Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework
Abstract Hydrogen-based renewable microgrid is considered as a prospective technique in power generation to reduce the carbon footprint, combat climate change and promote renewable energy sources integration. The photovoltaic-hydrogen-storage (PHS) microgrid system cleverly integrates renewable clea...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-02-01
|
| Series: | Energy Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42162-025-00482-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1823861604425400320 |
|---|---|
| author | Xinyu Guo Faying Gu Hongxu Liu Yongcheng Yu Runjie Li Juan Wang |
| author_facet | Xinyu Guo Faying Gu Hongxu Liu Yongcheng Yu Runjie Li Juan Wang |
| author_sort | Xinyu Guo |
| collection | DOAJ |
| description | Abstract Hydrogen-based renewable microgrid is considered as a prospective technique in power generation to reduce the carbon footprint, combat climate change and promote renewable energy sources integration. The photovoltaic-hydrogen-storage (PHS) microgrid system cleverly integrates renewable clean energy and hydrogen storage, providing a sustainable solution that maximizes the solar energy utilization. However, the changeable weather conditions and fluid market make it challenging to manage energy balance of the system. Moreover, in view of the fact that the existing energy management systems often ignore the dynamic synergy of microgrids, a hierarchical economic model predictive control (HEMPC) framework is proposed to realize the optimal operation of PHS microgrid. First, a precise nonlinear model of the PHS microgrid is established and the logic variables are introduced to capture the hydrogen devices’ short-term properties, i.e., the start-up/shut-down of electrolyzers and fuel cells. Then a comprehensive economic cost function, including internal power demand tracking cost, system operation cost and contract deviation cost, is considered in the proposed two-level HEMPC framework in order to address challenges such as fluctuating weather conditions, dynamic market environments, and the often-overlooked dynamic synergy of microgrid components. Under the proposed framework, a mixed-integer nonlinear optimization problem is solved by the long-term EMPC in the upper level to regulate the start-up/shut-down of hydrogen devices and the state of charge in the battery, and the short-term EMPC in the lower level reoptimizes the power demand tracking cost while tracking the optimal reference signal from the long-term EMPC, thereby improving overall control system efficiency. The simulation results along with qualitative and quantitative analysis show that compared with rule-based control, the proposed HEMPC is effective in managing the equipment power output, realizing dynamic synergy and enhancing the economic performance. |
| format | Article |
| id | doaj-art-ec8b9eb5a0634e479adac98adc8436eb |
| institution | Kabale University |
| issn | 2520-8942 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj-art-ec8b9eb5a0634e479adac98adc8436eb2025-02-09T12:56:40ZengSpringerOpenEnergy Informatics2520-89422025-02-018113210.1186/s42162-025-00482-zSustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control frameworkXinyu Guo0Faying Gu1Hongxu Liu2Yongcheng Yu3Runjie Li4Juan Wang5CHN Energy Qinghai Electric Power Co., LtdCHN Energy Qinghai Electric Power Co., LtdCHN Energy Qinghai Electric Power Co., LtdCHN Energy I&C Interconnection Technology Co., LtdCHN Energy I&C Interconnection Technology Co., LtdCHN Energy I&C Interconnection Technology Co., LtdAbstract Hydrogen-based renewable microgrid is considered as a prospective technique in power generation to reduce the carbon footprint, combat climate change and promote renewable energy sources integration. The photovoltaic-hydrogen-storage (PHS) microgrid system cleverly integrates renewable clean energy and hydrogen storage, providing a sustainable solution that maximizes the solar energy utilization. However, the changeable weather conditions and fluid market make it challenging to manage energy balance of the system. Moreover, in view of the fact that the existing energy management systems often ignore the dynamic synergy of microgrids, a hierarchical economic model predictive control (HEMPC) framework is proposed to realize the optimal operation of PHS microgrid. First, a precise nonlinear model of the PHS microgrid is established and the logic variables are introduced to capture the hydrogen devices’ short-term properties, i.e., the start-up/shut-down of electrolyzers and fuel cells. Then a comprehensive economic cost function, including internal power demand tracking cost, system operation cost and contract deviation cost, is considered in the proposed two-level HEMPC framework in order to address challenges such as fluctuating weather conditions, dynamic market environments, and the often-overlooked dynamic synergy of microgrid components. Under the proposed framework, a mixed-integer nonlinear optimization problem is solved by the long-term EMPC in the upper level to regulate the start-up/shut-down of hydrogen devices and the state of charge in the battery, and the short-term EMPC in the lower level reoptimizes the power demand tracking cost while tracking the optimal reference signal from the long-term EMPC, thereby improving overall control system efficiency. The simulation results along with qualitative and quantitative analysis show that compared with rule-based control, the proposed HEMPC is effective in managing the equipment power output, realizing dynamic synergy and enhancing the economic performance.https://doi.org/10.1186/s42162-025-00482-zPV-hydrogen-storage microgridEnergy management systemHierarchical economic model predictive controlMixed-integer nonlinear programming |
| spellingShingle | Xinyu Guo Faying Gu Hongxu Liu Yongcheng Yu Runjie Li Juan Wang Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework Energy Informatics PV-hydrogen-storage microgrid Energy management system Hierarchical economic model predictive control Mixed-integer nonlinear programming |
| title | Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework |
| title_full | Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework |
| title_fullStr | Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework |
| title_full_unstemmed | Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework |
| title_short | Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework |
| title_sort | sustainable pv hydrogen storage microgrid energy management using a hierarchical economic model predictive control framework |
| topic | PV-hydrogen-storage microgrid Energy management system Hierarchical economic model predictive control Mixed-integer nonlinear programming |
| url | https://doi.org/10.1186/s42162-025-00482-z |
| work_keys_str_mv | AT xinyuguo sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework AT fayinggu sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework AT hongxuliu sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework AT yongchengyu sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework AT runjieli sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework AT juanwang sustainablepvhydrogenstoragemicrogridenergymanagementusingahierarchicaleconomicmodelpredictivecontrolframework |