PV/Hydrogen DC microgrid control using distributed economic model predictive control
The integration of hydrogen energy into a photovoltaic-dominated microgrid is now becoming a promising approach to improve the photoconversion efficiency and enhance the operating reliability. However, the energy management and power regulation of the Photovoltaic/Hydrogen DC microgrid face challeng...
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| Vydáno v: | Renewable energy Ročník 222; s. 119871 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.02.2024
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| ISSN: | 0960-1481, 1879-0682 |
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| Abstract | The integration of hydrogen energy into a photovoltaic-dominated microgrid is now becoming a promising approach to improve the photoconversion efficiency and enhance the operating reliability. However, the energy management and power regulation of the Photovoltaic/Hydrogen DC microgrid face challenges due to the intermittency of photovoltaic (PV) power generation and the randomness of load. In this paper, a distributed economic model predictive control (DEMPC) scheme is developed for a PV/Hydrogen DC microgrid, which integrates the energy management, economic optimization, and power regulation into one optimal control framework. Based on the developed distributed converter-based mathematical model, three local controllers are designed to achieve the economic targets of PV subsystem, alkaline electrolyzer subsystem, and proton exchange membrane fuel cell subsystem respectively, which cooperate with each other through the communication network to realize the power supply–demand balance, DC bus voltage stability, and economic optimization. A mixed integer nonlinear programming algorithm utilizing the finite converter switching states is embedded into the DEMPC to solve the non-convex local optimization problems efficiently. The effectiveness and superiority of the proposed DEMPC scheme are verified by simulations under varying irradiance and load conditions, indicating that the DEMPC can achieve a comparable overall dynamic economic performance with a significantly reduced computation burden and power oscillation, compared to the centralized economic model predictive control (CEMPC).
•A DEMPC scheme is developed for a PV/Hydrogen DC microgrid.•An EMS is incorporated into the proposed DEMPC scheme.•An efficient algorithm is proposed to solve non-convex DEMPC optimization problem.•The DEMPC is validated by simulations under varying irradiance and load conditions. |
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| AbstractList | The integration of hydrogen energy into a photovoltaic-dominated microgrid is now becoming a promising approach to improve the photoconversion efficiency and enhance the operating reliability. However, the energy management and power regulation of the Photovoltaic/Hydrogen DC microgrid face challenges due to the intermittency of photovoltaic (PV) power generation and the randomness of load. In this paper, a distributed economic model predictive control (DEMPC) scheme is developed for a PV/Hydrogen DC microgrid, which integrates the energy management, economic optimization, and power regulation into one optimal control framework. Based on the developed distributed converter-based mathematical model, three local controllers are designed to achieve the economic targets of PV subsystem, alkaline electrolyzer subsystem, and proton exchange membrane fuel cell subsystem respectively, which cooperate with each other through the communication network to realize the power supply–demand balance, DC bus voltage stability, and economic optimization. A mixed integer nonlinear programming algorithm utilizing the finite converter switching states is embedded into the DEMPC to solve the non-convex local optimization problems efficiently. The effectiveness and superiority of the proposed DEMPC scheme are verified by simulations under varying irradiance and load conditions, indicating that the DEMPC can achieve a comparable overall dynamic economic performance with a significantly reduced computation burden and power oscillation, compared to the centralized economic model predictive control (CEMPC).
