Issue
Sci. Tech. Energ. Transition
Volume 79, 2024
Decarbonizing Energy Systems: Smart Grid and Renewable Technologies
Article Number 89
Number of page(s) 23
DOI https://doi.org/10.2516/stet/2024085
Published online 30 October 2024
  • Al-Turjman F., Abujubbeh M. (2019) IoT-enabled smart grid via SM: an overview, Future Gener. Comput. Sys. 96, 579–590. [CrossRef] [Google Scholar]
  • Kimani K., Oduol V., Langat K. (2019) Cyber security challenges for IoT-based smart grid networks, Int. J. Crit. Infrastruct. Prot. 25, 36–49. [CrossRef] [Google Scholar]
  • Babar M., Tariq M.U., Jan M.A. (2020) Secure and resilient demand side management engine using machine learning for IoT-enabled smart grid, Sustain. Cities Soc. 62, 102370. [CrossRef] [Google Scholar]
  • Wang Z., Liu Y., Ma Z., Liu X., Ma J. (2020) LiPSG: lightweight privacy-preserving Q-learning-based energy management for the IoT-enabled smart grid, IEEE Internet Things J. 7, 5, 3935–3947. [CrossRef] [Google Scholar]
  • Bagdadee A.H., Hoque M.Z., Zhang L. (2020) IoT based wireless sensor network for power quality control in smart grid, Procedia Comput. Sci. 167, 1148–1160. [CrossRef] [Google Scholar]
  • Ghosh S. (2021) Neuro-fuzzy-based IoT assisted power monitoring system for smart grid, IEEE Access 9, 168587–168599. [CrossRef] [Google Scholar]
  • Swastika A.C., Pramudita R., Hakimi R. (2017) IoT-based smart grid system design for smart home, in: 2017 3rd International Conference on Wireless and Telematics (ICWT), Palembang, Indonesia, 27–28 July, IEEE, pp. 49–53. [Google Scholar]
  • Ejaz W., Naeem M., Shahid A., Anpalagan A., Jo M. (2017) Efficient energy management for the internet of things in smart cities, IEEE Commun. Mag. 55, 1, 84–91. [CrossRef] [Google Scholar]
  • Liu Y., Yang C., Jiang L., Xie S., Zhang Y. (2019) Intelligent edge computing for IoT-based energy management in smart cities, IEEE Netw. 33, 2, 111–117. [CrossRef] [Google Scholar]
  • Morstyn T., Hredzak B., Agelidis V.G. (2016) Control strategies for microgrids with distributed energy storage systems: an overview, IEEE Trans. Smart Grid 9, 4, 3652–3666. [Google Scholar]
  • Pawar P., TarunKumar M. (2020) An IoT based Intelligent Smart Energy Management System with accurate forecasting and load strategy for renewable generation, Measurement 152, 107187. [CrossRef] [Google Scholar]
  • Alam M.S., Arefifar S.A. (2019) Energy management in power distribution systems: review, classification, limitations and challenges, IEEE Access 7, 92979–93001. [CrossRef] [Google Scholar]
  • Su J., Chu X., Chen M., Kadry S. (2021) Internet-of-things-assisted smart grid applications in industry 4.0, IOP Conf. Ser. Earth Environ. Sci. 621, 1 012056. [CrossRef] [Google Scholar]
  • Bhattacharjee A., Samanta H., Banerjee N., Saha H. (2018) Development and validation of a real time flow control integrated MPPT charger for solar PV applications of vanadium redox flow battery, Energy Convers. Manag. 171, 1449–1462. [CrossRef] [Google Scholar]
  • Yilmaz U., Kircay A., Borekci S. (2018) PV system fuzzy logic MPPT method and PI control as a charge controller, Renew. Sustain. Energy Rev. 81, 994–1001. [CrossRef] [Google Scholar]
  • Naik R.S.K., Devaraju T. (2024) Intelligent distribution systems and grid integration of renewable energy resources, in: Second International Conference on Smart Technologies for Power and Renewable Energy (SPECon), Ernakulam, India, 2–4 April, IEEE, pp. 1–5. [Google Scholar]
