دانلود و نمایش مقالات مرتبط با اینترنت 5G انرژی::صفحه 1
بلافاصله پس از پرداخت دانلود کنید

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

نتیجه جستجو - اینترنت 5G انرژی

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Deep reinforcement learning and LSTM for optimal renewable energy accommodation in 5G internet of energy with bad data tolerant
یادگیری تقویتی عمیق و LSTM برای استفاده بهینه از انرژی تجدیدپذیر در اینترنت 5G انرژی با تحمل داده های بد-2020
With the high penetration of large scale distributed renewable energy generations, there is a serious curtailment of wind and solar energy in 5G internet of energy. A reasonable assessment of large scale renewable energy grid-connected capacities under random scenarios is critical to promote the efficient utilization of renewable energy and improve the stability of power systems. To assure the authenticity of the data collected by the terminals and describe data characteristics precisely are crucial problems in assessing the accommodation capability of renewable energy. To solve these problems, in this paper, we propose an L-DRL algorithm based on deep reinforcement learning (DRL) to maximize renewable energy accommodation in 5G internet of energy. LSTM as a bad data tolerant mechanism provides real state value for the solution of accommodation strategy, which ensures the accurate assessment of renewable energy accommodation capacity. DDPG is used to obtain optimal renewable energy accommodation strategies in different scenarios. In the numerical results, based on real meteorological data, we validate the performance of the proposed algorithm. Results show considering the energy storage system and demand response mechanism can improve the capacity of renewable energy accommodation in 5G internet of energy.
Keywords: 5G internet of energy | Renewable energy accommodation | Deep reinforcement learning | Demand response | LSTM
مقاله انگلیسی
2 Edge intelligence based Economic Dispatch for Virtual Power Plant in 5G Internet of Energy
هوش لبه مبتنی بر اجرای اقتصادی برای نیروگاه مجازی در اینترنت 5G انرژی-2020
Nowadays, with a large of complicated geography of Distributed Energy Sources (DES), how to integrate distributed renewable energy source and reduce the operational costs by Virtual Power Plant (VPP) becomes a mainstream problem in Internet of energy. The traditional method of energy integration and operational cost optimization utilizes the cloud computing technology to centralized control the computational task, which increases the burden of computing. According with the development of information communication technology, such as Internet of Things and 5G, edge computing technology is an effective way to offload computational task to the edge side of 5G networks. Moreover, with the increase of collected data, it becomes a key point to effectively improve the computing power of edge nodes in edge computing. Currently, machine learning is an effective way to process the big data. Based this situation, it leads the combination of machine learning and edge computing. In this paper, the Edge Intelligence (EI) structure is proposed to solve the Economic Dispatch Problem (EDP) in VPP of Internet of Energy. Compared with the traditional edge computing, the proposed EI structure inherits its original features which reduce the burden of cloud computing, and also the proposed EI structure improves the computational power of edge computing. Through the splitting model and deploying the particle model in the terminal, it is facility to real-time control and take the less costs of VPP. Due to the transmission between the splitting models with counterpart, it transmits the part information and gradient information, which effectively reduces the consumption of communication. The proposed method has verified the effectiveness and feasibility through the numerical experiments of real application data sets.
Keywords: Virtual Power Plant | Machine leaning | Edge intelligence | Economic Dispatch
مقاله انگلیسی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 5412 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 5412 :::::::: افراد آنلاین: 53