A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption

Hydrogen plays a crucial role in the quest for sustainable and clean energy solutions, and its effect on smart home energy management is of particular interest. With the rapid advancements in smart home technologies, energy optimization has become essential, aiming to achieve efficient energy consum...

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Main Authors: Heba Youssef, Salah Kamel, Mohamed H. Hassan, Juan Yu, M. Safaraliev, Хеба Юсеф, Салах Камель, Мохаммед Х. Хассан, Хуан Ю, М. Сафаралиев
Other Authors: This work was supported in part by the National Key R&D Program of China (No. 2021YFE0191000) and in part by Science, Technology & Innovation Funding Authority (STDF) (No. 43180). The icons used in this paper were developed by Freepik, Amethyst Design, Arkinasi, and Smashicons from www.flaticon.com, Эта работа была частично поддержана National Key R&D Program НИОКР Китая (№ 2021YFE0191000) и частично Фондом финансирования науки, технологий и инноваций Authority (STDF) (№ 43180). Иконки, используемые в этой статье, были разработаны Freepik, Amethyst Design, Arkinasi и Smashicons на сайте Flaticon.com
Format: Article in Journal/Newspaper
Language:English
Published: Международный издательский дом научной периодики "Спейс 2024
Subjects:
Online Access:https://www.isjaee.com/jour/article/view/2325
https://doi.org/10.15518/isjaee.2023.11.181-204
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institution Open Polar
collection Alternative Energy and Ecology (ISJAEE)
op_collection_id ftjisjaee
language English
topic управление спросом
home energy management
northern goshawk optimization
high and low-velocity ratios
demand side management
управление энергопотреблением в доме
оптимизация northern goshawk
соотношение высоких и низких скоростей
spellingShingle управление спросом
home energy management
northern goshawk optimization
high and low-velocity ratios
demand side management
управление энергопотреблением в доме
оптимизация northern goshawk
соотношение высоких и низких скоростей
Heba Youssef
Salah Kamel
Mohamed H. Hassan
Juan Yu
M. Safaraliev
Хеба Юсеф
Салах Камель
Мохаммед Х. Хассан
Хуан Ю
М. Сафаралиев
A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
topic_facet управление спросом
home energy management
northern goshawk optimization
high and low-velocity ratios
demand side management
управление энергопотреблением в доме
оптимизация northern goshawk
соотношение высоких и низких скоростей
description Hydrogen plays a crucial role in the quest for sustainable and clean energy solutions, and its effect on smart home energy management is of particular interest. With the rapid advancements in smart home technologies, energy optimization has become essential, aiming to achieve efficient energy consumption, cost reduction, and enhanced user comfort. Green hydrogen, produced through the electrolysis of water using renewable energy sources, emerges as a promising solution for sustainable energy. It offers numerous benefits, including zero greenhouse gas emissions, high energy density, and versatile applications. In the context of this study, the enhanced northern goshawk optimization (ENGO) algorithm and the original northern goshawk optimization (NGO) algorithm are investigated for optimizing smart home energy management. By employing a two-stage approach based on high and low-velocity ratios, ENGO overcomes the limitations of NGO, such as low exploitation capability and being trapped in local optima. The study demonstrates that ENGO outperforms NGO in achieving multiple objectives simultaneously, including reducing the peak-to-average ratio (PAR), lowering electricity costs, and ensuring user comfort. Furthermore, ENGO proves to be more robust, capable of handling complex smart home energy management problems with multiple constraints. Thus, the integration of hydrogen solutions, such as green hydrogen, with advanced optimization techniques like ENGO, can significantly contribute to the effective management of energy resources in smart homes, promoting sustainability and user satisfaction. Водород играет решающую роль в поиске устойчивых и чистых энергетических решений, и его влияние на управление энергопотреблением в "умном доме" представляет особый интерес. С быстрым развитием технологий "умного дома" оптимизация энергопотребления стала важной задачей, направленной на достижение эффективного энергопотребления, снижение затрат и повышение комфорта пользователей. Зеленый водород, получаемый путем электролиза ...
