Md Saiful Islam, Israt Jahan Bushra, Tushar Kanti Roy, Amanullah Maung Than Oo
{"title":"集成氢能系统的可再生能源混合交直流微电网稳定性增强智能鲁棒控制框架","authors":"Md Saiful Islam, Israt Jahan Bushra, Tushar Kanti Roy, Amanullah Maung Than Oo","doi":"10.1049/esi2.70035","DOIUrl":null,"url":null,"abstract":"<p>Hybrid AC/DC microgrids that integrate photovoltaic, wind, battery and hydrogen energy systems are prone to DC-bus voltage fluctuations because of their low inertia and converter-based operation. This paper proposes a robust backstepping nonsingular fast terminal integral sliding mode controller that incorporates a virtual capacitor and a fractional-power reaching law to emulate synthetic inertia and improve transient damping. The controller coordinates energy exchange among distributed generation units and ensures precise DC-bus voltage regulation while managing bidirectional power transfer between AC and DC subgrids. An adaptive neuro-fuzzy inference system automatically tunes the controller gains in real time, and system stability is rigorously established through control Lyapunov functions. A detailed MATLAB/Simulink model, comprising PV, PMSG-based wind turbine, battery storage, electrolyser and PEM fuel cell, implements ANN-based MPPT to maximise renewable energy harvesting. The BNFTISMC is evaluated in three case studies against two benchmark controllers: the enhanced integral terminal SMC and the enhanced nonsingular terminal SMC. Under severe disturbances and varying load conditions, the proposed controller cuts overshoot by 75%–100%, reduces rise time by 58%–80% and completely eliminates mean absolute and mean squared errors. Processor-in-the-loop testing confirms zero steady-state error, whereas converter efficiency reaches 95.78% compared with 69.21% for the reference designs, demonstrating improved DC-bus voltage regulation, enhanced microgrid reliability and efficient real-time operation.</p>","PeriodicalId":33288,"journal":{"name":"IET Energy Systems Integration","volume":"8 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.70035","citationCount":"0","resultStr":"{\"title\":\"An Intelligent Robust Control Framework for Stability Enhancement in Renewable Energy Powered Hybrid AC/DC Microgrids With Integrated Hydrogen Energy Systems\",\"authors\":\"Md Saiful Islam, Israt Jahan Bushra, Tushar Kanti Roy, Amanullah Maung Than Oo\",\"doi\":\"10.1049/esi2.70035\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Hybrid AC/DC microgrids that integrate photovoltaic, wind, battery and hydrogen energy systems are prone to DC-bus voltage fluctuations because of their low inertia and converter-based operation. This paper proposes a robust backstepping nonsingular fast terminal integral sliding mode controller that incorporates a virtual capacitor and a fractional-power reaching law to emulate synthetic inertia and improve transient damping. The controller coordinates energy exchange among distributed generation units and ensures precise DC-bus voltage regulation while managing bidirectional power transfer between AC and DC subgrids. An adaptive neuro-fuzzy inference system automatically tunes the controller gains in real time, and system stability is rigorously established through control Lyapunov functions. A detailed MATLAB/Simulink model, comprising PV, PMSG-based wind turbine, battery storage, electrolyser and PEM fuel cell, implements ANN-based MPPT to maximise renewable energy harvesting. The BNFTISMC is evaluated in three case studies against two benchmark controllers: the enhanced integral terminal SMC and the enhanced nonsingular terminal SMC. Under severe disturbances and varying load conditions, the proposed controller cuts overshoot by 75%–100%, reduces rise time by 58%–80% and completely eliminates mean absolute and mean squared errors. Processor-in-the-loop testing confirms zero steady-state error, whereas converter efficiency reaches 95.78% compared with 69.21% for the reference designs, demonstrating improved DC-bus voltage regulation, enhanced microgrid reliability and efficient real-time operation.</p>\",\"PeriodicalId\":33288,\"journal\":{\"name\":\"IET Energy Systems Integration\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2026-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/esi2.70035\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Energy Systems Integration\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/esi2.70035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Energy Systems Integration","FirstCategoryId":"1085","ListUrlMain":"https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/esi2.70035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
An Intelligent Robust Control Framework for Stability Enhancement in Renewable Energy Powered Hybrid AC/DC Microgrids With Integrated Hydrogen Energy Systems
Hybrid AC/DC microgrids that integrate photovoltaic, wind, battery and hydrogen energy systems are prone to DC-bus voltage fluctuations because of their low inertia and converter-based operation. This paper proposes a robust backstepping nonsingular fast terminal integral sliding mode controller that incorporates a virtual capacitor and a fractional-power reaching law to emulate synthetic inertia and improve transient damping. The controller coordinates energy exchange among distributed generation units and ensures precise DC-bus voltage regulation while managing bidirectional power transfer between AC and DC subgrids. An adaptive neuro-fuzzy inference system automatically tunes the controller gains in real time, and system stability is rigorously established through control Lyapunov functions. A detailed MATLAB/Simulink model, comprising PV, PMSG-based wind turbine, battery storage, electrolyser and PEM fuel cell, implements ANN-based MPPT to maximise renewable energy harvesting. The BNFTISMC is evaluated in three case studies against two benchmark controllers: the enhanced integral terminal SMC and the enhanced nonsingular terminal SMC. Under severe disturbances and varying load conditions, the proposed controller cuts overshoot by 75%–100%, reduces rise time by 58%–80% and completely eliminates mean absolute and mean squared errors. Processor-in-the-loop testing confirms zero steady-state error, whereas converter efficiency reaches 95.78% compared with 69.21% for the reference designs, demonstrating improved DC-bus voltage regulation, enhanced microgrid reliability and efficient real-time operation.