Integrated Home Energy Management with Hybrid Backup Storage and Vehicle-to-Home Systems for Enhanced Resilience, Efficiency, and Energy Independence in Green Buildings
Source abstract
Abstract
This study presents an innovative home energy management system (HEMS) that incorporates PV, WTs, and hybrid backup storage systems, including a hydrogen storage system (HSS), a battery energy storage system (BESS), and electric vehicles (EVs) with vehicle-to-home (V2H) technology. The research, conducted in Liaoning Province, China, evaluates the performance of the HEMS under various demand response (DR) scenarios, aiming to enhance resilience, efficiency, and energy independence in green buildings. Four DR scenarios were analyzed: No DR, 20% DR, 30% DR, and 40% DR. The findings indicate that implementing DR programs significantly reduces peak load and operating costs. The 40% DR scenario achieved the lowest cumulative operating cost of $749.09, reflecting a 2.34% reduction compared with the $767.07 cost in the No DR scenario. The integration of backup systems, particularly batteries and fuel cells (FCs), effectively managed energy supply, ensuring continuous power availability. The system maintained a low loss of power supply probability (LPSP), indicating high reliability. Advanced optimization techniques, particularly the reptile search algorithm (RSA), are crucial in enhancing system performance and efficiency. These results underscore the potential of hybrid backup storage systems with V2H technology to enhance energy independence and sustainability in residential energy management.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Technologies Research · Electric Vehicles and Infrastructure · Smart Grid Energy Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
References (60)
Show source-provided references
1. Navigating the global energy landscape balancing growth, demand, and sustainability
2. Lovering, J., Swain, M., Blomqvist, L., and Hernandez, R.R. (2022). Land-use intensity of electricity production and tomorrow’s energy landscape. PLoS ONE, 17.10.1371/journal.pone.0270155 ↗
3. Natural resource scarcity, fossil fuel energy consumption, and total greenhouse gas emissions in top emitting countries10.1016/j.gsf.2023.101757 ↗
4. Yoro, K.O., and Daramola, M.O. (2020). CO2 emission sources, greenhouse gases, and the global warming effect. Advances in Carbon Capture, Elsevier.10.1016/B978-0-12-819657-1.00001-3 ↗
5. Palm, R., Bolsen, T., Palm, R., and Bolsen, T. (2020). The Science of Climate Change and Sea-Level Rise. Climate Change and Sea Level Rise in South Florida, Springer.10.1007/978-3-030-32602-9 ↗
6. How different power plant types contribute to electric grid reliability, resilience, and vulnerability: A comparative analytical framework10.1088/2516-1083/abf636 ↗
7. Changes in energy consumption and CO2 emissions in the Lithuanian household sector caused by environmental awareness and climate change policy10.1016/j.enpol.2023.113687 ↗
8. Home energy management system (HEMS): Concept, architecture, infrastructure, challenges and energy management schemes10.1007/s12667-019-00364-w ↗
9. Home energy management system concepts, configurations, and technologies for the smart grid10.1109/ACCESS.2020.3005244 ↗
10. Optimal resilient operation and sustainable power management within an autonomous residential microgrid using African vultures optimization algorithm10.1016/j.renene.2024.120247 ↗
11. Renewable energy systems for building heating, cooling and electricity production with thermal energy storage10.1016/j.rser.2022.112560 ↗
12. Smart home energy management system—A review10.1080/17512549.2020.1806925 ↗
13. Tahirou Halidou, I., Or Rashid Howlader, H., Gamil, M.M., Elkholy, M.H., and Senjyu, T. (2023). Optimal Power Scheduling and Techno-Economic Analysis of a Residential Microgrid for a Remotely Located Area: A Case Study for the Sahara Desert of Niger. Energies, 16.10.3390/en16083471 ↗
