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Optimal Control Strategy For A Multi-zone Air Conditioning System Using A Genetic Algorithm

机译:基于遗传算法的多区域空调系统最优控制策略

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摘要

This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme/model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005]. Energy savings up to 30.4% were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied.
机译:本文研究了变风量空调系统的最优控制策略。控制策略包括固定温度设定点的基本控制策略和确保舒适度和室内空气质量(IAQ)的两种高级策略。第一个高级控制可调节新鲜空气的供应速率和供应的空气温度,以在确保室内空气质量的同时保持每个区域的温度设定点。第二种策略控制新鲜空气速率和送风温度,以在每个区域保持可接受的热舒适度和IAQ。每种控制策略的优化问题都是基于能耗成本制定的,并受系统和热空间瞬态模型的约束。使用遗传算法解决了优化问题。该优化方案/模型被应用于贝鲁特天气下的建筑案例研究。使用Visual DOE 4.0软件[建筑能源合作公司,美国旧金山;热能空间和系统组件模型]对基本策略进行了验证。 2005]。与传统的基本策略相比,优化的高级策略在满足舒适性和室内空气质量的同时,在四个月的夏季中,节能高达30.4%。

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