author2 This work was supported in part by the National Key R&D Program of China (No. 2021YFE0191000) and in part by Science, Technology & Innovation Funding Authority (STDF) (No. 43180). The icons used in this paper were developed by Freepik, Amethyst Design, Arkinasi, and Smashicons from www.flaticon.com
Эта работа была частично поддержана National Key R&D Program НИОКР Китая (№ 2021YFE0191000) и частично Фондом финансирования науки, технологий и инноваций Authority (STDF) (№ 43180). Иконки, используемые в этой статье, были разработаны Freepik, Amethyst Design, Arkinasi и Smashicons на сайте Flaticon.com
format Article in Journal/Newspaper
author Heba Youssef
Salah Kamel
Mohamed H. Hassan
Juan Yu
M. Safaraliev
Хеба Юсеф
Салах Камель
Мохаммед Х. Хассан
Хуан Ю
М. Сафаралиев
author_facet Heba Youssef
Salah Kamel
Mohamed H. Hassan
Juan Yu
M. Safaraliev
Хеба Юсеф
Салах Камель
Мохаммед Х. Хассан
Хуан Ю
М. Сафаралиев
author_sort Heba Youssef
title A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
title_short A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
title_full A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
title_fullStr A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
title_full_unstemmed A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
title_sort smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption
publisher Международный издательский дом научной периодики "Спейс
publishDate 2024
url https://www.isjaee.com/jour/article/view/2325
https://doi.org/10.15518/isjaee.2023.11.181-204
genre Northern Goshawk
genre_facet Northern Goshawk
op_source Alternative Energy and Ecology (ISJAEE); № 11 (2023); 181-204
Альтернативная энергетика и экология (ISJAEE); № 11 (2023); 181-204
1608-8298
op_relation https://www.isjaee.com/jour/article/view/2325/1877
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S.Z. Zhiznin, S. Vassilev, A.L. Gusev. Economics of secondary renewable energy sources with hydrogen generation, International Journal of Hydrogen Energy, 2019, 44(23), 11385-11393.
Valverde-Isorna Luis, Rosa Felipe, Bordons Carlos, Guerra J. Energy management strategies in hydrogen smart-grids: a laboratory experience. Int J Hydrogen Energy 2016;41(31):13715-25.
Zhang Xiongwen, Chan Siew Hwa, Kwee Ho Hiang, Siew-ChongTan, Li Mengyu, Li Guojun, Li Jun, Feng Zhenping. Towards a smart energy network: The roles of fuel/electrolysis cells and technological perspective. Int J Hydrogen Energy 2015;40(21):6866-919.
Tabanjat Abdulkader, Mohamed Becherif, Hissel Daniel, Ramadan HS. Energy management hypothesis for hybrid power system of H2/2/PV/GMT via AI techniques. Int J Hydrogen Energy 2018;43(6):3527-41.
Arabul Fatma Keskin, Arabul Ahmet Yigit, Kumru Celal Fadil, Boynuegri Ali Rifat. Providing energy management of a fuel cellebatteryewind turbineesolar panel hybrid off grid smart home system. Int J Hydrogen Energy, 2017;42(43):26906-13.
Asanova, S., et al., Optimization of the structure of autonomous distributed hybrid power complexes and energy balance management in them. International Journal of Hydrogen Energy, 2021. 46(70): p. 34542-34549.
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Mary, G.A. and R. Rajarajeswari, Smart grid cost optimization using genetic algorithm. Int. J. Res. Eng. Technol, 2014. 3(07): p. 282-287.
Zhang, J., et al., A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints. Applied energy, 2016. 183: p. 791-804.
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Miao, H., X. Huang, and G. Chen, A genetic evolutionary task scheduling method for energy efficiency in smart homes. International Review of Electrical Engineering (IREE), 2012. 7(5): p. 5897-5904.