  • Parimalasundar E., Hemanthkumar B., Roshini B., Hemalatha G.M., Preethi C.R., Krishna D.V.S. (2024) Enhancing efficiency and improving power quality in grid-connected 17-level multilevel inverters for renewable energy applications, in: Second International Conference on Smart Technologies for Power and Renewable Energy (SPECon), Ernakulam, India, 2–4 April, IEEE, pp. 1–5. [Google Scholar]
  • Mehta M., Mehta B., Patel M.V. (2024) Control strategies for grid-connected hybrid renewable energy systems: Integrating modified direct torque control based doubly fed induction generator and ANFIS based maximum power point tracking for solar PV generation, e-Prime Adv. Electr. Eng. Electron. Energy 8, 100575. [CrossRef] [Google Scholar]
  • Dharamalla C.S., Pokanati V.V.V.R.R., Kiranmayi R. (2022) A novel efficient adaptive-neuro fuzzy inference system control based smart grid to enhance power quality, Int. J. Electr. Comput. Eng. 12, 4, 3375–3387. [Google Scholar]
  • Bilgundi S.K., Sachin R., Pradeepa H., Nagesh H.B., Likith Kumar M.V. (2022) Grid power quality enhancement using an ANFIS optimized PI controller for DG, Pro. Control Mod. Power Syst. 7, 3. [CrossRef] [Google Scholar]
  • Ullah Z., Rehman A.U., Wang S., Hasanien H.M., Luo P., Elkadeem M.R., Abido M.A. (2023) IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration, Energy 282, 128924. [CrossRef] [Google Scholar]
  • Murugan G., Vijayarajan S. (2023) IoT based secured data monitoring system for renewable energy fed micro grid system, Sustain. Energy Technol. Assess. 57, 103244. [Google Scholar]
  • Reddy C.R.S.R., Prasanth B.V., Chandra B.M. (2023) Active power management of grid-connected PV-PEV using a hybrid GRFO-ITSA technique, Sci. Tech. Energ. Transition 78, 7. [CrossRef] [Google Scholar]
  • Manzoor A., Akram W., Judge M.A., Khan N., Khattak H.A. (2024) Efficient economic energy scheduling in smart cities using distributed energy resources, Sci. Tech. Energ. Transition 79, 29. [CrossRef] [Google Scholar]
  • Korlepara N.S.D., Elanchezhian E., Pragaspathy S., Subramanian S. (2024) Novel multi-port converter for distributed MPPT operation in solar PV system, Sci. Tech. Energ. Transition 79, 32. [CrossRef] [Google Scholar]
  • Colaco S.G., Varghese S.G., Kurian C.P., Sanjeev Kumar T.M. (2023) A state-of-the-art artificial intelligent techniques in daylighting controller: models and performance, Sci. Tech. Energ. Transition 78, 37. [CrossRef] [Google Scholar]
  • MathWorks, Implement model of variable pitch wind turbine Retrieved July 25, 2021, from https://www.mathworks.com/help/physmod/sps/powersys/ref/windturbine.html. [Google Scholar]
  • Suresh K., Vijay Babu A.R., Venkatesh P.M. (2018) Experimental investigations on grid integrated wind energy storage systems using neuro fuzzy controller, Meas. Control A 91, 123–130. [CrossRef] [Google Scholar]
  • Rahiman B.A., Jayakumar J., Meenal R. (2024) An improved MPPT approach using artificial neural network for PV grid system, in: International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI), Chennai, India, 17–18 April, IEEE, pp. 1–6. [Google Scholar]
  • Narasipuram R.P., Mopidevi S. (2024) Assessment of E-mode GaN technology, practical power loss, and efficiency modelling of iL2C resonant DC-DC converter for xEV charging applications, J. Energy Storage 91, 112008. [CrossRef] [Google Scholar]
  • Narasipuram R.P., Mopidevi S., Dianov A., Tandon A.S. (2024) Analysis of scalable resonant DC–DC converter using GaN switches for xEV charging stations, World Electr. Veh. J. 15, 218. [CrossRef] [Google Scholar]
