Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression
Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression作者机构：Department of Electronics and Communications Ahlliya Amman University Department of Electrical Engineering The Hashemite University
出 版 物：《Smart Grid and Renewable Energy》 (智能电网与可再生能源（英文）)
年 卷 期：2011年第2卷第2期
页 面：126-135页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Medium-Term Load Forecasting Electrical Peak Load Multivariable Regression And Time Series
摘 要：Medium-term forecasting is an important category of electric load forecasting that covers a time span of up to one year ahead. It suits outage and maintenance planning, as well as load switching operation. We propose a new methodol-ogy that uses hourly daily loads to predict the next year hourly loads, and hence predict the peak loads expected to be reached in the next coming year. The technique is based on implementing multivariable regression on previous year s hourly loads. Three regression models are investigated in this research: the linear, the polynomial, and the exponential power. The proposed models are applied to real loads of the Jordanian power system. Results obtained using the pro-posed methods showed that their performance is close and they outperform results obtained using the widely used ex-ponential regression technique. Moreover, peak load prediction has about 90% accuracy using the proposed method-ology. The methods are generic and simple and can be implemented to hourly loads of any power system. No extra in-formation other than the hourly loads is required.
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