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Surender Reddy, S., J.Y. Park, and C.M. Jung, Optimal operation of microgrid using hybrid differential evolution and harmony search algorithm. Frontiers in Energy, 2016. 10(3): p. 355-362.
Ma, K., et al., Residential power scheduling for demand response in smart grid. International Journal of Electrical Power & Energy Systems, 2016. 78: p. 320-325.
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Geem, Z.W. and Y. Yoon, Harmony search optimization of renewable energy charging with energy storage system. International Journal of Electrical Power & Energy Systems, 2017. 86: p. 120-126.
Wu, Z., et al., Energy-efficiency-oriented scheduling in smart manufacturing. Journal of Ambient Intelligence and Humanized Computing, 2019. 10: p. 969-978.
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op_doi https://doi.org/10.15518/isjaee.2023.11.181-204
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spelling ftjisjaee:oai:oai.alternative.elpub.ru:article/2325 2024-05-12T08:08:50+00:00 A smart home energy management approach incorporating an enhanced northern goshawk optimizer to enhance user comfort, minimize costs, and promote efficient energy consumption Подход к управлению энергопотреблением умного дома внедрением методики «улучшенного северного ястреба-тетеревятника»; оптимизация комфорта пользователя, минимизация затрат и содействие эффективному потреблению энергии Heba Youssef Salah Kamel Mohamed H. Hassan Juan Yu M. Safaraliev Хеба Юсеф Салах Камель Мохаммед Х. Хассан Хуан Ю М. Сафаралиев This work was supported in part by the National Key R&D Program of China (No. 2021YFE0191000) and in part by Science, Technology & Innovation Funding Authority (STDF) (No. 43180). The icons used in this paper were developed by Freepik, Amethyst Design, Arkinasi, and Smashicons from www.flaticon.com Эта работа была частично поддержана National Key R&D Program НИОКР Китая (№ 2021YFE0191000) и частично Фондом финансирования науки, технологий и инноваций Authority (STDF) (№ 43180). Иконки, используемые в этой статье, были разработаны Freepik, Amethyst Design, Arkinasi и Smashicons на сайте Flaticon.com 2024-04-09 application/pdf https://www.isjaee.com/jour/article/view/2325 https://doi.org/10.15518/isjaee.2023.11.181-204 eng eng Международный издательский дом научной периодики "Спейс https://www.isjaee.com/jour/article/view/2325/1877 S.Z. Zhiznin, N.N. Shvets, V.M. Timokhov, A.L. Gusev. Economics of hydrogen energy of green transition in the world and Russia. Part I, International Journal of Hydrogen Energy, 2023, 48(57), p. 21544-21567. S.Z. Zhiznin, S. Vassilev, A.L. Gusev. Economics of secondary renewable energy sources with hydrogen generation, International Journal of Hydrogen Energy, 2019, 44(23), 11385-11393. Valverde-Isorna Luis, Rosa Felipe, Bordons Carlos, Guerra J. Energy management strategies in hydrogen smart-grids: a laboratory experience. Int J Hydrogen Energy 2016;41(31):13715-25. Zhang Xiongwen, Chan Siew Hwa, Kwee Ho Hiang, Siew-ChongTan, Li Mengyu, Li Guojun, Li Jun, Feng Zhenping. Towards a smart energy network: The roles of fuel/electrolysis cells and technological perspective. Int J Hydrogen Energy 2015;40(21):6866-919. Tabanjat Abdulkader, Mohamed Becherif, Hissel Daniel, Ramadan HS. Energy management hypothesis for hybrid power system of H2/2/PV/GMT via AI techniques. Int J Hydrogen Energy 2018;43(6):3527-41. Arabul Fatma Keskin, Arabul Ahmet Yigit, Kumru Celal Fadil, Boynuegri Ali Rifat. Providing energy management of a fuel cellebatteryewind turbineesolar panel hybrid off grid smart home system. Int J Hydrogen Energy, 2017;42(43):26906-13. Asanova, S., et al., Optimization of the structure of autonomous distributed hybrid power complexes and energy balance management in them. International Journal of Hydrogen Energy, 2021. 