eprintid: 4832 rev_number: 2 eprint_status: archive userid: 1 dir: disk0/00/00/48/32 datestamp: 2023-11-09 16:16:32 lastmod: 2023-11-09 16:16:32 status_changed: 2023-11-09 15:59:36 type: conference_item metadata_visibility: show creators_name: Hassan, S. creators_name: Khosravi, A. creators_name: Jaafar, J. creators_name: Raza, M.Q. title: Electricity load and price forecasting with influential factors in a deregulated power industry ispublished: pub keywords: Costs; Distributed power generation; Forecasting; Neural networks; Smart power grids; Systems engineering, Demand response programs; Distributed generation technologies; Electricity generation; Forecasting models; Influential factors; Neural network model; Power industry; Price forecasting, Electric load forecasting note: cited By 13; Conference of 9th International Conference on System of Systems Engineering, SoSE 2014 ; Conference Date: 9 June 2014 Through 13 June 2014; Conference Code:114536 abstract: With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response programs are likely to be deteriorated in the absence of accurate load and price forecasting. Electricity generation companies, system operators, and consumers are highly reliant on the accuracy of the forecasting models. However, historical prices from the financial market, weekly price/load information, historical loads and day type are some of the explanatory factors that affect the accuracy of the forecasting. In this paper, a neural network (NN) model that considers different influential factors as feedback to the model is presented. This model is implemented with historical data from the ISO New England. It is observed during experiments that price forecasting is more complicated and hence less accurate than the load forecasting. © 2014 IEEE. date: 2014 publisher: Institute of Electrical and Electronics Engineers Inc. official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908614947&doi=10.1109%2fSYSOSE.2014.6892467&partnerID=40&md5=0a6e161e4834d9fa9ec25c37f78b36ac id_number: 10.1109/SYSOSE.2014.6892467 full_text_status: none publication: Proceedings of the 9th International Conference on System of Systems Engineering: The Socio-Technical Perspective, SoSE 2014 pagerange: 79-84 refereed: TRUE isbn: 9781479952274 citation: Hassan, S. and Khosravi, A. and Jaafar, J. and Raza, M.Q. (2014) Electricity load and price forecasting with influential factors in a deregulated power industry. In: UNSPECIFIED.