Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting
Energy management systems (EMSs) play an important role in the optimal operation of prosumers. As an essential segment of each EMS, the load forecasting (LF) block enhances the optimal utilization of renewable energy sources (RESs) and battery energy storage systems (BESSs). In this paper, a new opt...
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9082670/ |
| _version_ | 1819296364921618432 |
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| author | Jamal Faraji Abbas Ketabi Hamed Hashemi-Dezaki Miadreza Shafie-Khah Joao P. S. Catalao |
| author_facet | Jamal Faraji Abbas Ketabi Hamed Hashemi-Dezaki Miadreza Shafie-Khah Joao P. S. Catalao |
| author_sort | Jamal Faraji |
| collection | DOAJ |
| description | Energy management systems (EMSs) play an important role in the optimal operation of prosumers. As an essential segment of each EMS, the load forecasting (LF) block enhances the optimal utilization of renewable energy sources (RESs) and battery energy storage systems (BESSs). In this paper, a new optimal day-ahead scheduling and operation of the prosumer is proposed based on the two-level corrective LF. The proposed two-level corrective LF actions are developed through a very precise short-term LF. In the first level, a time-series LF is applied using multi-layer perceptron artificial neural networks (MLP-ANNs). In order to improve the accuracy of the forecasted load data at the first level, the second level corrective LF is applied using feed-forward (FF) ANNs. The second stage prediction is initiated when the LF results violate the pre-defined criteria. The proposed method is applied to a prosumer under different cases (based on the consideration of BESS operation behaviors and cost) and various scenarios (based on the accuracy of the load data). The obtained optimal day-ahead operation results illustrate the advantages of the proposed method and its corrective forecasting process. The comparison of the obtained results and those of other available ones show the effectiveness of the proposed optimal operation of the prosumers. The advantages of the proposed method are highlighted while the BESS costs are considered. |
| first_indexed | 2024-12-24T04:56:57Z |
| format | Article |
| id | doaj.art-36fc269e929944398b4545d4a5107386 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-24T04:56:57Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-36fc269e929944398b4545d4a51073862022-12-21T17:14:22ZengIEEEIEEE Access2169-35362020-01-018835618358210.1109/ACCESS.2020.29914829082670Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load ForecastingJamal Faraji0https://orcid.org/0000-0001-5790-6936Abbas Ketabi1Hamed Hashemi-Dezaki2Miadreza Shafie-Khah3https://orcid.org/0000-0003-1691-5355Joao P. S. Catalao4Energy Research Institute, University of Kashan, Kashan, IranDepartment of Electrical and Computer Engineering, University of Kashan, Kashan, IranDepartment of Electrical and Computer Engineering, University of Kashan, Kashan, IranSchool of Technology and Innovations, University of Vaasa, Vaasa, FinlandFaculty of Engineering, University of Porto and INESC TEC, Porto, PortugalEnergy management systems (EMSs) play an important role in the optimal operation of prosumers. As an essential segment of each EMS, the load forecasting (LF) block enhances the optimal utilization of renewable energy sources (RESs) and battery energy storage systems (BESSs). In this paper, a new optimal day-ahead scheduling and operation of the prosumer is proposed based on the two-level corrective LF. The proposed two-level corrective LF actions are developed through a very precise short-term LF. In the first level, a time-series LF is applied using multi-layer perceptron artificial neural networks (MLP-ANNs). In order to improve the accuracy of the forecasted load data at the first level, the second level corrective LF is applied using feed-forward (FF) ANNs. The second stage prediction is initiated when the LF results violate the pre-defined criteria. The proposed method is applied to a prosumer under different cases (based on the consideration of BESS operation behaviors and cost) and various scenarios (based on the accuracy of the load data). The obtained optimal day-ahead operation results illustrate the advantages of the proposed method and its corrective forecasting process. The comparison of the obtained results and those of other available ones show the effectiveness of the proposed optimal operation of the prosumers. The advantages of the proposed method are highlighted while the BESS costs are considered.https://ieeexplore.ieee.org/document/9082670/load forecasting (LF)multi-layer perceptron artificial neural network (ANN-MLP)optimal operation and schedulingprosumerbattery energy storage system (BESS)renewable energy sources (RESs) |
| spellingShingle | Jamal Faraji Abbas Ketabi Hamed Hashemi-Dezaki Miadreza Shafie-Khah Joao P. S. Catalao Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting IEEE Access load forecasting (LF) multi-layer perceptron artificial neural network (ANN-MLP) optimal operation and scheduling prosumer battery energy storage system (BESS) renewable energy sources (RESs) |
| title | Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting |
| title_full | Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting |
| title_fullStr | Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting |
| title_full_unstemmed | Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting |
| title_short | Optimal Day-Ahead Scheduling and Operation of the Prosumer by Considering Corrective Actions Based on Very Short-Term Load Forecasting |
| title_sort | optimal day ahead scheduling and operation of the prosumer by considering corrective actions based on very short term load forecasting |
| topic | load forecasting (LF) multi-layer perceptron artificial neural network (ANN-MLP) optimal operation and scheduling prosumer battery energy storage system (BESS) renewable energy sources (RESs) |
| url | https://ieeexplore.ieee.org/document/9082670/ |
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