•A DEMPC scheme is developed for a PV/Hydrogen DC microgrid.•An EMS is incorporated into the proposed DEMPC scheme.•An efficient algorithm is proposed to solve non-convex DEMPC optimization problem.•The DEMPC is validated by simulations under varying irradiance and load conditions. The integration of hydrogen energy into a photovoltaic-dominated microgrid is now becoming a promising approach to improve the photoconversion efficiency and enhance the operating reliability. However, the energy management and power regulation of the Photovoltaic/Hydrogen DC microgrid face challenges due to the intermittency of photovoltaic (PV) power generation and the randomness of load. In this paper, a distributed economic model predictive control (DEMPC) scheme is developed for a PV/Hydrogen DC microgrid, which integrates the energy management, economic optimization, and power regulation into one optimal control framework. Based on the developed distributed converter-based mathematical model, three local controllers are designed to achieve the economic targets of PV subsystem, alkaline electrolyzer subsystem, and proton exchange membrane fuel cell subsystem respectively, which cooperate with each other through the communication network to realize the power supply–demand balance, DC bus voltage stability, and economic optimization. A mixed integer nonlinear programming algorithm utilizing the finite converter switching states is embedded into the DEMPC to solve the non-convex local optimization problems efficiently. The effectiveness and superiority of the proposed DEMPC scheme are verified by simulations under varying irradiance and load conditions, indicating that the DEMPC can achieve a comparable overall dynamic economic performance with a significantly reduced computation burden and power oscillation, compared to the centralized economic model predictive control (CEMPC). |
| ArticleNumber | 119871 |
| Author | Liu, Xiangjie Ma, Lele Lee, Kwang Y. Xu, Yuping Kong, Xiaobing Zhu, Zheng |
| Author_xml | – sequence: 1 givenname: Zheng orcidid: 0009-0004-5104-7578 surname: Zhu fullname: Zhu, Zheng organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, Beijing, China – sequence: 2 givenname: Xiangjie orcidid: 0000-0002-9116-518X surname: Liu fullname: Liu, Xiangjie organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, Beijing, China – sequence: 3 givenname: Xiaobing surname: Kong fullname: Kong, Xiaobing email: kongxiaobing@ncepu.edu.cn organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, Beijing, China – sequence: 4 givenname: Lele surname: Ma fullname: Ma, Lele organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, Beijing, China – sequence: 5 givenname: Kwang Y. orcidid: 0000-0002-9965-9117 surname: Lee fullname: Lee, Kwang Y. organization: Department of Electrical and Computer Engineering, Baylor University, Waco, 76798, TX, USA – sequence: 6 givenname: Yuping surname: Xu fullname: Xu, Yuping organization: The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, Beijing, China |
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| Cites_doi | 10.1016/j.renene.2022.06.140 10.1109/TSMC.2019.2897646 10.1109/TIE.2006.878328 10.1109/TPEL.2011.2179672 10.1109/TSG.2015.2457910 10.1109/TCST.2013.2295737 10.1016/S0360-3199(02)00033-2 10.1016/j.rser.2020.110626 10.1016/j.renene.2021.09.048 10.1109/TSTE.2018.2873390 10.1016/j.jprocont.2018.11.003 10.1109/TIE.2017.2779412 10.1109/TSTE.2021.3066334 10.1109/TIA.2019.2921028 10.1109/TCST.2013.2248156 10.1016/j.apenergy.2022.119549 10.1016/j.apenergy.2021.118092 10.1016/j.solener.2017.02.017 10.1016/j.renene.2022.12.031 10.1016/j.apenergy.2023.121058 10.1016/j.ijhydene.2018.04.013 10.1016/j.renene.2021.12.011 10.1109/TPEL.2022.3159828 10.1109/TEC.2008.2011837 10.1016/j.apenergy.2020.115960 10.1109/TSTE.2019.2919499 10.1016/j.rser.2020.110422 10.1016/j.ijhydene.2019.05.097 10.1109/TSG.2016.2524688 10.1016/j.apenergy.2022.119050 10.1016/j.renene.2016.05.006 10.1016/j.conengprac.2018.09.025 10.1016/j.apenergy.2018.03.085 |
