industrial Engineering Year:2018 | Volume:52 | Issue:2 Page(s): 277-290

Download Full-Text

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Verion

View:

1,100

Download:

Cites:

Information Journal Paper

Title

Forecasting price of electricity emphasizing prices jumps using combination of neural and fuzzy network with particle swarm optimization

Author(s)

NAZEMI ALI | MAMIPOUR SIAB | RAHIMI SALMAN | Issue Writer Certificate

Keywords

Forecasting price of electricityQ1

neuralQ2

fuzzy networkQ1

particle swarm optimizationQ1

Abstract

After deregulation in electricity markets, huge amount of studies were done especially in designing new systems and energy pricing in order to improve efficiency of power systems and increase investors’ profit. Investment’ s profit could be increased by better contracts and better price bidding for buying and selling energy in electricity market, as a consequence price forecasting is essential. The main goal of this paper is to predict price of electricity in Iran’ s electricity market, using combined of fuzzy-neural network with particle swarm optimization (PSO). In this paper, past prices, past loads, working and nonworking days, day hours and effect of seasons in 1394 have been taken into account as effective factors in forecasting mechanism. Combined model, is more precise in contrast to other methods like ARIMA, neural network, neural-fuzzy network and combination of fuzzy-neural with genetic algorithm. In following, process of price fluctuations has discussed for improving and increasing effectiveness of bidding. Results of simulation revealed that price forecasting is much more precise with price process mechanism.

Cites

No record.

References

No record.

Cite

APA: Copy

NAZEMI, ALI, MAMIPOUR, SIAB, & RAHIMI, SALMAN. (2018). Forecasting price of electricity emphasizing prices jumps using combination of neural and fuzzy network with particle swarm optimization. ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING), 52(2 ), 277-290. SID. https://sid.ir/paper/166432/en

Vancouver: Copy

NAZEMI ALI, MAMIPOUR SIAB, RAHIMI SALMAN. Forecasting price of electricity emphasizing prices jumps using combination of neural and fuzzy network with particle swarm optimization. ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING)[Internet]. 2018;52(2 ):277-290. Available from: https://sid.ir/paper/166432/en

IEEE: Copy

ALI NAZEMI, SIAB MAMIPOUR, and SALMAN RAHIMI, “Forecasting price of electricity emphasizing prices jumps using combination of neural and fuzzy network with particle swarm optimization,” ADVANCES IN INDUSTRIAL ENGINEERING (JOURNAL OF INDUSTRIAL ENGINEERING), vol. 52, no. 2 , pp. 277–290, 2018, [Online]. Available: https://sid.ir/paper/166432/en

Related Journal Papers