NREL Standard Scenarios

NREL's Standard Scenarios are a suite of forward-looking scenarios of the U.S. power sector that are updated annually to support and inform energy analysis. The Standard Scenarios are simulated using the Regional Energy Deployment Systemand Distributed Generation Market Demand Model capacity expansion models and are updated each year to provide timely information regarding power sector evolution. The scenarios have been designed to capture a range of possible power system futures and consider a variety of factors from high vehicle electrification to major cost declines for electricity generation technologies (e.g., using costinputs from the Annual Technology Baseline). For select scenarios, the models are run using the PLEXOS software and the Cambium tool that assembles structured data sets of hourly cost, emissions, andoperational data for modeled futures. Results are available using the Scenario Viewer and Data Downloader. Archived from https://www.nrel.gov/analysis/standard-scenarios.html This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources: The PUDL Repository on GitHub PUDL Documentation Other Catalyst Cooperative data archives美国国家可再生能源实验室（National Renewable Energy Laboratory，NREL）的标准情景（Standard Scenarios）是一套前瞻性的美国电力部门情景合集，每年更新迭代，以支撑能源分析工作并为其提供决策参考。该系列情景依托区域能源部署系统（Regional Energy Deployment System）与分布式发电市场需求模型（Distributed Generation Market Demand Model）的容量扩展模型进行模拟，并每年更新，以期及时提供电力部门演进的相关资讯。本系列情景旨在覆盖电力系统未来的多种潜在发展路径，考量从车辆高电气化率到发电技术成本大幅下降等多类影响因素（例如采用年度技术基线（Annual Technology Baseline）中的成本输入参数）。针对部分选定情景，模型将借助PLEXOS软件与Cambium工具运行，后者可针对模拟的未来电力系统场景构建包含小时级成本、排放及运行数据的结构化数据集。相关分析结果可通过情景查看器（Scenario Viewer）与数据下载器（Data Downloader）获取。本存档原始链接归档自https://www.nrel.gov/analysis/standard-scenarios.html 本存档包含由Catalyst Cooperative开发的公共事业数据解放（Public Utility Data Liberation, PUDL）软件所需的原始输入数据，其采用无摩擦数据包（Frictionless Data Packages）格式进行组织。如需了解该数据及PUDL的更多详情，请参阅以下资源： GitHub平台上的PUDL存储库 PUDL官方文档 Catalyst Cooperative其他数据存档