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| References | Liu, Mo, Zhao (b3) 2023; 203 Kong, Yu, Cai (b14) 2019; 44 Çelik, Meral (b13) 2019; 82 Mutoh, Ohno, Inoue (b29) 2006; 53 Quevedo, Aguilera, Perez, Cortes, Lizana (b34) 2012; 27 Wang, Zhang, Bao (b28) 2019; 73 Hu, Shan, Yang, Parisio, Li, Amjady, Islam, Cheng, Guerrero, Rodríguez (b22) 2023 Jia, Li, Wang, Cham, Han (b32) 2009; 24 Zhao, Zhou, Gao, Ma, Qin (b33) 2017; 144 Li, Chen, Wu, Wang, Liu, Qi, Lu, Gao (b9) 2021; 137 Kong, Ma, Wang, Guo, Abdelbaky, Liu, Lee (b25) 2022; 181 Cai, Xiang, Wei (b30) 2018; 65 Hu, Xu, Cheng, Guerrero (b19) 2018; 221 Ulleberg (b31) 2003; 28 Liu, Fu, Qiu, Zhang, Li, Yang, Liu, Jiang (b18) 2023; 341 Trifkovic, Sheikhzadeh, Nigim, Daoutidis (b10) 2014; 22 Kong, Liu, Ma, Lee (b11) 2019; 49 Han, Chen, Li, Yang, Zare, Zheng (b7) 2019; 44 Dou, Yue, Guerrero, Xie, Hu (b16) 2017; 8 Tobajas, Garcia-Torres, Roncero-Sánchez, Vázquez, Bellatreche, Nieto (b23) 2022; 306 Jia, Dong, Sun, Chen (b26) 2020; 11 Xing, Xu, Guo, Wu, Liu (b17) 2021; 12 Hu, Shan, Cheng, Islam (b12) 2022; 37 Shan, Hu, Chan, Fu, Guerrero (b20) 2019; 10 Li, Gao, Li, Zhou (b1) 2022; 185 Lotfi, Khodaei (b6) 2017; 8 K/bidi, Damour, Grondin, Hilairet, Benne (b15) 2022; 323 Zhang, Bao, Wang, Zheng, Skyllas-Kazacos (b27) 2017; 100 Armghan, Yang, Ali, Armghan, Alanazi (b2) 2022; 316 Hu, Shan, Guerrero, Ioinovici, Chan, Rodriguez (b4) 2021; 136 Mahmud, Roy, Saha, Haque, Pota (b8) 2019; 55 Grover, Verma, Bhatti (b5) 2022; 196 Clarke, Brear, Manzie (b24) 2020; 280 Parisio, Rikos, Glielmo (b21) 2014; 22 Hu (10.1016/j.renene.2023.119871_b22) 2023 Jia (10.1016/j.renene.2023.119871_b32) 2009; 24 Kong (10.1016/j.renene.2023.119871_b14) 2019; 44 Li (10.1016/j.renene.2023.119871_b1) 2022; 185 Lotfi (10.1016/j.renene.2023.119871_b6) 2017; 8 Parisio (10.1016/j.renene.2023.119871_b21) 2014; 22 Shan (10.1016/j.renene.2023.119871_b20) 2019; 10 Tobajas (10.1016/j.renene.2023.119871_b23) 2022; 306 Jia (10.1016/j.renene.2023.119871_b26) 2020; 11 Hu (10.1016/j.renene.2023.119871_b19) 2018; 221 Clarke (10.1016/j.renene.2023.119871_b24) 2020; 280 Trifkovic (10.1016/j.renene.2023.119871_b10) 2014; 22 Quevedo (10.1016/j.renene.2023.119871_b34) 2012; 27 Mutoh (10.1016/j.renene.2023.119871_b29) 2006; 53 Kong (10.1016/j.renene.2023.119871_b11) 2019; 49 Zhang (10.1016/j.renene.2023.119871_b27) 2017; 100 Li (10.1016/j.renene.2023.119871_b9) 2021; 137 Liu (10.1016/j.renene.2023.119871_b18) 2023; 341 Kong (10.1016/j.renene.2023.119871_b25) 2022; 181 Dou (10.1016/j.renene.2023.119871_b16) 2017; 8 Hu (10.1016/j.renene.2023.119871_b4) 2021; 136 Liu (10.1016/j.renene.2023.119871_b3) 2023; 203 Zhao (10.1016/j.renene.2023.119871_b33) 2017; 144 Armghan (10.1016/j.renene.2023.119871_b2) 2022; 316 Han (10.1016/j.renene.2023.119871_b7) 2019; 44 Xing (10.1016/j.renene.2023.119871_b17) 2021; 12 Cai (10.1016/j.renene.2023.119871_b30) 2018; 65 Wang (10.1016/j.renene.2023.119871_b28) 2019; 73 Hu (10.1016/j.renene.2023.119871_b12) 2022; 37 K/bidi (10.1016/j.renene.2023.119871_b15) 2022; 323 Mahmud (10.1016/j.renene.2023.119871_b8) 2019; 55 Ulleberg (10.1016/j.renene.2023.119871_b31) 2003; 28 Grover (10.1016/j.renene.2023.119871_b5) 2022; 196 Çelik (10.1016/j.renene.2023.119871_b13) 2019; 82 |
