Smart home power management in the presence of electric vehicle to reduce operating costs

Subject Areas : International Journal of Smart Electrical Engineering

Mahdi Hajihosseinlou ^{1 *} , amir ebrahimi ² , Mahmoodreza Haghifam ³ , Majid Miri Laari ⁴

1 -
2 - Tarbiat Modares University, Tehran, Iran
3 - Tarbiat Modarres University
4 - Tarbiat Modares University

Received: 2024-09-28 Accepted : 2024-11-02 Published : 2025-01-29

Keywords: optimization, smart home energy management system, electric vehicle, renewable energy resources.,

Abstract :

In recent years, the increase in electricity consumption in the household sector and the increase in the purchase price of electricity have led to the creation of an energy management system in smart homes. The smart home energy management system schedules the equipment for the next 24 hours. This paper examines a smart home that incorporates new technologies like interruptible loads, electric vehicles, energy storage systems, renewable energy sources, and smart devices. In this paper, the smart home energy management system, knowing its consumption needs and the current price of electricity in the electricity market, provides the power it requires by purchasing from the power grid or using the production power of renewable energy resources. Additionally, the smart home energy management system can sell its excess production power to the grid in a few hours. This paper aims to reduce the operating costs of a smart home during the day, and it has done so in several different scenarios. The effect of charging and discharging electric vehicle, energy storage system, and renewable energy resources in reducing costs has been investigated in these scenarios.

References:

[1] A. R. Al-Ali, A. El-Hag, M. Bahadiri, M. Harbaji, and Y. Ali El Haj, “Smart Home Renewable Energy Management System,” Energy Procedia, vol. 12, pp. 120–126, 2011, doi: https://doi.org/10.1016/j.egypro.2011.10.017.

[2] X. Fang, S. Misra, G. Xue, and D. Yang, “Smart Grid — The New and Improved Power Grid: A Survey,” Commun. Surv. Tutorials, IEEE, vol. 14, pp. 944–980, 2012, doi: 10.1109/SURV.2011.101911.00087.

[3] I. Gonçalves, Á. Gomes, and C. Henggeler Antunes, “Optimizing the management of smart home energy resources under different power cost scenarios,” Appl. Energy, vol. 242, pp. 351–363, 2019, doi: https://doi.org/10.1016/j.apenergy.2019.03.108.

[4] A. Saif, S. K. Khadem, M. F. Conlon, and B. Norton, “Impact of Distributed Energy Resources in Smart Homes and Community-Based Electricity Market,” IEEE Trans. Ind. Appl., vol. 59, no. 1, pp. 59–69, 2023, doi: 10.1109/TIA.2022.3202756.

[5] P. P. Gaikwad, J. P. Gabhane, and S. S. Golait, “A survey based on Smart Homes system using Internet-of-Things,” in 2015 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC), 2015, pp. 330–335. doi: 10.1109/ICCPEIC.2015.7259486.

[6] M. R. Alam, M. B. I. Reaz, and M. A. M. Ali, “A Review of Smart Homes—Past, Present, and Future,” IEEE Trans. Syst. Man, Cybern. Part C (Applications Rev., vol. 42, no. 6, pp. 1190–1203, 2012, doi: 10.1109/TSMCC.2012.2189204.

[7] V. Pilloni, A. Floris, A. Meloni, and L. Atzori, “Smart Home Energy Management Including Renewable Sources: A QoE-Driven Approach,” IEEE Trans. Smart Grid, vol. 9, no. 3, pp. 2006–2018, 2018, doi: 10.1109/TSG.2016.2605182.

[8] J. P. Sausen, M. F. B. Binelo, M. D. Campos, A. T. Z. R. Sausen, and P. S. Sausen, “Economic Feasibility Study Of Using An Electric Vehicle And Photovoltaic Microgeneration In A Smart Home,” IEEE Lat. Am. Trans., vol. 16, no. 7, pp. 1907–1913, 2018, doi: 10.1109/TLA.2018.8447356.

[9] A. Solat, S. H. Hosseinian, G. B. Gharehpetian, and S. M. Hosseini, “Optimal Energy Dispatch of Smart Home Equipped with PV, WT, and ESS Using Load Control under RTP,” in 2018 Smart Grid Conference (SGC), 2018, pp. 1–7. doi: 10.1109/SGC.2018.8777872.

[10] L. Chandra and S. Chanana, “Energy Management of Smart Homes with Energy Storage, Rooftop PV and Electric Vehicle,” in 2018 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), 2018, pp. 1–6. doi: 10.1109/SCEECS.2018.8546857.

[11] Z. Yahia and A. Pradhan, “Optimal load scheduling of household appliances considering consumer preferences: An experimental analysis,” Energy, vol. 163, pp. 15–26, 2018, doi: https://doi.org/10.1016/j.energy.2018.08.113.

[12] S. Pal and R. Kumar, “Smart Household Energy Management by Employing EV and BESS as Enabling Technologies,” in 2018 8th IEEE India International Conference on Power Electronics (IICPE), 2018, pp. 1–6. doi: 10.1109/IICPE.2018.8709595.

[13] M. Yousefi, A. Hajizadeh, and M. N. Soltani, “A Comparison Study on Stochastic Modeling Methods for Home Energy Management Systems,” IEEE Trans. Ind. Informatics, vol. 15, no. 8, pp. 4799–4808, 2019, doi: 10.1109/TII.2019.2908431.

[14] S. Aznavi, P. Fajri, A. Asrari, and F. Harirchi, “Realistic and Intelligent Management of Connected Storage Devices in Future Smart Homes Considering Energy Price Tag,” IEEE Trans. Ind. Appl., vol. 56, no. 2, pp. 1679–1689, 2020, doi: 10.1109/TIA.2019.2956718.

[15] Y. Liu, L. Xiao, G. Yao, and S. Bu, “Pricing-Based Demand Response for a Smart Home With Various Types of Household Appliances Considering Customer Satisfaction,” IEEE Access, vol. 7, pp. 86463–86472, 2019, doi: 10.1109/ACCESS.2019.2924110.

[16] M. Alilou, B. Tousi, and H. Shayeghi, “Home energy management in a residential smart micro grid under stochastic penetration of solar panels and electric vehicles,” Sol. Energy, vol. 212, pp. 6–18, 2020, doi: https://doi.org/10.1016/j.solener.2020.10.063.

[17] J. Zhao, S. Kucuksari, E. Mazhari, and Y.-J. Son, “Integrated analysis of high-penetration PV and PHEV with energy storage and demand response,” Appl. Energy, vol. 112, no. C, pp. 35–51, 2013, doi: 10.1016/j.apenergy.2013.0.

[18] D. Q. Hung, N. Mithulananthan, and K. Y. Lee, “Determining PV Penetration for Distribution Systems With Time-Varying Load Models,” IEEE Trans. Power Syst., vol. 29, no. 6, pp. 3048–3057, 2014, doi: 10.1109/TPWRS.2014.2314133.

[19] R. Jabbari-Sabet, S.-M. Moghaddas-Tafreshi, and S.-S. Mirhoseini, “Microgrid operation and management using probabilistic reconfiguration and unit commitment,” Int. J. Electr. Power Energy Syst., vol. 75, pp. 328–336, 2016, doi: https://doi.org/10.1016/j.ijepes.2015.09.012.

[20] Bagen, “Reliability and cost/worth evaluation of generating systems utilizing wind and solar energy,” 2005.