国家建筑存量自下而上的能源供应优化
Bottom-up energy supply optimization of a national building stock
摘要：
分布式能源（DER）的安装和运行以及供热的电气化显著改变了住宅建筑与电网基础设施的相互作用。评估DER在国家一级的大规模部署将需要分析数百万个建筑物，这将带来巨大的计算负担。为了克服这一点，这项工作提出了一种新的自下而上的模型，该模型包括一个聚合算法，从人口普查数据中创建一组空间分布的典型住宅建筑。每个典型的建筑物，然后优化与混合线性规划，以获得其成本最优的技术采用和操作，确定其在未来的情况下不断变化的电网负荷。该模型在德国进行了验证，200个典型的建筑物被认为是充分代表了住宅建筑存量的多样性。在2050年的未来情景中，光伏和热泵预计将成为不同建筑类型的最经济和生态稳健的供应解决方案。然而，它们的发电量和需求量在时间上并不匹配，导致冬季农村地区电网高峰负荷增加一倍。城市地区可以用高效的热电联产装置来弥补这一点，而农村地区的热电联产装置成本效益不高。
英文摘要：
The installation and operation distributed energy resources (DER) and the electrification of the heat supply significantly changes the interaction of the residential building stock with the grid infrastructure. Evaluating the mass deployment of DER at the national level would require analyzing millions of individual buildings, entailing significant computational burden. To overcome this, this work proposes a novel bottom-up model that consists of an aggregation algorithm to create a spatially distributed set of typical residential buildings from census data. Each typical building is then optimized with a Mixed-Integer Linear Program to derive its cost optimal technology adoption and operation, determining its changing grid load in future scenarios. The model is validated for Germany, with 200 typical buildings considered to sufficiently represent the diversity of the residential building stock. In a future scenario for 2050, photovoltaic and heat pumps are predicted to be the most economically and ecologically robust supply solutions for the different building types. Nevertheless, their electricity generation and demand temporally do not match, resulting in a doubling of the peak electricity grid load in the rural areas during the winter. The urban areas can compensate this with efficient co-generation units, which are not cost-efficient in the rural areas.
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