| References_xml | – volume: 49 start-page: 1570 year: 2019 end-page: 1581 ident: b11 article-title: Hierarchical distributed model predictive control of standalone wind/solar/battery power system publication-title: IEEE Trans. Syst. Man Cybern.: Syst. – volume: 341 year: 2023 ident: b18 article-title: Charging private electric vehicles solely by photovoltaics: A battery-free direct-current microgrid with distributed charging strategy publication-title: Appl. Energy – volume: 22 start-page: 1813 year: 2014 end-page: 1827 ident: b21 article-title: A model predictive control approach to microgrid operation optimization publication-title: IEEE Trans. Control Syst. Technol. – volume: 28 start-page: 21 year: 2003 end-page: 33 ident: b31 article-title: Modeling of advanced alkaline electrolyzers: A system simulation approach publication-title: Int. J. Hydrogen Energy – volume: 24 start-page: 283 year: 2009 end-page: 291 ident: b32 article-title: Modeling and dynamic characteristic simulation of a proton exchange membrane fuel cell publication-title: IEEE Trans. Energy Convers. – volume: 323 year: 2022 ident: b15 article-title: Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage publication-title: Appl. Energy – volume: 203 start-page: 102 year: 2023 end-page: 112 ident: b3 article-title: Two-level optimal scheduling method for a renewable microgrid considering charging performances of heat pump with thermal storages publication-title: Renew. Energy – volume: 55 start-page: 5343 year: 2019 end-page: 5352 ident: b8 article-title: Robust nonlinear adaptive feedback linearizing decentralized controller design for islanded DC microgrids publication-title: IEEE Trans. Ind. Appl. – volume: 37 start-page: 9907 year: 2022 end-page: 9922 ident: b12 article-title: Overview of power converter control in microgrids—Challenges, advances, and future trends publication-title: IEEE Trans. Power Electron. – volume: 196 start-page: 883 year: 2022 end-page: 900 ident: b5 article-title: DOBC-based frequency & voltage regulation strategy for PV-diesel hybrid microgrid during islanding conditions publication-title: Renew. Energy – volume: 185 start-page: 86 year: 2022 end-page: 95 ident: b1 article-title: Effect of the temperature difference between land and lake on photovoltaic power generation publication-title: Renew. Energy – volume: 181 start-page: 581 year: 2022 end-page: 591 ident: b25 article-title: Large-scale wind farm control using distributed economic model predictive scheme publication-title: Renew. Energy – volume: 27 start-page: 3128 year: 2012 end-page: 3136 ident: b34 article-title: Model predictive control of an AFE rectifier with dynamic references publication-title: IEEE Trans. Power Electron. – volume: 316 year: 2022 ident: b2 article-title: Quick reaching law based global terminal sliding mode control for wind/hydrogen/battery DC microgrid publication-title: Appl. Energy – volume: 144 start-page: 767 year: 2017 end-page: 779 ident: b33 article-title: A novel global maximum power point tracking strategy (GMPPT) based on optimal current control for photovoltaic systems adaptive to variable environmental and partial shading conditions publication-title: Sol. Energy – volume: 22 start-page: 169 year: 2014 end-page: 179 ident: b10 article-title: Modeling and control of a renewable hybrid energy system with hydrogen storage publication-title: IEEE Trans. Control Syst. Technol. – volume: 44 start-page: 25129 year: 2019 end-page: 25144 ident: b14 article-title: Modeling, control and simulation of a photovoltaic /hydrogen/ supercapacitor hybrid power generation system for grid-connected applications publication-title: Int. J. Hydrogen Energy – volume: 8 start-page: 2370 year: 2017 end-page: 2381 ident: b16 article-title: Multiagent system-based distributed coordinated control for radial DC microgrid considering transmission time delays publication-title: IEEE Trans. Smart Grid – volume: 306 year: 2022 ident: b23 article-title: Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control publication-title: Appl. Energy – volume: 53 start-page: 1055 year: 2006 end-page: 1065 ident: b29 article-title: A method for MPPT control while searching for parameters corresponding to weather conditions for PV generation systems publication-title: IEEE Trans. Ind. Electron. – volume: 100 start-page: 18 year: 2017 end-page: 34 ident: b27 article-title: Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage