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نتیجه جستجو - مدیریت انرژی میکروگرید

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 Multi-agent microgrid energy management based on deep learning forecaster
مدیریت انرژی میکروگیدر چند عامل مبتنی بر پیشگویی یادگیری عمیق-2019
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
مقاله انگلیسی
2 Game-theoretical Energy Management for Energy Internet with Big Data-based Renewable Power Forecasting
مدیریت انرژی بازی تئوری برای اینترنت انرژی با پیش بینی قدرت قابل بازیافت مبتنی بر داده های بزرگ-2017
Energy internet, as a major trend in power system, can provide an open framework for integrating equipments of energy generation, transmission, storage and consumption, etc., so that global energy can be managed and controlled efficiently by information and communication technologies. In this paper, we focus on the coordinated management of renewable and traditional energy, which is a typical issue on energy connections. We consider a conventional power system consisting of the utility company, the energy storage company, the microgrid, and electricity users. Firstly, we formulate the energy management problem as a three-stage Stackelberg game, and every player in the electricity market aims to maximize its individual payoff while guaranteeing the system reliability and satisfying users’ electricity demands. We employ the backward induction method to solve the three-stage non-cooperative game problem, and give the closed-form expressions of the optimal strategies for each stage. Next, we study the big data-based power generation forecasting techniques, and introduce a scheme of the wind power forecasting, which can assist the microgrid to make strategies. Furthermore, we prove the properties of the proposed energy management algorithm including the existence and uniqueness of Nash equilibrium and Stackelberg equilibrium. Simulation results show that accurate prediction results of wind power is conducive to better energy management.
Index Terms: energy internet | Stackelberg game | microgrid energy management | wind power forecasting.
مقاله انگلیسی
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