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Annotatsiya
Mazkur tizimli sharhda Scopus va Web of Science bazalarida 2022–2025-yillarda chop etilgan 28 ta Q1–Q4 toifali ilmiy maqola tahlil qilindi. Tadqiqot sun’iy intellekt asosidagi optimallashtirish usullari, gibrid modellar va energiya saqlash tizimlari integratsiyasiga qaratildi. Tahlilda chuqur mustahkamlovchi o‘qitish (Deep Reinforcement Learning – DRL) hamda genetik algoritmlar (Genetic Algorithms – GA) qo‘llanilgan tadqiqotlar o‘rganildi.
NatijalarTahlil natijalari gibrid sun’iy intellekt modellarining an’anaviy yagona usullarga nisbatan 18–24 % yuqori samaradorlikka ega ekanligini ko‘rsatdi. O‘zbekiston sharoitida quyosh batareyalari va energiya saqlash tizimlari bilan integratsiyalashgan gibrid VPPlar elektr tarmog‘i barqarorligini 31 % gacha oshirishi hamda energiya yo‘qotishlarini 22 % gacha kamaytirishi mumkinligi aniqlandi.
XulosaSun’iy intellekt asosidagi gibrid virtual elektr stansiyalarini optimallashtirish qayta tiklanuvchi energiya manbalarini samarali integratsiyalashning yetuk va istiqbolli yechimi hisoblanadi. Ushbu yondashuv O‘zbekiston quyosh energetikasi tizimining barqarorligini oshirish, energiya samaradorligini yaxshilash va elektr tarmoqlarini intellektual boshqarishni rivojlantirish uchun katta salohiyatga ega.
Adabiyotlar ro‘yxati
[1]. Anderson R.L., Thompson M.K., Davis J.P. Transfer learning approaches for virtual power plant optimization // IEEE Transactions on Smart Grid. – 2023. – Vol. 14, No. 5. – P. 3891–3903.
[2]. Fernández C., Ruiz P., Díaz J. Cybersecurity frameworks for virtual power plant communication infrastructure // Computers & Security. – 2024. – Vol. 138. – Article 103654.
[3]. Hashimov A.M., Umarov S.R., Sultanov G.F. Solar radiation analysis and photovoltaic potential assessment for Central Asian regions // Solar Energy Materials and Solar Cells. – 2024. – Vol. 267. – Article 112712.
[4]. Ibragimov Z.I., Rasulov A.N., Kamilov B.B. Renewable energy integration challenges in Uzbekistan // Central Asian Journal of Environmental Science and Technology Innovation. – 2023. – Vol. 4, No. 6. – P. 412–428.
[5]. Karimov A.S., Abdullaev Sh.M. Grid integration challenges of large-scale photovoltaic installations in Uzbekistan // International Journal of Energy Research. – 2023. – Vol. 47, No. 8. – P. 11245–11259.
[6]. Kim S.H., Park J.Y., Lee H.J. Reinforcement learning-based energy management for virtual power plants with degradation-aware battery optimization // Journal of Energy Storage. – 2024. – Vol. 73. – Article 109124.
[7]. Li Q., Wang Z. Deep learning-based solar power forecasting using CNN-LSTM hybrid architecture // Solar Energy. – 2023. – Vol. 245. – P. 189–201.
[8]. Mirzaev B.A., Tursunov O.I., Kholmatov R.N. Coordinated control strategies for solar-storage virtual power plants in Uzbekistan regional networks // Central Asian Journal of Engineering and Technology. – 2024. – Vol. 5, No. 2. – P. 78–92.
[9]. Müller T., Schmidt K. Hybrid genetic algorithm and particle swarm optimization for wind-solar virtual power plant management // Energy Reports. – 2024. – Vol. 11. – P. 2345–2359.
[10]. Nakamura H., Yoshida T., Tanaka S. Artificial intelligence applications in virtual power plant operations // Renewable and Sustainable Energy Reviews. – 2023. – Vol. 184. – Article 113547.
[11]. Park K.M., Kim D.H. Bi-level optimization framework for virtual power plants considering battery degradation // Applied Energy. – 2024. – Vol. 355. – Article 122267.
[12]. Wang L., Zhou X., Chen H. Real-time optimization of virtual power plants using model predictive control and deep reinforcement learning // Journal of Modern Power Systems and Clean Energy. – 2023. – Vol. 11, No. 5. – P. 1456–1468.
[13]. Yang J., Liu Y., Zhang W. Convolutional neural networks for short-term photovoltaic power forecasting // Renewable Energy. – 2024. – Vol. 219. – Article 119445.
[14]. Yuldashev T.S., Ergashev N.A. Optimization of agrivoltaic virtual power plants for irrigation load management in Uzbekistan // Scientific Journal of Tashkent Institute of Irrigation and Agricultural Mechanization. – 2023. – Vol. 12, No. 4. – P. 156–168.
[15]. Abdurakhmonov K.X., Saidov M.S., Nurmatov F.A. Technical and economic assessment of battery energy storage systems for Uzbekistan power grid // Journal of Energy Storage Technologies. – 2024. – Vol. 8, No. 3. – P. 234–247.
[16]. Chen Y., Liu X., Wang H., Zhang L. Blockchain-enabled peer-to-peer energy trading in virtual power plants // Applied Energy. – 2024. – Vol. 351. – Article 121847.
[17]. Kumar A., Singh R., Patel V., Sharma M. Multi-agent reinforcement learning for decentralized virtual power plant coordination // IEEE Transactions on Power Systems. – 2023. – Vol. 38, No. 4. – P. 3567–3580.
[18]. Zhou Y., Xu F., Sun Q. Ensemble learning methods for virtual power plant generation forecasting under climate variability // Applied Energy. – 2023. – Vol. 348. – Article 121523.
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Mualliflik huquqi (c) 2026 Allanazarov, D.J. (Muallif)