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Evaluation of energy saving potential using Stochastic Model Predictive Control for stand alone Air Conditioning units a study in Indian scenario

机译:独立模型空调单元的随机模型预测控制对节能潜力的评估在印度的研究

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Reduction in energy consumption has become imperative in the modern day. The building segment is responsible for almost 40% consumption. These installations are typically located at the distribution level. There are losses associated with the transmission system, such as T&D Losses and pilferage losses. Hence a single unit of energy saved at distribution level would amount to greater savings at the generation level. Developing nations rely largely on standalone Air Conditioning units for office and domestic use since these facilities rarely designed to accommodate centralized Heating ventilation and Air Conditioning (HVAC) systems. In this paper a novel approach to control all these air conditioning units using a centralized controller based on Stochastic Model Predictive Control (SMPC) has been presented. The SMPC takes into account the predicted weather to reduce energy consumption while maintaining the comfort level of the occupants. A sample office space has been modeled and performance of the algorithm has been studied for weather conditions of large cities of India. With centralized SMPC the system has significantly outperformed the existing SAC with localized controller.
机译:在现代,减少能耗已成为当务之急。建筑部门将消耗近40%的能源。这些安装通常位于分发级别。存在与传输系统相关的损失,例如输配电损失和盗窃损失。因此,在配电级别节省的单个单位的能量将相当于在发电级别节省的更多能量。发展中国家主要依赖于办公室和家庭使用的独立空调设备,因为这些设备很少设计用于容纳集中供暖通风和空调(HVAC)系统。在本文中,提出了一种基于随机模型预测控制(SMPC)的使用集中控制器控制所有这些空调单元的新颖方法。 SMPC将预测的天气考虑在内,以减少能耗,同时保持乘员的舒适度。已对一个示例办公空间进行了建模,并针对印度大城市的天气状况研究了该算法的性能。使用集中式SMPC,该系统的性能大大优于具有本地化控制器的现有SAC。

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