  • Chaitanya S., Patnaik N.R., Murthy K.V.S.R. (2017) A novel seven level symmetrical multilevel inverter topology, in: 2017 Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bioinformatics (AEEICB), Chennai, India, 27–28 February, IEEE, pp. 432–435 [Google Scholar]
  • Narasipuram R.P., Mopidevi S. (2023) A dual primary side FB DC-DC converter with variable frequency phase shift control strategy for on/off board EV charging applications, in: 2023 9th IEEE India International Conference on Power Electronics (IICPE), Sonipat, India, 28–30 November, IEEE, pp. 1–5. [Google Scholar]
  • Abreu V., Santin A.O., Viegas E.K., Cogo V.V. (2020) Identity and access management for IoT in smart grid, in: Barolli L., Amato F., Moscato F., Enokido T., Takizawa M. (eds), International Conference on Advanced Information Networking and Applications, Springer, Cham, pp. 1215–1226. [CrossRef] [Google Scholar]
  • Narasipuram R.P., Mopidevi S. (2024) An industrial design of 400 V–48 V, 98.2% peak efficient charger using E-mode GaN technology with wide operating ranges for xEV applications, Int. J. Numer. Model. Electron. Networks Devices Fields 37, e3194. [CrossRef] [Google Scholar]
  • Suresh K., Venkatesan M., Vijay Babu A.R. (2017) Design and implementation of energy storage system by using converters and renewable energy source, J. Adv. Res. Dyn. Control Syst. 9, 5, 259–269. [Google Scholar]
  • Narasipuram R.P., Mopidevi S. (2023) Parametric modelling of interleaved resonant DC-DC converter with common secondary rectifier circuit for xEV charging applications, in: 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET), Ghaziabad, India, 14–15 September, IEEE, pp. 842–846. [Google Scholar]
  • Tabassum S., Vijay Babu A.R., Dheer D.K., Pasha M.M. (2022) Inspection and surveillance of energy consumption in iot-smart grid using wireless sensor network, in: 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON), Durgapur, India, 17–19 December, IEEE, pp. 308–312. [Google Scholar]
  • Rabie A.H., Saleh A.I., Ali H.A. (2021) Smart electrical grids based on cloud, IoT, and big data technologies: State of the art, J. Ambient Intell. Humaniz. Comput. 12, 10, 9449–9480. [CrossRef] [Google Scholar]
  • Narasipuram R., Karkhanis V., Ellinger M., Saranath K.M., Alagarsamy G., Jadhav R. (2024) Systems engineering – a key approach to transportation electrification, SAE Technical Paper 2024-26-0128. https://doi.org/10.4271/2024-26-0128. [Google Scholar]
  • Chaitanya S., Patnaik N.R., Raju C.B.A. (2018) A novel transformerless asymmetrical fifteen level inverter topology for renewable energy applications, in: 2018 Fourth International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), Chennai, India, 27–28 February, IEEE, pp. 1–4. [Google Scholar]
  • Babu A.V., Devunuri N., Manisha D.R., Prashanthi Y., Merugu R., Teja A.R. (2014) Magnesium hydrides for hydrogen storage: a mini review, Int. J. ChemTech Res 6, 7, 3451–3455. [Google Scholar]
  • Vijay Babu A.R., Srinivasa Rao G., Manoj Kumar P. (2020) A novel diagnostic technique to detect flooding and dehydration states of an air breathing fuel cell used in fuel cell vehicles, Int. J. Electr. Hybrid Veh. 12, 1, 32–43. [CrossRef] [Google Scholar]
  • Vijay Babu A.R., Srinivasa Rao G., Manoj Kumar P., Suman S., Sihari Babu A., Umamaheswararao Ch., Ravi Teja A.J.R. (2015) Energy and green house gas payback times of an air breathing fuel cell stack, J. Electri. Eng. 15, 4, 52–62. [Google Scholar]
