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A Study of Predictive Control Strategies for Optimally Designed Solar Homesud

机译:优化设计的太阳能房屋的预测控制策略研究 ud

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摘要

This thesis investigates the development of predictive control strategies for optimally or near-optimally designed solar homes. Optimal design refers to the integration of renewable energy technologies (mainly active and passive solar) with a high-quality building envelope as well as efficiency and conservation measures to achieve substantial reductions in energy consumption and peak demand. Effective implementation of these technologies requires an integrated design approach, which considers their interactions with the building and its services. Furthermore, control strategies must be an essential part of the integrated design of a building to improve energy performance and ensure occupant comfort. In optimally designed solar homes, control strategies should incorporate the collection, storage and delivery of solar energy. Weather forecasts along with an understanding of the building’s thermal dynamics (e.g., time delays due to thermal mass) enable predicting and managing loads and solar energy availability.ududDesign and operation strategies of a case study, the Alstonvale House, are presented. Features of this house include passive solar design, a building-integrated photovoltaic/thermal (BIPV/T) system coupled with a solar-assisted heat pump, a thermal energy storage tank and a radiant floor heating system in a thermally massive concrete slab. Design and control approaches developed for the Alstonvale House provided the basis for generalized control strategies applicable to optimally designed solar homes.ud udSimplified building models, which can be derived from more detailed models or on-site measurements, can facilitate the implementation of predictive control techniques. In this investigation, model-based predictive control was applied to a radiant floor heating system and the position of roller blinds in a room with high solar gains. ududPredictive control can also be applied to optimize the operation of renewable energy systems. In this study, forecasts of heating loads and solar radiation were used in a dynamic programming algorithm to select a near-optimal set-point trajectory for an energy storage tank heated with a heat pump assisted by a BIPV/T system. ud
机译:本文研究了针对最优或接近最优设计的太阳能房屋的预测控制策略的发展。最佳设计是指将可再生能源技术(主要是主动式和被动式太阳能)与高质量的建筑围护结构以及效率和节约措施相结合,以实现能源消耗和峰值需求的大幅减少。有效实施这些技术需要采用集成设计方法,该方法应考虑它们与建筑物及其服务之间的相互作用。此外,控制策略必须是建筑物集成设计的重要组成部分,以提高能源效率并确保居住者的舒适度。在设计最佳的太阳能房屋中,控制策略应包括太阳能的收集,存储和输送。天气预报以及对建筑物热动力学的理解(例如,由于热质量导致的时间延迟)可以预测和管理负载以及太阳能的可用性。 ud ud提供了案例研究Alstonvale House的设计和操作策略。这栋房屋的特色包括被动式太阳能设计,与太阳能辅助热泵相结合的建筑物集成光伏/热能(BIPV / T)系统,热能储罐和热成块混凝土板中的辐射地板采暖系统。为Alstonvale House开发的设计和控制方法为适用于最佳设计的太阳能房屋的通用控制策略提供了基础。 ud ud简化的建筑模型可以从更详细的模型或现场测量中得出,可以促进实施预测性建筑控制技术。在这项研究中,将基于模型的预测控制应用于辐射式地板采暖系统,以及将百叶窗的位置安装在具有较高日照增益的房间中。 ud ud预测性控制还可用于优化可再生能源系统的运行。在这项研究中,在动态编程算法中使用了对热负荷和太阳辐射的预测,以为由BIPV / T系统辅助的热泵加热的储能罐选择接近最佳的设定点轨迹。 ud

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