Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting
At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this probl...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/9/2539 |
| _version_ | 1797535946319593472 |
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| author | Zhengjie Li Zhisheng Zhang |
| author_facet | Zhengjie Li Zhisheng Zhang |
| author_sort | Zhengjie Li |
| collection | DOAJ |
| description | At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level. |
| first_indexed | 2024-03-10T11:52:34Z |
| format | Article |
| id | doaj.art-e58a228158e44630b9d92eb17538327a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T11:52:34Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-e58a228158e44630b9d92eb17538327a2023-11-21T17:38:51ZengMDPI AGEnergies1996-10732021-04-01149253910.3390/en14092539Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power ForecastingZhengjie Li0Zhisheng Zhang1College of Electrical Engineering, Qingdao University, Qingdao 266071, ChinaCollege of Electrical Engineering, Qingdao University, Qingdao 266071, ChinaAt present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level.https://www.mdpi.com/1996-1073/14/9/2539integrated energy systemday-ahead and intra-day dispatchintegrated demand responseload forecastingmulti load |
| spellingShingle | Zhengjie Li Zhisheng Zhang Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting Energies integrated energy system day-ahead and intra-day dispatch integrated demand response load forecasting multi load |
| title | Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting |
| title_full | Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting |
| title_fullStr | Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting |
| title_full_unstemmed | Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting |
| title_short | Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting |
| title_sort | day ahead and intra day optimal scheduling of integrated energy system considering uncertainty of source load power forecasting |
| topic | integrated energy system day-ahead and intra-day dispatch integrated demand response load forecasting multi load |
| url | https://www.mdpi.com/1996-1073/14/9/2539 |
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