46(70): p. 34542-34549. Asanov, M., et al., Design methodology of intelligent autonomous distributed hybrid power complexes with renewable energy sources. International Journal of Hydrogen Energy, 2023. Hashmi, M., S. Hänninen, and K. Mäki. Survey of smart grid concepts, architectures, and technological demonstrations worldwide. in 2011 IEEE PES conference on innovative smart grid technologies Latin America (ISGT LA). 2011. IEEE. Rahimi, F. and A. Ipakchi, Demand response as a market resource under the smart grid paradigm. IEEE Transactions on smart grid, 2010. 1(1): p. 82-88. Ozturk, Y., et al., An intelligent home energy management system to improve demand response. IEEE Transactions on smart Grid, 2013. 4(2): p. 694-701. Yi, P., et al., Real-time opportunistic scheduling for residential demand response. IEEE Transactions on smart grid, 2013. 4(1): p. 227-234. Molderink, A., et al. Domestic energy management methodology for optimizing efficiency in smart grids. in 2009 IEEE Bucharest PowerTech. 2009. IEEE. Tsui, K.M. and S.-C. Chan, Demand response optimization for smart home scheduling under real-time pricing. IEEE Transactions on Smart Grid, 2012. 3(4): p. 1812-1821. Logenthiran, T., D. Srinivasan, and T.Z. Shun, Demand side management in smart grid using heuristic optimization. IEEE transactions on smart grid, 2012. 3(3): p. 1244-1252. Muralitharan, K., R. Sakthivel, and Y. Shi, Multiobjective optimization technique for demand side management with load balancing approach in smart grid. Neurocomputing, 2016. 177: p. 110-119. Motevasel, M. and A.R. Seifi, Expert energy management of a micro-grid considering wind energy uncertainty. Energy Conversion and Management, 2014. 83: p. 58-72. Mary, G.A. and R. Rajarajeswari, Smart grid cost optimization using genetic algorithm. Int. J. Res. Eng. Technol, 2014. 3(07): p. 282-287. Zhang, J., et al., A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints. Applied energy, 2016. 183: p. 791-804. Siano, P., et al., Designing and testing decision support and energy management systems for smart homes. Journal of Ambient Intelligence and Humanized Computing, 2013. 4: p. 651-661. Miao, H., X. Huang, and G. Chen, A genetic evolutionary task scheduling method for energy efficiency in smart homes. International Review of Electrical Engineering (IREE), 2012. 7(5): p. 5897-5904. Agnetis, A., et al., Load scheduling for house-hold energy consumption optimization. IEEE Transactions on Smart Grid, 2013. 4(4): p. 2364-2373. Moenik, J., et al., A concept to optimize power consumption in smart homes based on demand-side management and using smart switches. Electrotechnical Review, 2013. 80(5): p. 217-221. Ogwumike, C., M. Short, and M. Denai. Near-optimal scheduling of residential smart home appliances using heuristic approach. in 2015 IEEE International Conference on Industrial Technology (ICIT). 2015. IEEE. Ahmad, A., et al., A modified feature selection and artificial neural network-based day-ahead load fore-casting model for a smart grid. Applied Sciences, 2015. 5(4): p. 1756-1772. Rastegar, M., M. Fotuhi-Firuzabad, and H. Zareipour, Home energy management incorporating operational priority of appliances. International Journal of Electrical Power & Energy Systems, 2016. 74: p. 286-292. Rasheed, M.B., et al., Priority and delay constrained demand side management in real‐time price environment with renewable energy source. International Journal of Energy Research, 2016. 40(14): p. 2002-2021. Khan, M.A., et al., A generic demand‐side management model for smart grid. International Journal of Energy Research, 2015. 39(7): p. 954-964. Surender Reddy, S., J.Y. Park, and C.M. Jung, Optimal operation of microgrid using hybrid differential evolution and harmony search algorithm. Frontiers in Energy, 2016. 10(3): p. 355-362. Ma, K., et al., Residential power scheduling for demand response in smart grid. International Journal of Electrical Power & Energy Systems, 2016. 78: p. 320-325. Rasheed, M.B., et al., Real time information based energy management using customer preferences and dynamic pricing in smart homes. Energies, 2016. 