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Prediction Model for Iran's Electricity Market Clearing Pricees: Improved SVM Algorithm
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Omid Motamedi   , Bakhtiar Ostadi * , Ali Husseinzadeh Kashan |
| Tarbiat Modares University |
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Abstract: (3717 Views) |
| Since the formation of the Iranian electricity market in 1382 (2003), power plants have been competing with each other on a daily basis in the ISO by registering their bid prices. In this competition, the winners are those power plants whose bid prices are lower than the market clearing price for each hour in the next day, so the forecasting the next day market prices is vital for energy producers. In this study, using a combination of K-means algorithm and support vector machine, a new model for predicting the next day market settlement prices is proposed and the model has been used the hourly electricity market prices for 1395-1396 (2016-2017). According to the results, seven competitive clusters were identified for the Iranian electricity market. The average forecasting accuracy of the proposed model for each of these clusters for the years 1395 (2016) and 1396 (2017) was 96% and 94%, repectively. |
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| Keywords: Support Vector Machine, Clustering, Market Clearing Price Forecast, Iranian Electricity Day-ahead Market |
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Full-Text [PDF 359 kb]
(1190 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2018/05/15 | Accepted: 2018/07/19 | Published: 2018/12/16
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