publication-title: Renew. Energy – volume: 10 start-page: 1823 year: 2019 end-page: 1833 ident: b20 article-title: Model predictive control of bidirectional DC–DC converters and AC/DC interlinking converters—A new control method for PV-Wind-Battery microgrids publication-title: IEEE Trans. Sustain. Energy – volume: 136 year: 2021 ident: b4 article-title: Model predictive control of microgrids – An overview publication-title: Renew. Sustain. Energy Rev. – volume: 137 year: 2021 ident: b9 article-title: How to make better use of intermittent and variable energy? A review of wind and photovoltaic power consumption in China publication-title: Renew. Sustain. Energy Rev. – volume: 221 start-page: 195 year: 2018 end-page: 203 ident: b19 article-title: A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions publication-title: Appl. Energy – volume: 12 start-page: 1801 year: 2021 end-page: 1810 ident: b17 article-title: Distributed secondary control for DC microgrid with event-triggered signal transmissions publication-title: IEEE Trans. Sustain. Energy – volume: 280 year: 2020 ident: b24 article-title: Control of an isolated microgrid using hierarchical economic model predictive control publication-title: Appl. Energy – volume: 65 start-page: 5601 year: 2018 end-page: 5610 ident: b30 article-title: Decentralized coordination control of multiple photovoltaic sources for DC bus voltage regulating and power sharing publication-title: IEEE Trans. Ind. Electron. – volume: 44 start-page: 19395 year: 2019 end-page: 19404 ident: b7 article-title: Two-level energy management strategy for PV-Fuel cell-battery-based DC microgrid publication-title: Int. J. Hydrogen Energy – volume: 8 start-page: 296 year: 2017 end-page: 304 ident: b6 article-title: AC versus DC microgrid planning publication-title: IEEE Trans. Smart Grid – volume: 82 start-page: 72 year: 2019 end-page: 85 ident: b13 article-title: Current control based power management strategy for distributed power generation system publication-title: Control Eng. Pract. – start-page: 1 year: 2023 ident: b22 article-title: Economic model predictive control for microgrid optimization: A review publication-title: IEEE Trans. Smart Grid – volume: 11 start-page: 1089 year: 2020 end-page: 1099 ident: b26 article-title: Distributed economic model predictive control for a wind–photovoltaic–battery microgrid power system publication-title: IEEE Trans. Sustain. Energy – volume: 73 start-page: 9 year: 2019 end-page: 18 ident: b28 article-title: A self-interested distributed economic model predictive control approach to battery energy storage networks publication-title: J. Process Control – volume: 196 start-page: 883 year: 2022 ident: 10.1016/j.renene.2023.119871_b5 article-title: DOBC-based frequency & voltage regulation strategy for PV-diesel hybrid microgrid during islanding conditions publication-title: Renew. Energy doi: 10.1016/j.renene.2022.06.140 – volume: 49 start-page: 1570 issue: 8 year: 2019 ident: 10.1016/j.renene.2023.119871_b11 article-title: Hierarchical distributed model predictive control of standalone wind/solar/battery power system publication-title: IEEE Trans. Syst. Man Cybern.: Syst. doi: 10.1109/TSMC.2019.2897646 – volume: 53 start-page: 1055 issue: 4 year: 2006 ident: 10.1016/j.renene.2023.119871_b29 article-title: A method for MPPT control while searching for parameters corresponding to weather conditions for PV generation systems publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2006.878328 – volume: 27 start-page: 3128 issue: 7 year: 2012 ident: 10.1016/j.renene.2023.119871_b34 article-title: Model predictive control of an AFE rectifier with dynamic references publication-title: IEEE Trans. Power Electron. doi: 10.1109/TPEL.2011.2179672 – volume: 8 start-page: 296 issue: 1 year: 2017 ident: 10.1016/j.renene.2023.119871_b6 article-title: AC versus DC microgrid