9(7): p. 542. Geem, Z.W. and Y. Yoon, Harmony search optimization of renewable energy charging with energy storage system. International Journal of Electrical Power & Energy Systems, 2017. 86: p. 120-126. Wu, Z., et al., Energy-efficiency-oriented scheduling in smart manufacturing. Journal of Ambient Intelligence and Humanized Computing, 2019. 10: p. 969-978. Moon, S. and J.-W. Lee, Multi-residential demand response scheduling with multi-class appliances in smart grid. IEEE transactions on smart grid, 2016. 9(4): p. 2518-2528. Jalili, H., et al., Modeling of demand response programs based on market elasticity concept. Journal of Ambient Intelligence and Humanized Computing, 2019. 10: p. 2265-2276. Khan, A., et al., A priority-induced demand side management system to mitigate rebound peaks using multiple knapsack. Journal of Ambient Intelligence and Humanized Computing, 2019. 10: p. 1655-1678. Liu, B., et al., Cost control of the transmission congestion management in electricity systems based on ant colony algorithm. Energy and Power Engineering, 2011. 3(01): p. 17. Tang, L., Y. Zhao, and J. Liu, An improved differential evolution algorithm for practical dynamic scheduling in steelmaking-continuous casting production. 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Alternative Energy and Ecology (ISJAEE); № 11 (2023); 181-204 Альтернативная энергетика и экология (ISJAEE); № 11 (2023); 181-204 1608-8298 управление спросом home energy management northern goshawk optimization high and low-velocity ratios demand side management управление энергопотреблением в доме оптимизация northern goshawk соотношение высоких и низких скоростей info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion 2024 ftjisjaee https://doi.org/10.15518/isjaee.2023.11.181-204 2024-04-18T16:57:46Z Hydrogen plays a crucial role in the quest for sustainable and clean energy solutions, and its effect on smart home energy management is of particular interest. With the rapid advancements in smart home technologies, energy optimization has become essential, aiming to achieve efficient energy consumption, cost reduction, and enhanced user comfort. Green hydrogen, produced through the electrolysis of water using renewable energy sources, emerges as a promising solution for sustainable energy. It offers numerous benefits, including zero greenhouse gas emissions, high energy density, and versatile applications. In the context of this study, the enhanced northern goshawk optimization (ENGO) algorithm and the original northern goshawk optimization (NGO) algorithm are investigated for optimizing smart home energy management. By employing a two-stage approach based on high and low-velocity ratios, ENGO overcomes the limitations of NGO, such as low exploitation capability and being trapped in local optima. The study demonstrates that ENGO outperforms NGO in achieving multiple objectives simultaneously, including reducing the peak-to-average ratio (PAR), lowering electricity costs, and ensuring user comfort. Furthermore, ENGO proves to be more robust, capable of handling complex smart home energy management problems with multiple constraints. Thus, the integration of hydrogen solutions, such as green hydrogen, with advanced optimization techniques like ENGO, can significantly contribute to the effective management of energy resources in smart homes, promoting sustainability and user satisfaction. Водород играет решающую роль в поиске устойчивых и чистых энергетических решений, и его влияние на управление энергопотреблением в "умном доме" представляет особый интерес. С быстрым развитием технологий "умного дома" оптимизация энергопотребления стала важной задачей, направленной на достижение эффективного энергопотребления, снижение затрат и повышение комфорта пользователей. Зеленый водород, получаемый путем электролиза ... Article in Journal/Newspaper Northern Goshawk Alternative Energy and Ecology (ISJAEE)