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Energy flexible building through smart demand-side management and latent heat storage

机译:通过智能需求侧管理和潜热存储实现能源灵活的建筑

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One of the greatest challenges for long-term emissions reduction is the decarbonisation of heating and cooling due to the large scale, seasonal variation and distributed nature. Energy flexible buildings with electric heating, smart demand-side management and efficient thermal energy storage are one of the most promising strategies to deploy low-carbon technologies which can benefit the electricity system by reducing the need of reinforcing existing networks and their ability to use electricity in times of low demand and high supply. Combined with spot price contracts, in which the electricity tariff changes every half-hour depending on supply and demand, they can effectively reduce on-peak demand periods, achieve economic profits for end-users and retailers, and reduce the environmental impact of the electricity grid by operating in periods with lower CO2 emissions rate. To achieve these benefits, it is crucial to develop accurate models for energy flexible buildings as well as control strategies to optimise the complex system operation. This paper proposes a novel flexible energy building concept, based on smart control, high density latent heat storage and smart grids, able to predict the best operational strategy according to the environmental conditions, economic rates and expected occupancy patterns. The smart integration model, carried out in TRNSYS for a Scottish case study, solves a multi-criteria assessment based on future energy demand prediction (learning machine model supported by end-user's predefined occupancy by Internet of Things, present and forecast weather data, and building load monitoring), electricity tariff evolution and building performance. The results show that end-user's electricity bill savings of 20% are obtained and retailer's associated electricity cost is reduced by 25%. In addition, despite an increase in final energy consumption of up to 8%, the environmental impact remains constant due to operation at times with lower CO2 emissions rate in electricity generation. The developed tools enable the design of smart energy systems for energy flexible buildings which can have a large positive impact on the building sector decarbonisation.
机译:长期减排的最大挑战之一是由于规模大,季节变化和分布性而导致的供热和制冷的脱碳。具有电加热,智能需求侧管理和高效热能存储的能源灵活型建筑物是部署低碳技术的最有前途的策略之一,这些低碳技术可通过减少加强现有网络的需求及其用电能力来使电力系统受益在需求低迷和供应高涨的时期。结合现货价格合同(电价每半小时根据供需变化),它们可以有效地减少高峰需求期,为最终用户和零售商获得经济利润,并减少电力对环境的影响通过在二氧化碳排放量较低的时期内运行来实现电网。为了获得这些好处,至关重要的是为能源柔性建筑开发精确的模型以及控制策略以优化复杂的系统操作。本文提出了一种基于智能控制,高密度潜热存储和智能电网的新型柔性能源建筑概念,能够根据环境条件,经济水平和预期的占用模式预测最佳的运营策略。在TRNSYS中针对苏格兰的案例研究进行了智能集成,该模型基于未来的能源需求预测解决了多标准评估(学习机模型由最终用户通过物联网预先定义的占用量支持,可以显示和预测天气数据,以及建筑负荷监测),电价演变和建筑性能。结果表明,最终用户可节省20%的电费,而零售商的相关电费降低了25%。此外,尽管最终能耗增加了8%,但由于有时发电时的CO2排放率较低,因此对环境的影响保持恒定。所开发的工具可以设计用于灵活能源建筑的智能能源系统,这可以对建筑行业的脱碳产生巨大的积极影响。

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