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Medium-Term Electric Load Forecasting Using Multivariable Linear and Non-Linear Regression
| Content Provider | Semantic Scholar |
|---|---|
| Author | Elkarmi, Fawwaz |
| Copyright Year | 2011 |
| Abstract | 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 methodology 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 proposed methods showed that their performance is close and they outperform results obtained using the widely used exponential regression technique. Moreover, peak load prediction has about 90% accuracy using the proposed methodology. The methods are generic and simple and can be implemented to hourly loads of any power system. No extra information other than the hourly loads is required. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://file.scirp.org/pdf/SGRE20110200006_15157345.pdf |
| Alternate Webpage(s) | https://eis.hu.edu.jo/deanshipfiles/pub102722603.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Approximation error Downtime Electrical load Entity Name Part Qualifier - adopted Generic Drugs Html Link Type - copyright Linear model Load profile Mathematical model Numerous Polynomial Projections and Predictions Recommender system Regression Analysis Span Distance cell growth pattern cisplatin/cytarabine/etoposide protocol exponential |
| Content Type | Text |
| Resource Type | Article |