14. Optimal sizing of PV-BESS units for home energy management system-equipped households considering day-ahead load scheduling for demand response and self-consumption10.1016/j.enbuild.2022.112164 ↗
15. Rotor equivalent wind speed prediction based on mechanism analysis and residual correction using Lidar measurements10.1016/j.enconman.2023.117385 ↗
16. Gamil, M.M., Masrur, H., Muttaqi, K.M., Huang, Y., Lotfy, M.E., and Senjyu, T. (2022, January 9–14). Multi-objective Optimal Power Scheduling of A Residential Microgrid Considering V2G and Demand Response Techniques. Proceedings of the 2022 IEEE Industry Applications Society Annual Meeting (IAS), Detroit, MI, USA.10.1109/IAS54023.2022.9939886 ↗
17. A comprehensive review on renewable energy integration for combined heat and power production10.1016/j.enconman.2020.113454 ↗
18. Integration and performance analysis of optimal large-scale hybrid PV and pump hydro storage system based upon floating PV for practical application
19. Alblawi, A., Said, T., Talaat, M., and Elkholy, M.H. (2022, January 29–31). PV solar power forecasting based on hybrid MFFNN-ALO. Proceedings of the 2022 13th International Conference on Electrical Engineering (ICEENG), Cairo, Egypt.10.1109/ICEENG49683.2022.9782040 ↗
20. Experimental Investigation of AI-Enhanced FPGA-Based Optimal Management and Control of an Isolated Microgrid10.1109/TTE.2023.3315729 ↗
21. Rekioua, D. (2023). Energy Storage Systems for Photovoltaic and Wind Systems: A Review. Energies, 16.10.3390/en16093893 ↗
22. Dufo-López, R., and Lujano-Rojas, J.M. (2024). Simulation and Optimisation of Utility-Scale PV–Wind Systems with Pumped Hydro Storage. Appl. Sci., 14.10.20944/preprints202407.1539.v1 ↗
23. Liang, Y., Liu, H., Zhou, H., Meng, Z., Liu, J., and Zhou, M. (2024). Multi-Stage Coordinated Planning for Transmission and Energy Storage Considering Large-Scale Renewable Energy Integration. Appl. Sci., 14.10.3390/app14156486 ↗
24. National infrastructures as complex interactive networks
25. A home energy management system with an integrated smart thermostat for demand response in smart grids10.1016/j.scs.2020.102639 ↗
26. Demand Response Strategy Based on Reinforcement Learning and Fuzzy Reasoning for Home Energy Management10.1109/ACCESS.2020.2974286 ↗
27. Optimization strategy based on deep reinforcement learning for home energy management
28. Optimizing residential demand response in Ghana through iterative techniques and home appliance trend analysis10.1016/j.heliyon.2024.e25807 ↗
29. Optimization model for home energy management system of rural dwellings10.1016/j.energy.2023.129039 ↗
30. Optimizing home energy management: Robust and efficient solutions powered by attention networks10.1016/j.heliyon.2024.e26397 ↗
31. Energy optimization of the smart residential electrical grid considering demand management approaches10.1016/j.energy.2024.131641 ↗
32. Research on interval optimization of power system considering shared energy storage and demand response10.1016/j.est.2024.111273 ↗
33. Techno-economic optimization of hybrid solar system with energy storage for increasing the energy independence in green buildings10.1016/j.est.2023.106642 ↗
34. Optimizing design and performance assessment of a community-scale hybrid power system with distributed renewable energy and flexible demand response10.1016/j.scs.2022.104042 ↗
35. Distributed energy management of electric vehicle charging stations based on hierarchical pricing mechanism and aggregate feasible regions10.1016/j.energy.2024.130332 ↗
36. Alonso-Cepeda, A., Villena-Ruiz, R., Honrubia-Escribano, A., and Gómez-Lázaro, E. (2024). A Review on Electric Vehicles for Holistic Robust Integration in Cities: History, Legislation, Meta-Analysis of Technology and Grid Impact. Appl. Sci., 14.10.3390/app14167147 ↗
37. Optimizing solar-wind hybrid energy systems for sustainable charging stations and commercial applications: A two-stage framework with ebola-inspired optimization10.1016/j.eswa.2024.123180 ↗
