A new recursive neural network algorithm to forecast electricity price for PJM day-ahead market

Journal article

Peer reviewed

Paras MANDAL, Anurag K SRIVASTAVA, Tomonobu SENJYU and Michael NEGNEVITSKY

International journal of energy research, Vol.34(6), pp.507-522

2010

Handle:

https://hdl.handle.net/2376/101070

Abstract

Energy

Applied sciences

Exact sciences and technology

7 Record Views

Title: A new recursive neural network algorithm to forecast electricity price for PJM day-ahead market
Creators: Paras MANDAL - Center for Renewable Energy and Power Systems (CREPS), University of Tasmania, Hobart, Tasmania 7001, Australia
Anurag K SRIVASTAVA - Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762, United States
Tomonobu SENJYU - Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
Michael NEGNEVITSKY - Center for Renewable Energy and Power Systems (CREPS), University of Tasmania, Hobart, Tasmania 7001, Australia
Publication Details: International journal of energy research, Vol.34(6), pp.507-522
Academic Unit: Electrical Engineering and Computer Science, School of
Publisher: Wiley; Chichester
Identifiers: 99900546560501842
Language: English
Resource Type: Journal article