Artificial Neural Network Approach for the Integration of Renewable Energy in Telecommunication Systems

K. A. Dotche, Adekunlé Akim Salami, K. M. Kodjo, F. Sekyere, K. Bedja
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引用次数: 2

Abstract

The integration of the renewable energy into the electric power grid is important to sustain the economic development, particularly for many African nations. Therefore, these countries could also equip their airport’s electrical system with advanced artificial intelligence technology in manner to harvest the renewable energy. The paper seeks to propose a real time power management algorithm for a distributive hybrid renewable energy grid. It proceeds on the network modelling with the integration of the photovoltaic and wind energy. A multi objective formulation is proposed for the maximization of the area spectral efficiency and the energy efficiency as function of the number of wind aero-generators and photovoltaic solar panels. Radio parameters for a Mobile Wireless inter-operability Medium Access (WiMAX) technology are considered for the simulation in Matlab software. The obtained results are much mitigated but theoretically encouraging for the integration of the green energy integration into the modern telecommunication systems.
电信系统中可再生能源集成的人工神经网络方法
将可再生能源纳入电网对维持经济发展具有重要意义,特别是对许多非洲国家而言。因此,这些国家也可以为机场的电力系统配备先进的人工智能技术,以收获可再生能源。提出了一种分布式混合可再生能源电网的实时电源管理算法。并结合光伏和风能进行了网络建模。提出了区域频谱效率和能量效率随风力发电机组和光伏太阳能板数量的函数最大化的多目标公式。考虑了移动无线互操作介质接入(WiMAX)技术的无线电参数,并在Matlab软件中进行了仿真。所得结果对绿色能源集成到现代通信系统中有一定的借鉴意义。
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