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Distributed Real-Time HVAC Control for Cost-Efficient Commercial Buildings under Smart Grid Environment

机译:分布式实时暖通空调控制成本效益商业银行   智能电网环境下的建筑物

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摘要

In this paper, we investigate the problem of minimizing the long-term totalcost (i.e., the sum of energy cost and thermal discomfort cost) associated witha Heating, Ventilation, and Air Conditioning (HVAC) system of a multizonecommercial building under smart grid environment. To be specific, we firstformulate a stochastic program to minimize the time average expected total costwith the consideration of uncertainties in electricity price, outdoortemperature, the most comfortable temperature level, and external thermaldisturbance. Due to the existence of temporally and spatially coupledconstraints as well as unknown information about the future system parameters,it is very challenging to solve the formulated problem. To this end, we proposea realtime HVAC control algorithm based on the framework of Lyapunovoptimization techniques without the need to predict any system parameters andknow their stochastic information. The key idea of the proposed algorithm is toconstruct and stabilize virtual queues associated with indoor temperatures ofall zones. Moreover, we provide a distributed implementation of the proposedrealtime algorithm with the aim of protecting user privacy and enhancingalgorithmic scalability. Extensive simulation results based on real-worldtraces show that the proposed algorithm could reduce energy cost effectivelywith small sacrifice in thermal comfort.
机译:在本文中,我们研究了在智能电网环境下与多区域商业建筑的供暖,通风和空调(HVAC)系统相关的长期总成本(即能源成本和热不适成本之和)最小化的问题。具体而言,我们首先制定一个随机程序,以考虑电价,室外温度,最舒适的温度水平和外部热扰动的不确定性,以最大程度地降低平均预期平均时间成本。由于存在时间和空间耦合约束以及关于未来系统参数的未知信息,解决所提出的问题非常具有挑战性。为此,我们提出了一种基于李雅普诺夫优化技术框架的实时HVAC控制算法,而无需预测任何系统参数并了解其随机信息。该算法的关键思想是构造和稳定与所有区域的室内温度相关的虚拟队列。此外,我们提供了所提出的实时算法的分布式实现,目的是保护用户隐私并增强算法可扩展性。基于真实世界轨迹的大量仿真结果表明,该算法可以有效地降低能源成本,而在热舒适性方面的牺牲很小。

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