CC BY
7УДК 620.9
Gaineev R.
student gr. ESm-1-23 Kazan State Power Engineering University (Kazan, Russia)
Scientific advisor: Marzoeva I.V.
Phd associate professor Kazan State Power Engineering University (Kazan, Russia)
FUTURE PROSPECTS OF SMART GRIDS FOR SUSTAINABLE ENERGY MANAGEMENT
Abstract: the growing demand for sustainable energy solutions and the need for more efficient energy management systems have led to the development and implementation of smart grids. The article presents the prospects for the innovative development of smart networks in Russia.
Keywords: energy efficiency, the intelligent power system, energy development, Smart Grid concept, smart accounting.
Smart Grid ("intelligent power supply networks") are modernized power supply networks that use information and communication networks and technologies to collect information about energy production and energy consumption, which automatically improves efficiency, reliability, and economic benefits. [1] Let's consider the principles of smart grid operation:
1. Flexibility. The network must adapt to the needs of electricity consumers.
2. Availability. The network should be accessible to new users, and user generated sources, including renewable energy sources with zero or reduced CO2 emissions, can act as new connections to the global network.
3. Reliability. The network must guarantee the security and quality of electricity supply in accordance with the requirements of the digital age.
4. Cost-effectiveness. Innovative technologies in the construction of a Smart Grid together with effective management and regulation of the functioning of the network should be of the greatest value. [2]
Big Data Management in Smart Grid. The real-time data entry is a key factor in a smart grid. It serves as the basis for the functioning of the network. smart grid is a rich source of information that covers data on the process of production, transmission, distribution and consumption of electricity [5]. This data includes electrical information from distribution stations, distribution switches, electricity meters, and non-electrical information such as marketing, meteorological, and regional economic data, as shown in Figure 1.
Fig. 1 Quantification of collected data with different sampling rates (Big data analytics and power consumption)
To predict the demand for energy at various locations, the algorithms must use all the data gathered from the sensors and associated devices. To produce the best results, the algorithms must be optimized. One of the main study subjects in smart grid technology is IT infrastructure, data gathering, governance, data processing, and, most critically, data security.[3]
By analyzing large volumes of data in real-time, utilities can make informed decisions to balance supply and demand, reduce wastage, and enhance reliability.
With the help of advanced algorithms and machine learning techniques, big data analytics can identify energy consumption patterns, predict peak demand periods, and adjust the distribution accordingly.
This proactive approach not only saves costs but also promotes sustainability by reducing the reliance on fossil fuels. [4]
Artificial intelligence technology plays a crucial role in improving demand response and optimizing energy storage. By analyzing large amounts of data in real time, artificial intelligence algorithms can predict the structure of energy demand and adjust the supply accordingly. This leads to a more efficient distribution of energy, reducing waste and costs. In addition, AI can optimize energy storage by determining the best time to charge or discharge batteries based on fluctuations in supply and demand. This helps to maximize the use of renewable energy sources and reduce dependence on fossil fuels. In general, artificial intelligence increases the efficiency of energy management by providing intelligent solutions that adapt to changing conditions, ultimately benefiting both consumers and the environment. [6]
In conclusion, the integration of smart grids and artificial intelligence has revolutionized the way we manage and optimize our energy consumption. With the help of technology, we achieve greater efficiency, reduce costs and make informed decisions for a sustainable future.
These achievements harmonize the complex elements of our energy systems, creating a seamless and intelligent network.
REFERENCES:
1. Dorofeev V.V., Makarov A.A. Active-adaptive network - a new quality of the UES of Russia [ Energoexpert] 2009, Vol 15, No. 4. (in Russian)
2. Inozemtsev N.A., Pascal I.N. Smart grid Technology. Collection of articles based on the materials of the XIII International scientific and practical conference [Innovations in Science and practice] 2018, pp. 30-37. (in Russian)
3. Peyghami, S., Palensky, P., & Blaabjerg, F. (2020). An Overview on the Reliability of Modern Power Electronic Based Power Systems. IEEE Open Journal of Power Electronics, 1, 34-50. https://doi.org/10.1109/ojpel.2020.2973926
4. Pal, R., Chavhan, S., Gupta, D., Khanna, A., Padmanaban, S., Khan, B., & Rodrigues, J. J. P. C. (2021, August 28). A comprehensive review on IoT-based infrastructure for smart grid applications. IET Renewable Power Generation, 15(16), 3761-3776. https://doi.org/10.1049/rpg2.12272
5. Sabirzyanova, A. S. Digital substation as a tool for increasing reliability of power supply / A. S. Sabirzyanova, G. Z. Gilyazieva // Энергетика и энергосбережение: теория и практика : СБОРНИК МАТЕРИАЛОВ VII МЕЖДУНАРОДНОЙ НАУЧНО-ПРАКТИЧЕСКОЙ КОНФЕРЕНЦИИ, Кемерово, 07-09 декабря 2022 года. - Кемерово: Кузбасский государственный технический университет имени Т.Ф. Горбачева, 2023. - P. 339-1-339-4. - EDN DZRZQH.
6. X. Fang, S. Misra, G. Xue and D. Yang, Smart Grid— The New and Improved Power Grid: A Survey [International Journal of IEEE Communications Surveys & Tutorials] Vol. 14, No. 4, 2011, pp. 944-980.