38. A CCP-based distributed cooperative operation strategy for multi-agent energy systems integrated with wind, solar, and buildings10.1016/j.apenergy.2024.123275 ↗
39. Zhang, H., Li, Z., Xue, Y., Chang, X., Su, J., Wang, P., Guo, Q., and Sun, H. (2024). A Stochastic Bi-level Optimal Allocation Approach of Intelligent Buildings Considering Energy Storage Sharing Services. IEEE Trans. Consum. Electron.10.1109/TCE.2024.3412803 ↗
40. Optimal scheduling algorithm for residential building distributed energy source systems using Levy flight and chaos-assisted artificial rabbits optimizer10.1016/j.egyr.2023.05.004 ↗
41. Hybrid Hydrogen Home Storage for Decentralized Energy Autonomy10.1016/j.ijhydene.2021.04.036 ↗
42. Multi-objective optimization of a hybrid renewable energy system supplying a residential building using NSGA-II and MOPSO algorithms10.1016/j.enconman.2023.117515 ↗
43. Vehicle-to-home operation and multi-location charging of electric vehicles for energy cost optimisation of households with photovoltaic system and battery energy storage10.1016/j.renene.2023.119729 ↗
44. Almutairi, K., Hosseini Dehshiri, S.S., Hosseini Dehshiri, S.J., Mostafaeipour, A., Issakhov, A., and Techato, K. (2021). Use of a Hybrid Wind—Solar—Diesel—Battery Energy System to Power Buildings in Remote Areas: A Case Study. Sustainability, 13.10.3390/su13168764 ↗
45. Techno-economic modeling and optimal sizing of autonomous hybrid microgrid renewable energy system for rural electrification sustainability using HOMER and grasshopper optimization algorithm10.1016/j.renene.2024.120712 ↗
46. Real-time energy scheduling for home energy management systems with an energy storage system and electric vehicle based on a supervised-learning-based strategy10.1016/j.enconman.2023.117340 ↗
47. An optimal home energy management system with integration of renewable energy and energy storage with home to grid capability10.1002/er.7735 ↗
48. Peer-to-peer home energy management incorporating hydrogen storage system and solar generating units10.1016/j.renene.2020.04.090 ↗
49. A data-driven DRL-based home energy management system optimization framework considering uncertain household parameters10.1016/j.apenergy.2023.122258 ↗
50. Mahmoud, F.S., Abdelhamid, A.M., Al Sumaiti, A., El-Sayed, A.-H.M., and Diab, A.A.Z. (2022). Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm. Mathematics, 10.10.3390/math10193708 ↗
51. Optimal sizing of stand-alone photovoltaic/wind/hydrogen hybrid system supplying a desalination unit10.1016/j.solener.2015.07.032 ↗
52. Artificial bee swarm optimization for optimum sizing of a stand-alone PV/WT/FC hybrid system considering LPSP concept10.1016/j.solener.2014.05.016 ↗
53. Technico-economic analysis of off grid solar PV/Fuel cell energy system for residential community in desert region10.1016/j.ijhydene.2018.05.110 ↗
54. Design and implementation of a Real-time energy management system for an isolated Microgrid: Experimental validation10.1016/j.apenergy.2022.120105 ↗
55. Economic analysis of integrated renewable energy system for electrification of remote rural area having scattered population
56. Kumar, N.M., Chopra, S.S., Chand, A.A., Elavarasan, R.M., and Shafiullah, G.M. (2020). Hybrid Renewable Energy Microgrid for a Residential Community: A Techno-Economic and Environmental Perspective in the Context of the SDG7. Sustainability, 12.10.3390/su12103944 ↗
57. Optimal sizing of hybrid renewable energy systems in presence of electric vehicles using multi-objective particle swarm optimization10.1016/j.energy.2020.118471 ↗
58. Maximizing microgrid resilience: A two-stage AI-Enhanced system with an integrated backup system using a novel hybrid optimization algorithm10.1016/j.jclepro.2024.141281 ↗
59. Zhang, N., Yang, N.-C., and Liu, J.-H. (2021). Optimal Sizing of PV/Wind/Battery Hybrid Microgrids Considering Lifetime of Battery Banks. Energies, 14.10.3390/en14206655 ↗
60. Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer10.1016/j.eswa.2021.116158 ↗