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用于生成瑞典、德国和英国合成住宅低压电网的数据集。

Dataset for generating synthetic residential low-voltage grids in Sweden, Germany and the UK.

作者信息

Hartvigsson Elias, Odenberger Mikael, Chen Peiyuan, Nyholm Emil

机构信息

Department of Space Earth and the Environment, Division of Energy Technology, Chalmers University of Technology, Sweden.

Department of Electric Engineering, Division of Electric Power Engineering, Chalmers University of Technology, Sweden.

出版信息

Data Brief. 2021 Apr 6;36:107005. doi: 10.1016/j.dib.2021.107005. eCollection 2021 Jun.

Abstract

Assessing grid capacity on national and local levels is important in order to formulate renewable energy targets, calculate integration costs of distributed generation (such as residential solar PV and electric vehicles). Currently, 70-96% of the residential solar PV installations in Germany and Italy are found in the low-voltage grid. Previous grid assessments have relied on grid data from individual low-voltage grids, making them limited to a few cases. This article presents synthetic low-voltage grid data from a reference network model. The reference network model generates synthetic low-voltage grids using publicly available data and national regulations and standards. In addition, the article presents data of residential solar photovoltaic hosting capacity in low-voltage grids. The datasets are high-resolution (1 × 1 km) and contains data on electricity peak demand, share of population living in apartments and important grid metrics such as transformer capacity, maximum feeder length and estimations of residential solar photovoltaic hosting capacity. Datasets on grid components are rare and the dataset can be used to assess grid impacts from other residential end-use technologies, and function as baseline for other reference network models.

摘要

评估国家和地方层面的电网容量对于制定可再生能源目标、计算分布式发电(如住宅太阳能光伏和电动汽车)的整合成本非常重要。目前,德国和意大利70%至96%的住宅太阳能光伏装置位于低压电网中。以往的电网评估依赖于单个低压电网的电网数据,因此仅限于少数案例。本文展示了来自参考网络模型的合成低压电网数据。该参考网络模型利用公开可用数据以及国家法规和标准生成合成低压电网。此外,本文还展示了低压电网中住宅太阳能光伏接纳能力的数据。这些数据集分辨率高(1×1千米),包含电力峰值需求、居住在公寓中的人口比例以及诸如变压器容量、最大馈线长度和住宅太阳能光伏接纳能力估算等重要电网指标的数据。关于电网组件的数据集很少见,该数据集可用于评估其他住宅终端使用技术对电网的影响,并作为其他参考网络模型的基准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de57/8086020/6556be98bcb3/gr1.jpg

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