DEVELOPMENT OF METHODS FOR SELECTING THE OPTIMAL COMPOSITION OF EQUIPMENT IN POWER PLANTS OPERATING WITH RENEWABLE ENERGY RESOURCES

Abstract

In modern conditions of intensive increasing the electricity consumption in all spheres
of human activity, limited hydrocarbon fuel reserves, as well as the severity of environmental
problems in the energy sector require the development and implementation of more effective methods
for the construction and operation of power plants in basis of renewable energy resources, primarily
solar and wind energy. The design of autonomous hybrid systems with stations using such energy
resources involves, in particular, the selection of the optimal composition of the main equipment.
Despite the current existence of a number of developments to solve this problem, the issues of
improving them by taking into account all limiting and influencing factors, increasing the accuracy
of optimization, remains an urgent task. This paper proposes an effective mathematical model and
algorithm for selecting the optimal composition of units in autonomous hybrid systems containing
solar and wind stations, as well as batteries, taking into account all factors. The proposed algorithm
involves solving the problem by reducing it to a linear programming problem and using the simplex
method. The results of a study of the effectiveness of the proposed model and optimization algorithm
are presented. Based on the results of the calculation experiments performed, it was revealed that the
proposed model and algorithm for optimizing the composition of equipment in an autonomous hybrid
system has good computational quality and high calculation accuracy.

Keywords

Keywords are not provided.

References

1. Wang, Zekun & Jia, Yan & Yang, Yingjian & Cai, Chang & Chen, Yinpeng. (2021). Optimal
2. Configuration of an Off-Grid Hybrid Wind-Hydrogen Enery System: Comparison of Two
3. Systems. Energy Engineering., 1641-1658.
4. SUN Qiana, MA Jianweia, SHE Yanjieb, ZHANG Jingchaoc, GU Bod, ZHANG Zichaoe.
5. (2019). Optimal Configuration of Standalone Wind–Solar–Storage Complementary
6. Generation. Journal of Power Technologies 99 (4) , 231-236.
7. Zhang, Junli & Wei, Huashuai. (2022, August 24). A review on configuration optimization of
8. hybrid energy system based on renewable energy. Frontiers in Energy Research, pp. 01-15.
9. Lanre Olatomiwa. (2016). Optimal configuration assessments of hybrid renewable power
10. supply for rural healthcare facilities. Energy Reports, 141-146.
11. Mas’ud, A.A.; Al-Garni, H.Z. (2021). Optimum Configuration of a Renewable Energy System
12. Using Multi-Year Parameters and Advanced Battery Storage Modules: A Case Study in
13. Northern Saudi Arabia. Sustainability, 13, 5123.
14. Freire-Gormaly, M, & Bilton, A,M. (2015, Avgust 2-5). Optimization of Renewable Energy
15. Power Systems for Remote Communities. Proceedings of the ASME 2015 International Design
16. Engineering Technical Conferences & Computers and Information in Engineering Conference
17. IDETC/CIE 2015 Boston, Massachusetts, USA, p. 11.
18. Farzad Ghayoor, Andrew G. Swanson, Hudson Sibanda. (2021). Optimal sizing for a gridconnected
19. hybrid renewable energy system: A case study of the residential sector in Durban,
20. South Africa. Journal of Energy in Southern Africa 32(4):, 11-27.
21. Tristar. (2014). TriStar MPPT Maximum Power Point Tracker.
22. TRISTAR MPPT 600V. (2022). Solar Battery Charger with TrakStarTM Maximum Power
23. Point Tracking Technology.
24. TriStar MPPT 600V TM with Off-grid / Grid-tie Transfer Switch. (2017). “Solar Battery
25. Charger with TrakStarTM Maximum Power Point Tracking Technology.
26. Christoph Kost, Shivenes Shammugam, Verena Fluri, Dominik Peper, Aschkhan Davoodi
27. Memar, Thomas Schelegl. (2021). Levelized Cost of Electricity Renewable Energy
28. Technologies. Germaniya.
29. Christoph Kost, Shivenes Shammugam, Verena Julch, Huyen-Tran Nguyen, Thomas Schelegl.
30. (2018). Levelized Cost of Electricity Renewable Energy Technologies. Germaniya.
31. J. White, K. Case, and D. Pratt. (2010). Principles of Engineering Economic Analysis.
32. Hoboken, NJ: Wiley Higher Education.
33. Lagerveld S., Röckmann C., & Scholl M. (2014). A study on the combination of offshore wind
34. energy with offshore aquaculture. IMARES Report C056/14. Retrieved August 2, 2016, from
35. http://edepot.wur.nl/318329.
36. Felipe Sabadini, Reinhard Madlener. (2021). The economic potential of grid defection of
37. energy prosumer households in Germany. Anvances in Applied Energy.
38. Гайибов Т. (2020). Выбор оптимальных параметров солнечных фотоэлектрических
39. станций и аккумуляторов в распределительных электрических сетях. Тенденции
40. развития современной физики полупроводников: проблемы, достижения и перспективы
41. (pp. 237-242). 2020: НИИ Физика полупроводников и микроэлектроники при
42. Национальном университете Узбекистан.
43. Gayibov T.Sh., Fayziyev M.M., Toshev T.U. (2022). Tarkibida qayta tiklanuvchan energiya
44. manbalarida ishlovchi elektr stansiyalari mavjud bo‘lgan elektr energetika tizimlarining
45. rejimlarini optimallash. Инновацион технологиялар, 26-29.
46. T.Sh. Gayibov, T.U. Toshev. (2023). Аvtonom quyosh fotoelektr tizimlarining tarkibini
47. optimallashtirish. Energiya va resurs tejash muammolari, 292-298 b.
48. Gayibov T.Sh., Toshev T.U. (2023). Quyosh Fotoelektr stansiyalari elementlarning optimal
49. tarkibini tanlash masalasining matematik model va uni yechish algortimi. Инновацион
50. технологиялар, 13-21.
51. Toshev T.U., Tuxtayev B.B. (2023). Quyosh Fotoelektr tizimlarini elektr ta’minoti tarmog‘iga
52. ulanish holati. Kelajak samarali energetikasi: muammolar va echimlar (pp. 351-354). Farg‘ona:
53. Farg‘ona politexnika instituti.