planning publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2015.2457910 – volume: 22 start-page: 1813 issue: 5 year: 2014 ident: 10.1016/j.renene.2023.119871_b21 article-title: A model predictive control approach to microgrid operation optimization publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2013.2295737 – volume: 28 start-page: 21 issue: 1 year: 2003 ident: 10.1016/j.renene.2023.119871_b31 article-title: Modeling of advanced alkaline electrolyzers: A system simulation approach publication-title: Int. J. Hydrogen Energy doi: 10.1016/S0360-3199(02)00033-2 – volume: 137 year: 2021 ident: 10.1016/j.renene.2023.119871_b9 article-title: How to make better use of intermittent and variable energy? A review of wind and photovoltaic power consumption in China publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2020.110626 – volume: 181 start-page: 581 year: 2022 ident: 10.1016/j.renene.2023.119871_b25 article-title: Large-scale wind farm control using distributed economic model predictive scheme publication-title: Renew. Energy doi: 10.1016/j.renene.2021.09.048 – volume: 10 start-page: 1823 issue: 4 year: 2019 ident: 10.1016/j.renene.2023.119871_b20 article-title: Model predictive control of bidirectional DC–DC converters and AC/DC interlinking converters—A new control method for PV-Wind-Battery microgrids publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2018.2873390 – volume: 73 start-page: 9 year: 2019 ident: 10.1016/j.renene.2023.119871_b28 article-title: A self-interested distributed economic model predictive control approach to battery energy storage networks publication-title: J. Process Control doi: 10.1016/j.jprocont.2018.11.003 – volume: 65 start-page: 5601 issue: 7 year: 2018 ident: 10.1016/j.renene.2023.119871_b30 article-title: Decentralized coordination control of multiple photovoltaic sources for DC bus voltage regulating and power sharing publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2017.2779412 – volume: 12 start-page: 1801 issue: 3 year: 2021 ident: 10.1016/j.renene.2023.119871_b17 article-title: Distributed secondary control for DC microgrid with event-triggered signal transmissions publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2021.3066334 – volume: 55 start-page: 5343 issue: 5 year: 2019 ident: 10.1016/j.renene.2023.119871_b8 article-title: Robust nonlinear adaptive feedback linearizing decentralized controller design for islanded DC microgrids publication-title: IEEE Trans. Ind. Appl. doi: 10.1109/TIA.2019.2921028 – volume: 22 start-page: 169 issue: 1 year: 2014 ident: 10.1016/j.renene.2023.119871_b10 article-title: Modeling and control of a renewable hybrid energy system with hydrogen storage publication-title: IEEE Trans. Control Syst. Technol. doi: 10.1109/TCST.2013.2248156 – volume: 323 year: 2022 ident: 10.1016/j.renene.2023.119871_b15 article-title: Multistage power and energy management strategy for hybrid microgrid with photovoltaic production and hydrogen storage publication-title: Appl. Energy doi: 10.1016/j.apenergy.2022.119549 – volume: 306 year: 2022 ident: 10.1016/j.renene.2023.119871_b23 article-title: Resilience-oriented schedule of microgrids with hybrid energy storage system using model predictive control publication-title: Appl. Energy doi: 10.1016/j.apenergy.2021.118092 – start-page: 1 year: 2023 ident: 10.1016/j.renene.2023.119871_b22 article-title: Economic model predictive control for microgrid optimization: A review publication-title: IEEE Trans. Smart Grid – volume: 144 start-page: 767 year: 2017 ident: 10.1016/j.renene.2023.119871_b33 article-title: A novel global maximum power point tracking strategy (GMPPT) based on optimal current control for photovoltaic systems adaptive to variable environmental and partial shading conditions publication-title: Sol. Energy doi: 10.1016/j.solener.2017.02.017 – volume: 203 start-page: 102 year: 2023 ident: 