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SUN’IY INTELLEKT ASOSIDA QUYOSH VIRTUAL ELEKTR STANSIYALARINI OPTIMALLASHTIRISH: TIZIMLI SHARH

Fan yo'nalishi:Energiya (turli xil)Qayta tiklanadigan energiya, barqarorlik va atrof -muhit
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2. АЭ_1_2026_01(22)_14-....pdf

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MAQOLA ANNOTATSIYASI

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Annotatsiya. Kirish. Virtual elektr stansiyalari (VPP) tarqatilgan qayta tiklanadigan energiya manbalarini samarali integratsiya qilish imkonini beradi. O‘zbekistonda quyosh energetikasi rivojlanayotgan sharoitda VPP texnologiyalari tarmoq barqarorligini ta’minlaydi. Materiallar va usullar. Tizimli adabiyotlarni ko‘rib chiqish 2022–2025 yillarda Scopus va Web of Science bazalarida chop etilgan 28 ta Q1–Q4 maqolani o‘z ichiga oladi. Tadqiqotda sun’iy intellekt asosida optimallashtirish, gibrid modellar va energiya saqlash tizimlari tahlil qilindi. Asosiy texnikalar: Deep Reinforcement Learning (DRL) va Genetic Algorithms (GA). Natijalar. Gibrid AI modellari yagona usullarga nisbatan 18–24% yuqori samaradorlikni ko‘rsatadi. O‘zbekistonda quyosh–akkumulyator gibrid VPP tizimlari tarmoq barqarorligini 31% gacha oshirishi va energiya yo‘qotishlarini 22% gacha kamaytirishi mumkin. Xulosa. Sun’iy intellektga asoslangan gibrid VPP optimallashtirish qayta tiklanadigan energiyani integratsiya qilishda samarali va rivojlangan yondashuv hisoblanadi, O‘zbekiston quyosh energetikasi uchun katta imkoniyat yaratadi.

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Science ID: MTN-0225-0183

Teglar

# storage# learning# virtual# optimization# intelligence# power# machine# energy# hybrid# plants# artificial# solar

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