Document Type : Research article
Authors
1 Khuzestan Regional Electric Company, Ahvaz 61365-1373, Iran
2 Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz 61357-85311, Iran
3 Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful 646616-45169, Iran
Abstract
Internet of Things (IoT)-based energy management systems (EMSs) are considered a new technology in which consumers can manage their electricity payments according to their preferences, such as reducing costs or increasing satisfaction. Each consumer has its own program for communicating with a central control unit. In addition, the central control unit that is responsible for energy pricing can access consumer information and network performance status through the IoT infrastructure. Therefore, technical analysis can be performed using big data to determine the optimal price in order to make a compromise between the buyer and the goals of the distribution system operators. This paper presents a model to accurately assess the impact of pricing on the behavior of IoT-based energy systems. Then, according to the load specifications of each item and the technical limitations of the distribution network, the best time to use pricing is determined. The results show that the higher the price variance, the more discomfort the consumer and the lower the daily payment. Therefore, in this paper, the main goal of energy management is to minimize the total weight of the costs paid and their discomfort level. The paper could facilitate further penetration of IoT-based EMSs into smart grids. The study was performed on an IEEE standard 33-bus network. Optimization was implemented using YALMIP and MOSEK toolboxes. Therefore, it can be concluded that IoT technology allows consumers to enjoy the benefits of the network and makes optimal consumption management possible.
Highlights
- Proposing an energy management system (EMS) in the presence of the Internet of Things (IoT)
- Using the Kohlberg convergence distance to show the difference between the general consumer distribution function and the normal distribution function
- Considering the effect of changes in consumer behavior on energy management in the presence of IoT
- Considering the effect of consumer discomfort on energy management in the presence of IoT
Keywords
Main Subjects
- B. Guneet, G. K. Venayagamoorthy, R. Singh, R. R. Brooks, and K. C. Wang, "Review of internet of things (IoT) in electric power and energy systems," IEEE Internet of Things Journal, vol. 5, no. 2, pp. 847-870, April 2018.
- N. Silva, M. Khan, and K. Han, "Internet of things: A comprehensive review of enabling technologies, architecture, and challenges," IETE Technical Review, vol. 35, no. 2, pp. 205-220, 2018.
- Aazam, S. Zeadally, and K. A. Harras, "Deploying fog computing in industrial internet of things and industry 4.0", IEEE Transactions on Industrial Informatics, vol. 14, no. 10, pp. 4674-4682, 2018.
- S. Reka, and T. Dragicevic, "Future effectual role of energy delivery: A comprehensive review of internet of things and smart grid", Renewable and Sustainable Energy Reviews, vol. 91, pp. 90-108, 2018.
- Biljana, L. Risteska, and K. V. Trivodaliev, "A review of internet of things for smart home: challenges and solutions," Journal of Cleaner Generation, vol. 140, no. 3, pp. 1454-1464, 2017.
- Collier, and E. Steven, "The emerging enernet: Convergence of the smart grid with the internet of things." IEEE Industry Applications Magazine, vol. 23, no. 2, pp. 12-16, 2017.
- Talari, M. Shafie-Khah, P. Siano, V. Loia, A. Tommasetti, and J. P. Catalão, "A review of smart cities based on the internet of things concept", Energies, vol. 10, no. 4, 421, 2017.
- Yang, "Internet of things application in smart grid: A brief overview of challenges, opportunities, and future trends in smart power distribution systems", Academic Press, pp. 267-283, 2019.
- Zareifar, H. Zartabi, and Z. Ouraei, "Internet of things benefits on smart grid," in 27th Iranian Conference on Electrical Engineering (ICEE), 2019, pp. 725-730.
- Xu, W. Yu, D. Griffith, N. Golmie, and P. Moulema, "Toward integrating distributed energy resources and storage devices in smart grid", IEEE Internet of Things Journal, vol. 4, no. 1, pp. 192-204, 2017.
- Basit, G. A. S. Sidhu, A. Mahmood, and F. Gao, “Efficient and autonomous energy management techniques for the future smart homes,” IEEE Transactions on Smart Grid, vol. 8, no. 2, pp. 917-926, 2017.
- Mohseni, M. Joorabian, A. Lashkar Ara, "Distribution system reconfiguration in presence of Internet of Things,'' IET Generation, Transmission and Distribution, vol. 15, no. 3, 2020.
- (April 1, 2022). Siemens to build digital substation with grid IoT applications for Glitre Energi Nett [Online]. Available: https://press.siemens.com/global/en/pressrelease/siemens-build-digital-substation-grid-iot-applications-glitre-energi-nett.
- (April 1, 2022). Cybersane Project [Online]. Available: https://www.cybersane-project.eu/project/.
- Ashrafi, and S. Soleymani, "An energy management system based on economic and environmental aspects for microgrids incorporating active and reactive power sources and demand response programs," International Journal of Industrial Electronics, Control and Optimization, vol. 3, no. 3, pp. 259-273, 2020.
- Vosoogh, M. Rashidinejad, and A. Abdollahi, "Efficient networked microgrid management considering plug-in electric vehicles and storage units," International Journal of Industrial Electronics Control and Optimization, vol. 4, no. 2, pp. 245-255, 2019.
- Li and S. Wang, "Energy management and operational control methods for grid battery energy storage systems," CSEE Journal of Power and Energy Systems, vol. 7, no. 5, pp.1026-1040, 2021,
- U. Saleem, M. R. Usman, and M. Shakir, "Design, implementation, and deployment of an IoT based smart energy management system," IEEE Access, vol. 9, pp. 59649-59664, 2021.
- Mohammadi, A. Kavousi-Fard, M. Dabbaghjamanesh, A. Farughian, and A. Khosravi, "Effective management of energy internet in renewable hybrid microgrids: a secured data driven resilient architecture," IEEE Transactions on Industrial Informatics, vol. 18, no. 3, pp. 1896-1904, 2022.
)