10.1016/j.renene.2023.119871_b3 article-title: Two-level optimal scheduling method for a renewable microgrid considering charging performances of heat pump with thermal storages publication-title: Renew. Energy doi: 10.1016/j.renene.2022.12.031 – volume: 341 year: 2023 ident: 10.1016/j.renene.2023.119871_b18 article-title: Charging private electric vehicles solely by photovoltaics: A battery-free direct-current microgrid with distributed charging strategy publication-title: Appl. Energy doi: 10.1016/j.apenergy.2023.121058 – volume: 44 start-page: 19395 issue: 35 year: 2019 ident: 10.1016/j.renene.2023.119871_b7 article-title: Two-level energy management strategy for PV-Fuel cell-battery-based DC microgrid publication-title: Int. J. Hydrogen Energy doi: 10.1016/j.ijhydene.2018.04.013 – volume: 185 start-page: 86 year: 2022 ident: 10.1016/j.renene.2023.119871_b1 article-title: Effect of the temperature difference between land and lake on photovoltaic power generation publication-title: Renew. Energy doi: 10.1016/j.renene.2021.12.011 – volume: 37 start-page: 9907 issue: 8 year: 2022 ident: 10.1016/j.renene.2023.119871_b12 article-title: Overview of power converter control in microgrids—Challenges, advances, and future trends publication-title: IEEE Trans. Power Electron. doi: 10.1109/TPEL.2022.3159828 – volume: 24 start-page: 283 issue: 1 year: 2009 ident: 10.1016/j.renene.2023.119871_b32 article-title: Modeling and dynamic characteristic simulation of a proton exchange membrane fuel cell publication-title: IEEE Trans. Energy Convers. doi: 10.1109/TEC.2008.2011837 – volume: 280 year: 2020 ident: 10.1016/j.renene.2023.119871_b24 article-title: Control of an isolated microgrid using hierarchical economic model predictive control publication-title: Appl. Energy doi: 10.1016/j.apenergy.2020.115960 – volume: 11 start-page: 1089 issue: 2 year: 2020 ident: 10.1016/j.renene.2023.119871_b26 article-title: Distributed economic model predictive control for a wind–photovoltaic–battery microgrid power system publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2019.2919499 – volume: 136 year: 2021 ident: 10.1016/j.renene.2023.119871_b4 article-title: Model predictive control of microgrids – An overview publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2020.110422 – volume: 44 start-page: 25129 issue: 46 year: 2019 ident: 10.1016/j.renene.2023.119871_b14 article-title: Modeling, control and simulation of a photovoltaic /hydrogen/ supercapacitor hybrid power generation system for grid-connected applications publication-title: Int. J. Hydrogen Energy doi: 10.1016/j.ijhydene.2019.05.097 – volume: 8 start-page: 2370 issue: 5 year: 2017 ident: 10.1016/j.renene.2023.119871_b16 article-title: Multiagent system-based distributed coordinated control for radial DC microgrid considering transmission time delays publication-title: IEEE Trans. Smart Grid doi: 10.1109/TSG.2016.2524688 – volume: 316 year: 2022 ident: 10.1016/j.renene.2023.119871_b2 article-title: Quick reaching law based global terminal sliding mode control for wind/hydrogen/battery DC microgrid publication-title: Appl. Energy doi: 10.1016/j.apenergy.2022.119050 – volume: 100 start-page: 18 year: 2017 ident: 10.1016/j.renene.2023.119871_b27 article-title: Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage publication-title: Renew. Energy doi: 10.1016/j.renene.2016.05.006 – volume: 82 start-page: 72 year: 2019 ident: 10.1016/j.renene.2023.119871_b13 article-title: Current control based power management strategy for distributed power generation system publication-title: Control Eng. Pract. doi: 10.1016/j.conengprac.2018.09.025 – volume: 221 start-page: 195 year: 2018 ident: 10.1016/j.renene.2023.119871_b19 article-title: A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions publication-title: Appl. Energy doi: 10.1016/j.apenergy.2018.03.085 |
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