  • Tabassum S., Babu A.R.V., Dheer D.K. (2023) Hybrid smart microgrid system modelling, design and control using an adaptive neuro fuzzy inference system, in: 2023 3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India, 21–22 December, IEEE, pp. 1–6. [Google Scholar]
  • Hamouda Y.E.M. (2017) Smart irrigation decision support based on fuzzy logic using wireless sensor network, in: Proceedings of the 2017 International Conference on Promising Electronic Technologies (ICPET), Deir El-Balah, Palestine, 16–17 October, IEEE, pp. 109–113. [Google Scholar]
  • Kamal J., Alharbi W., Muqaybil Y., Barkat E. (2024) Optimizing smart grid integration: a comprehensive analysis review of load flow and advanced optimization strategies, in: Proceedings of the 2024 21st Learning and Technology Conference (L&T), Jeddah, Saudi Arabia, 15–16 January, IEEE, pp. 115–120. [Google Scholar]
  • Tyagi S., Singh B., Das S. (2024) Control of interlinking converter for power quality improvement in hybrid microgrid, IEEE Trans. Ind. Electron. https://doi.org/10.1109/TIE.2024.3419224. [Google Scholar]
  • Sharma S., Jately V., Kuchhal P., Kala P., Azzopardi B. (2023) A comprehensive review of flexible power-point-tracking algorithms for grid-connected photovoltaic systems, Energies 16, 11, 5976. [CrossRef] [Google Scholar]
  • Xu Y., Dong Z., Li Z., Liu Y., Ding Z. (2021) Distributed optimization for integrated frequency regulation and economic dispatch in microgrids, IEEE Trans. Smart Grid 12, 5, 4595–4606. [CrossRef] [Google Scholar]
  • Ghafouri S., Gharehpetian G.B., Naderi M.S., Mahdavi M.S. (2024) An integrated multi-function control scheme for independent BESS in islanded synchronous generator-based microgrids, IEEE Trans. Ind. Electron. https://doi.org/10.1109/TII.2024.3435357. [Google Scholar]
  • Bhujel N., Rai A., Hummels D., Tamrakar U., Tonkoski R. (2024) Integrated voltage and frequency support in microgrids using droop and model predictive control with energy storage systems, in: Proceedings of the 2024 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), Napoli, Italy, 19–21 June, IEEE, pp. 141–146. [Google Scholar]
  • Saxena A., Shankar R., El-Saadany E., Kumar M., Al Zaabi O., Al Hosani K., Muduli U. R. (2024) Intelligent load forecasting and renewable energy integration for enhanced grid reliability, IEEE Trans. Ind. Appl. https://doi.org/10.1109/TIA.2024.3436471. [Google Scholar]
  • Xu H., Sun J., Huang J., Lin X., Ma C. (2024) Distributed optimization of islanded microgrids integrating multi-type VSG frequency regulation and integrated economic dispatch, Energies 17, 7, 1618. [CrossRef] [Google Scholar]
  • Al-Salloomee A.G.S., Romero-Cadaval E., Roncero-Clemente C., Swadi M. (2024) Efficient control scheme for compensating voltage unbalance and harmonics in islanded microgrid inverters, in: Proceedings of the 2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON), Porto, Portugal, 25–27 June, IEEE, pp. 574–579. [Google Scholar]
  • Javadi M., Gong Y., Chung C.Y. (2022) Frequency stability constrained microgrid scheduling considering seamless islanding, IEEE Trans. Power Syst. 37, 1, 306–316. [CrossRef] [Google Scholar]
  • Saranya D.N.S., Vijay Babu A.R., Srinivasa Rao G., Tagore Y.R., Bharath Kumar N. (2015) Fuel cell powered bidirectional DC-DC converter for electric vehicles, Int. J. Control Theory Appl. 8, 1, 109–120. [Google Scholar]
