Volume 19, Issue 1 (JIAEEE Vol.19 No.1 2022)
Journal of Iranian Association of Electrical and Electronics Engineers 2022, 19(1): 307-318 |
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Kaheh Z, Shabanzadeh M. Effect of Information Ensemble on Electricity Load Forecasting by Proposing a Novel Hierarchical Forecasting Method. Journal of Iranian Association of Electrical and Electronics Engineers 2022; 19 (1) :307-318
URL: http://jiaeee.com/article-1-1450-en.html
URL: http://jiaeee.com/article-1-1450-en.html
Department of Power System Operation and Planning,Niroo Research Institute (NRI)
Abstract: (1274 Views)
To forecast the electricity load of a city or country and facilitate the strategic decision-making, it is common to collect the historical data from different zones of the city or different cities of the country. However, normally all the zones or different sectors’ load (residential, industrial, and commercial) are not important equally. In other words, a certain zone or a sector may have the most effect on decision making. Therefore, the simple algebraic sum of the different zones’ forecasting may not be meaningful for the ultimate objective. There are different methods for aggregation of the different zones’ forecasts. The most convenient method is the simple algebraic sum of the different zones’ forecasts, which is not only inefficient but also needs more details about the effective factors on the electricity demand in each zone. In this paper, different aggregation approaches such as bottom-up, top-down, optimal combination methods are presented. It should be mentioned that any research paper in the field of the electrical power system and load forecasting have not studied the hierarchical forecasting; therefore, presenting the hierarchical method for load forecasting is a strict innovation of this paper. The Auto-Regressive Integrated Moving Average (ARIMA) and Exponential Smoothing methods are embedded in proposed aggregation approaches. The proposed methods are applied to forecast Australian electric load in short-term and long-term horizons.
Type of Article: Research |
Subject:
Power
Received: 2018/07/16 | Accepted: 2018/11/17 | Published: 2022/04/14
Received: 2018/07/16 | Accepted: 2018/11/17 | Published: 2022/04/14
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