This paper investigates the potential benefits of integrating rooftop greenhouses (RTGs) with buildings to reduce energy and CO costs, contributing to urban decarbonization efforts. This integration not only advances sustainable urban agriculture but also aligns with the United Nations Sustainable Development Goal 7 (SDG7) - Affordable and Clean Energy, and Sustainable Development Goal 11 (SDG11) - Sustainable Cities and Communities, through its energy-efficient, low-carbon approach. We hypothesize that this integration can significantly lower energy use in integrated RTGs (i-RTGs) and set out to validate this through dynamic models for both building and i-RTG climates, focusing on CO concentration, humidity, and temperature. Central to our approach is the implementation of a nonlinear model predictive control (NMPC) framework, which utilizes these dynamic models to make control decisions aimed at minimizing total control costs. This framework operates in a receding horizon procedure, regulating climate factors within the i-RTG and building using various actuators. We validate our approach by simulating an i-RTG atop a building in eleven different cities, demonstrating interactions such as energy, moisture, and CO exchange. Significantly, our study reveals that integrating i-RTG with buildings under the NMPC framework leads to a 15.2% reduction in control costs. Additionally, we find that the i-RTG model is adaptable to different climates, with colder regions showing greater cost reduction potential. Our study underscores the viability and advantages of integrating i-RTGs with buildings, offering a sustainable, decarbonizing solution for urban agriculture and building management that contributes to the fulfillment of SDG7 and SDG11.

中文翻译：

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通过智能能源管理实现脱碳：各种气候条件下城市农业建筑一体化屋顶温室的气候控制

本文研究了将屋顶温室 (RTG) 与建筑物集成的潜在好处，以降低能源和二氧化碳成本，从而促进城市脱碳工作。这种一体化不仅促进可持续城市农业，而且通过其节能、低耗能​​的方式，符合联合国可持续发展目标 7 (SDG7) - 负担得起的清洁能源和可持续发展目标 11 (SDG11) - 可持续城市和社区。碳方法。我们假设这种集成可以显着降低集成 RTG (i-RTG) 的能源消耗，并着手通过建筑和 i-RTG 气候的动态模型来验证这一点，重点关注二氧化碳浓度、湿度和温度。我们方法的核心是实施非线性模型预测控制（NMPC）框架，该框架利用这些动态模型做出控制决策，旨在最大限度地降低总控制成本。该框架以地平线后退程序运行，调节 i-RTG 内的气候因素并使用各种执行器进行建筑。我们通过模拟 11 个不同城市的建筑物顶部的 i-RTG 来验证我们的方法，展示能量、湿度和二氧化碳交换等相互作用。值得注意的是，我们的研究表明，在 NMPC 框架下将 i-RTG 与建筑物集成可以使控制成本降低 15.2%。此外，我们发现 i-RTG 模型可以适应不同的气候，较寒冷的地区显示出更大的成本降低潜力。我们的研究强调了将 i-RTG 与建筑物集成的可行性和优势，为城市农业和建筑管理提供可持续的脱碳解决方案，有助于实现 SDG7 和 SDG11。