The article reviews current research and developments in the field of energymanagement and storage in the context of photovoltaic (PV) systems. The focus is on energy storagemethods, such as electrical and thermal systems, and methods for managing reactive power, voltage,and frequency in networks with a high share of solar generation. The review emphasizes the need forefficient and cost-effective energy storage systems and intelligent demand management for the fullintegration of PV systems into the grid and ensuring its stability.The methods include the analysis of energy storage systems, investigation of reactive powerand frequency management, use of machine learning for power prediction and optimization of energysystem management, as well as modeling in MATLAB/Simulink. The materials consist of weathercondition data, experimental results from solar PV power plants, and technical literature on energymanagement and storage.The results include an analysis of approaches to energy storage, the development of activepower control (APC) strategies for frequency stabilization in networks with PV generation, machinelearning-based power prediction methods, an assessment of storage and management systems forimproving PV system integration, and a demonstration of improved power system prediction andoptimization through intelligent management methods.Energy management and storage are key to the successful integration of photovoltaic systemsinto power grids. The development of efficient energy storage systems and intelligent managementmethods helps to smooth the variability of solar generation and ensure grid stability
| Mualliflar | Komilov, Asliddin, Asanova, Sayyora |
|---|---|
| Jurnal | Инновацион технологиялар |
| Nashriyot | Қарши муҳандислик-иқтисодиёт институти |
| ISSN | 2181-4732, 2181-4015 |
| Nashr sanasi | 2024-12-26 |
| Jild | 54 |
| Son | 02 |
| Til | Ingliz |
| Indeksga qo‘shilgan | 2026-08-26 |
photovoltaic systems (PV), machine learning, grid stability, reactive power, energy storage, power prediction., фотоэлектрические системы (PV), машинное обучение, стабильность сети, реактивная мощность, хранение энергии, прогнозирование мощности., fotoelektrik tizimlar (PV), mashinani oʻrganish, tarmoq barqarorligi, reaktiv quvvat, energiyani saqlash, quvvatni prognozlash.
| APA | Komilov, Asliddin, & Asanova, Sayyora (2024). ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS. Инновацион технологиялар, 54(02). https://ojs.qmii.uz/index.php/it/article/view/895 |
|---|---|
| GOST (OAK) | Komilov, Asliddin, Asanova, Sayyora ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS // Инновацион технологиялар. – 2024. – T. 54, № 02. |
| MLA | Komilov, Asliddin, and Asanova, Sayyora. “ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS.” Инновацион технологиялар, 54(02), 2024. https://ojs.qmii.uz/index.php/it/article/view/895 |
| Chicago | Komilov, Asliddin, and Asanova, Sayyora. “ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS.” Инновацион технологиялар, 54(02) (2024). https://ojs.qmii.uz/index.php/it/article/view/895 |
| Harvard | Komilov, Asliddin, and Asanova, Sayyora (2024) ‘ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS’, Инновацион технологиялар, 54(02). https://ojs.qmii.uz/index.php/it/article/view/895 |
| BibTeX | @article{komilovasliddin2024,
title = {ENERGY MANAGEMENT AND STORAGE IN PHOTOVOLTAIC SYSTEMS: A REVIEW OF CURRENT RESEARCH AND DEVELOPMENTS},
author = {Komilov, Asliddin and Asanova, Sayyora},
journal = {Инновацион технологиялар},
year = {2024},
volume = {54},
number = {02},
url = {https://ojs.qmii.uz/index.php/it/article/view/895}
} |
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