دانلود مقاله انگلیسی رایگان:مدیریت انرژی میکروگیدر چند عامل مبتنی بر پیشگویی یادگیری عمیق - 2019
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  • Multi-agent microgrid energy management based on deep learning forecaster Multi-agent microgrid energy management based on deep learning forecaster
    Multi-agent microgrid energy management based on deep learning forecaster

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    Multi-agent microgrid energy management based on deep learning forecaster


    ترجمه فارسی عنوان مقاله:

    مدیریت انرژی میکروگیدر چند عامل مبتنی بر پیشگویی یادگیری عمیق


    منبع:

    Sciencedirect - Elsevier - Energy, 186 (2019) 115873: doi:10:1016/j:energy:2019:115873


    نویسنده:

    Mousa Afrasiabi a, Mohammad Mohammadi a, *, Mohammad Rastegar a, Amin Kargarian b


    چکیده انگلیسی:

    This paper presents a multi-agent day-ahead microgrid energy management framework. The objective is to minimize energy loss and operation cost of agents, including conventional distributed generators, wind turbines, photovoltaics, demands, battery storage systems, and microgrids aggregator agent. To forecast market prices, wind generation, solar generation, and load demand, a deep learning-based approach is designed based on a combination of convolutional neural networks and gated recurrent unit. Each agent utilizes the designed learning approach and its own historical data to forecast its required parameters/data for scheduling purposes. To preserve the information privacy of agents, the alternating direction method of multipliers (ADMM) is utilized to find the optimal operating point of microgrid distributedly. To enhance the convergence performance of the distributed algorithm, an accelerated ADMM is presented based on the concept of over-relaxation. In the proposed framework, the agents do not need to share with other parties either their historical data for forecasting purposes or commercially sensitive information for scheduling purposes. The proposed framework is tested on a realistic test system. The forecast values obtained by the proposed forecasting method are compared with several other methods and the accelerated distributed algorithm is compared with the standard ADMM and analytical target cascading.
    Keywords: Microgrid energy management system | Short-term forecasting | Deep learning | Convolutional neural networks | Gated recurrent unit | Alternating direction method of multipliers


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 14
    حجم فایل: 1625 کیلوبایت

    قیمت: رایگان


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