Autors: Georgiev, M. G., Georgieva, A. N., Stoitseva-Delicheva, D. R., Gospodinova, D. N., Milanov, K. G.
Title: RES Digital Twin for Smart Energy Management Flexibility Research
Keywords: algorithm, demand response, digital twins, flexible energy management, RES, smart energy system

Abstract: In recent years, guidelines in developing energy systems have proposed massive participation of renewable energy sources. This inevitably leads to an increase in the flexibility of networks in terms of the ability to react to load changes quickly, but it also has disadvantages due to the random nature of energy production from RES. One of the main guidelines in the construction of future energy installations is to ensure flexibility in case of a lack or surplus of energy in the network. This flexibility could be ensured by synchronizing the load operation, storage capacity utilization, and generation facilities flexible control. It could be granted by developing new algorithms for adequate reaction based on energy availability and demand response techniques and IoT technologies for metering and control. Testing of such algorithms involves the construction of pilot installations or laboratory models. This approach is expensive, time-consuming, and allows us to test a limited range of algorithms. Another approach is to use mathematical models or digital twins. Well-designed digital twin helps consolidate real-object data and make it available for use by machine learning and artificial intelligence algorithms to support decision-making in complex real-world situations, including energy systems. This article considers the application of power system control based on a programmable logic controller and virtual environment for simulating the behavior of loads, batteries, and photovoltaic installations. It proposes an approach to create a digital twin of energy system designed to easily and safely implement flexible algorithms for managing energy production and demand response.

References

  1. Laxmikant D. Jathar, S. Ganesan, et al. Comprehensive review of environmental factors influencing the performance of photovoltaic panels: Concern over emissions at various phases throughout the lifecycle,Environmental Pollution,Volume 326,2023,121474, ISSN 0269-7491,https://doi.org/10.1016/j.envpol.2023.121474.
  2. Strategic Energy Technology Plan, Energy, Climate change, Environment, European Commission https://energy.ec.europa.eu/topics/research-and-technology/strategicenergy-technology-plan_en
  3. European Comission, State of the Energy Union Report 2024, Brussels, 11.9.2024, COM(2024) 404 final
  4. Angelova DD, Fernández DC, Godoy MC, Moreno JAÁ, González JFG. A Review on Digital Twins and Its Application in the Modeling of Photovoltaic Installations. Energies. 2024; 17(5):1227. https://doi.org/10.3390/en1705122
  5. M. Georgiev, A. Georgieva and K. Milanov, "Optimal Demand Response of Smart Buildings with Utilization of Renewable Energy Sources," 2022 14th Electrical Engineering Faculty Conference (BulEF), Varna, Bulgaria, 2022, pp. 1-5, doi: 10.1109/BulEF56479.2022.10021175
  6. M. Nasrin,A. Chakrabarty,M. C. Barman, Sunrise And Sunset Time Prediction In a Specific Latitude, IOSR Journal of Mathematics (IOSR-JM)e-ISSN: 2278-5728, p-ISSN: 2319-765X. Volume 13, Issue 6 Ver. III (Nov. - Dec. 2017), PP 01-07www.iosrjournals.org

Issue

2024 16th Electrical Engineering Faculty Conference, BulEF 2024, 2024, , https://doi.org/10.1109/BULEF63204.2024.10794907

Copyright IEEE

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus