Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption
In recent years, global energy shortages and environmental pollution have intensified. With the large-scale development of new energy wind energy, there is also a major problem-insufficient absorption capacity. In order to promote large-scale wind power consumption, a model predictive control method...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10216939/ |
| _version_ | 1797741044590182400 |
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| author | Qilong Zhang Xiangping Chen Guangming Li Junjie Feng Anqian Yang |
| author_facet | Qilong Zhang Xiangping Chen Guangming Li Junjie Feng Anqian Yang |
| author_sort | Qilong Zhang |
| collection | DOAJ |
| description | In recent years, global energy shortages and environmental pollution have intensified. With the large-scale development of new energy wind energy, there is also a major problem-insufficient absorption capacity. In order to promote large-scale wind power consumption, a model predictive control method based on wind hydrogen coupled power generation system is proposed. Firstly, the mathematical models of equivalent state of charge in wind power, hydrogen energy storage systems (HESS), and gas storage tanks are analyzed. Secondly, the optimization objective function is to maximize the local wind energy consumption and minimize the energy interaction between the main grid. Establish an SSM prediction model based on the MPC strategy. Genetic optimization algorithm is used for rolling solution. Aiming at the interference and prediction error generated during the operation of the system, a feedback mechanism is introduced to embed it into the MPC framework. Then, the rolling time domain method is used to compensate for system interference. Finally, a case study was conducted based on actual measurement data from a certain area in the Netherlands. By comparing the wind power dissipation effects of the system during operation, it is verified that the proposed method can effectively reduce interactive power consumption. Maximize the local consumption of wind power. |
| first_indexed | 2024-03-12T14:21:12Z |
| format | Article |
| id | doaj.art-2eaddb281b55498da97687a2862cfb97 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-12T14:21:12Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-2eaddb281b55498da97687a2862cfb972023-08-18T23:00:16ZengIEEEIEEE Access2169-35362023-01-0111866978671010.1109/ACCESS.2023.330469710216939Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power ConsumptionQilong Zhang0https://orcid.org/0009-0000-7239-0552Xiangping Chen1https://orcid.org/0000-0002-6064-4508Guangming Li2Junjie Feng3Anqian Yang4School of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui, ChinaGuizhou University, Guiyang, ChinaSchool of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui, ChinaSchool of Physics and Electrical Engineering, Liupanshui Normal University, Liupanshui, ChinaElectric Power Research Institute, Guizhou Power Grid Company Ltd., Guiyang, ChinaIn recent years, global energy shortages and environmental pollution have intensified. With the large-scale development of new energy wind energy, there is also a major problem-insufficient absorption capacity. In order to promote large-scale wind power consumption, a model predictive control method based on wind hydrogen coupled power generation system is proposed. Firstly, the mathematical models of equivalent state of charge in wind power, hydrogen energy storage systems (HESS), and gas storage tanks are analyzed. Secondly, the optimization objective function is to maximize the local wind energy consumption and minimize the energy interaction between the main grid. Establish an SSM prediction model based on the MPC strategy. Genetic optimization algorithm is used for rolling solution. Aiming at the interference and prediction error generated during the operation of the system, a feedback mechanism is introduced to embed it into the MPC framework. Then, the rolling time domain method is used to compensate for system interference. Finally, a case study was conducted based on actual measurement data from a certain area in the Netherlands. By comparing the wind power dissipation effects of the system during operation, it is verified that the proposed method can effectively reduce interactive power consumption. Maximize the local consumption of wind power.https://ieeexplore.ieee.org/document/10216939/Wind power consumptionmulti-energy flow systemHESSMPC optimization method |
| spellingShingle | Qilong Zhang Xiangping Chen Guangming Li Junjie Feng Anqian Yang Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption IEEE Access Wind power consumption multi-energy flow system HESS MPC optimization method |
| title | Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption |
| title_full | Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption |
| title_fullStr | Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption |
| title_full_unstemmed | Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption |
| title_short | Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption |
| title_sort | model predictive control method of multi energy flow system considering wind power consumption |
| topic | Wind power consumption multi-energy flow system HESS MPC optimization method |
| url | https://ieeexplore.ieee.org/document/10216939/ |
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