  • Banothu C.S., Rao G.S., Vijay Babu A.R. (2023) Magnetic coupling spiral-square coil mutual inductance evaluation for interoperable conditions with different misalignments, in: 2023 3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India, 21–22 December, IEEE, pp. 1–6. [Google Scholar]
  • Banothu C.S., Gorantla S.R., Attuluri R.V.B., Evuri G.R. (2024) Interoperable square-circular coupled coils for wireless electric vehicle battery charging system with different misalignments, IET Power Electron. https://doi.org/10.1049/pel2.12742. [Google Scholar]
  • Banothu C.S., Rao G.S., Babu A.R.V., Reddy E.G. (2024) Impacts of wireless charging system for electric vehicles on power grid, e-Prime-Adv. Electr. Eng. Electron. Energy 8, 100561. [CrossRef] [Google Scholar]
  • Zhang S., Wang C., Zhang H., Lin H. (2024) Collective dynamics of adaptive memristor synapse-cascaded neural networks based on energy flow, Chaos Solitons Fractals 186, 115191. [CrossRef] [Google Scholar]
  • Ma K., Yang J., Liu P. (2020) Relaying-assisted communications for demand response in smart grid: cost modeling, game strategies, and algorithms, IEEE J. Sel. Areas Commun. 38, 1, 48–60. [CrossRef] [Google Scholar]
  • Fang H., Ma S., Wang J., Zhao L., Nie F., Ma X., Lü W., Yan S., Zheng L. (2024) Multimodal in-sensor computing implemented by easily-fabricated oxide-heterojunction optoelectronic synapses, Adv. Funct. Mater. 2409045. [Google Scholar]
  • Li L., Han Y., Li Q., Chen W. (2024) Multi-dimensional economy-durability optimization method for integrated energy and transportation system of net-zero energy buildings, IEEE Trans. Sustain. Energy 15, 1, 146–159. [CrossRef] [Google Scholar]
  • Yin L., Wang L., Lu S., Wang R., Ren H., AlSanad A., AlQahtani S.A., Yin Z., Li X., Zheng W. (2024) AFBNet: a lightweight adaptive feature fusion module for super-resolution algorithms, Comput. Model. Eng. Sci. 140, 3, 2315–2347. [Google Scholar]
  • Wang B., Zheng W., Wang R., Lu S., Yin L., Wang L., Yin Z., Chen X. (2024) Stacked noise reduction auto encoder–OCEAN: a novel personalized recommendation model enhanced, Systems 12, 6, 188. [CrossRef] [Google Scholar]
  • Fang S., Zhang R., Maltsev S., Chen D., Fan X., Levtsev A. (2024) A novel adaptive fast sliding mode control method based on fuzzy algorithm for the air management system of fuel cell stack, Process Saf. Environ. Prot. 187, 506–517. [CrossRef] [Google Scholar]
  • Ju Y., Liu W., Zhang Z., Zhang R. (2022) Distributed three-phase power flow for AC/DC hybrid networked microgrids considering converter limiting constraints, IEEE Trans. Smart Grid 13, 3, 1691–1708. [CrossRef] [Google Scholar]
  • Shirkhani M., Tavoosi J., Danyali S., Sarvenoee A.K., Abdali A., Mohammadzadeh A., Zhang C. (2023) A review on microgrid decentralized energy/voltage control structures and methods, Energy Rep. 10, 368–380. [CrossRef] [Google Scholar]
  • Cao B., Zhao J., Liu X., Li Y. (2024) Adaptive 5G-and-beyond network-enabled interpretable federated learning enhanced by neuroevolution, Sci. China Inf. Sci. 67, 7, 170306. [CrossRef] [Google Scholar]
  • Zhou M., Zhao X., Luo F., Luo J., Pu H., Xiang T. (2023) Robust RGB-T tracking via adaptive modality weight correlation filters and cross-modality learning, ACM Trans. Multimedia Comput. Commun. Appl. 20, 4, 1–20. [Google Scholar]
  • Wang J., Li Y., Wu Y., Liu Z., Chen K., Chen C.L.P. (2024) Fixed-time formation control for uncertain nonlinear multiagent systems with time-varying actuator failures, IEEE Trans. Fuzzy Syst. 32, 4, 1965–1977. [CrossRef] [Google Scholar]
