首页> 外文会议>International Association for Energy Economics International Conference >THE OPEN SOURCE STOCHASTIC BUILDING SIMULATION TOOL SLBM AND ITS CAPABILITIES TO CAPTURE UNCERTAINTY OF POLICYMAKING IN THE US BUILDING SECTOR
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THE OPEN SOURCE STOCHASTIC BUILDING SIMULATION TOOL SLBM AND ITS CAPABILITIES TO CAPTURE UNCERTAINTY OF POLICYMAKING IN THE US BUILDING SECTOR

机译:开源随机建筑仿真工具SLBM及其在美国建筑业中捕获决策不确定性的能力

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The increasing concern about climate change as well as the expected direct environmental economic impacts of global warming will put considerable constraints on the US building sector, which consumes roughly 48% of the total primary energy, making it the biggest single source of CO2 emissions. It is obvious that the battle against climate change can only be won by considering innovative building approaches and consumer behaviors and bringing new, effective low carbon technologies to the building / consumer market. However, the limited time given to mitigate climate change is unforgiving to misled research and / or policy. This is the reason why Lawrence Berkeley National Lab is working on an open source long range Stochastic Lite Building Module (SLBM) to estimate the impact of different policies and consumer behavior on the market penetration of low carbon building technologies. SLBM is designed to be a fast running, user-friendly model that analysts can readily run and modify in its entirety through a visual interface. The tool is fundamentally an engineering-economic model with technology adoption decisions based on cost and energy performance characteristics of competing technologies. It also incorporates consumer preferences and passive building systems as well as interactions between technologies (such as internal heat gains). Furthermore, everything is based on service demand, e.g. a certain temperature or luminous intensity, instead of energy intensities. The core objectives of this paper are to demonstrate the practical approach used, to start a discussion process between relevant stakeholders and to build collaborations.
机译:对气候变化的越来越担心以及全球变暖的预期直接环境经济影响将对美国建设部门提出相当大的限制,该部门消耗总体总能量的约48%,使其成为二氧化碳排放的最大来源。很明显,只有考虑创新的建筑方法和消费者行为,才能赢得对气候变化的战斗,并为建筑物/消费者市场带来新的有效的低碳技术。但是,减轻气候变化的有限时间是误导研究和/或政策的不足。这就是为什么Lawrence Berkeley国家实验室正在开展开源长期随机lecation Lite建筑模块(SLBM)的原因,以估计不同政策和消费者行为对低碳建筑技术的市场渗透性的影响。 SLBM旨在是一个快速运行的用户友好的模型,分析师可以通过可视界面整体运行和修改。该工具基本上是一种基于竞争技术成本和能源性能特征的技术采用决策的工程学 - 经济模式。它还包括消费者偏好和被动建筑系统以及技术之间的相互作用(例如内部热量增益)。此外,一切都是基于服务需求,例如服务需求。一定的温度或发光强度,而不是能量强度。本文的核心目标是展示所使用的实用方法,开始相关利益攸关方之间的讨论过程并建立合作。

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