  • Wang J., Wu Y., Chen C.L.P., Liu Z., Wu W. (2024) Adaptive PI event-triggered control for MIMO nonlinear systems with input delay, Inf. Sci. 677, 120817. [CrossRef] [Google Scholar]
  • Meng Q., Tong X., Hussain S., Luo F., Zhou F., Liu L., He Y., Jin X., Li B. (2024) Revolutionizing photovoltaic consumption and electric vehicle charging: a novel approach for residential distribution systems, IET Gener. Transm. Dis. 18, 17, 2822–2833. [CrossRef] [Google Scholar]
  • Pavan G., Babu A.R. (2024) Enhanced randomized Harris Hawk optimization of PI controller for power flow control in the microgrid with the PV-wind-battery system, Sci. Tech. Energ. Transition 79, 45. [CrossRef] [Google Scholar]
  • Messaoudi H., Bourogaoui M., Abdelghani A.B.-B. (2024) Real-time simulation of a new design of a smart and fast electric vehicle charger, Sci. Tech. Energ. Transition. 79, 11. [Google Scholar]
  • Said-Romdhane M.B., Skander-Mustapha S., Belhassen R. (2023) Adaptive deadbeat predictive control for PMSM-based solar-powered electric vehicles with enhanced stator resistance compensation, Sci. Tech. Energ. Transition 78, 35. [CrossRef] [Google Scholar]
  • Tabassum S., Vijay Babu A.R., Dheer D.K. (2024) A comprehensive exploration of IoT-enabled smart grid systems: Power quality issues, solutions, and challenges, Sci. Tech. Energ. Transition 79, 62. [CrossRef] [Google Scholar]
  • Muller D.C., Selvanathan S.P., Cüce E., Kumarasamy S. (2023) Hybrid solar, wind, and energy storage system for a sustainable campus: a simulation study, Sci. Tech. Energ. Transition 78, 13. [CrossRef] [Google Scholar]
  • Antalem D.T., Muneer V., Avik B. (2022) Decentralized control of islanding/grid-connected hybrid DC/AC microgrid using interlinking converters, Sci. Tech. Energ. Transition 77, 22. [CrossRef] [Google Scholar]
  • Hole S.R., Goswami A.D. (2024) EPCMSDB: design of an ensemble predictive control model for solar PV MPPT deployments via dual bioinspired optimizations, Sci. Tech. Energ. Transition 79, 8. [CrossRef] [Google Scholar]
  • Meng Q., Jin X., Luo F., Wang Z., Hussain S. (2024) Distributionally robust scheduling for benefit allocation in regional integrated energy system with multiple stakeholders, J. Mod. Power Syst. Clean Energy 12, 1631–1642. [CrossRef] [Google Scholar]
  • Zhang J., Yang D., Li W., Zhang H., Li G., Gu P. (2024) Resilient output control of multiagent systems with dos attacks and actuator faults: fully distributed event-triggered approach, IEEE Trans. Cybern. 1–10. https://doi.org/10.1109/TCYB.2024.3404010. [Google Scholar]
  • Li P., Hu J., Qiu L., Zhao Y., Ghosh B.K. (2022) A distributed economic dispatch strategy for power–water networks, IEEE Trans. Control Netw. Syst. 9, 1, 356–366. [CrossRef] [MathSciNet] [Google Scholar]
  • Xu B., Guo Y. (2022) A novel DVL calibration method based on robust invariant extended Kalman filter, IEEE Trans. Veh. Technol. 71, 9, 9422–9434. [CrossRef] [Google Scholar]
  • Xu B., Wang X., Zhang J., Guo Y., Razzaqi A.A. (2022) A novel adaptive filtering for cooperative localization under compass failure and non-gaussian noise, IEEE Trans. Veh. Technol. 71, 4, 3737–3749. [CrossRef] [Google Scholar]
  • Hou X., Xin L., Fu Y., Na Z., Gao G., Liu Y., Xu Q., Zhao P., Yan G., Su Y., Cao K. (2023) A self-powered biomimetic mouse whisker sensor (BMWS) aiming at terrestrial and space objects perception, Nano Energy 118, 109034. [CrossRef] [Google Scholar]

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