This paper introduces the full Low-carbon Expansion Generation Optimization (LEGO) model available on Github (https://github.com/wogrin/LEGO). LEGO is a mixed-integer quadratically constrained optimization problem and has been designed to be a multi-purpose tool, like a Swiss army knife, that can be employed to study many different aspects of the energy sector. Ranging from short-term unit commitment to long-term generation and transmission expansion planning. The underlying modeling philosophies are: modularity and flexibility. Its unique temporal structure allows LEGO to function with either chronological hourly data, or all kinds of representative periods. LEGO is also composed of thematic modules that can be added or removed from the model easily via data options depending on the scope of the study. Those modules include: unit commitment constraints; DC- or AC-OPF formulations; battery degradation; rate of change of frequency inertia constraints; demand-side management; or the hydrogen sector. LEGO also provides a plethora of model outputs (both primal and dual), which is the basis for both technical but also economic analyses. To our knowledge, there is no model that combines all of these capabilities, which we hereby make freely available to the scientific community.

中文翻译：

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完整的低碳扩张发电优化 (LEGO) 模型

本文介绍了 Github (https://github.com/wogrin/LEGO) 上可用的完整低碳扩张代优化 (LEGO) 模型。LEGO 是一个混合整数二次约束优化问题，它被设计成一种多功能工具，就像瑞士军刀一样，可用于研究能源领域的许多不同方面。从短期机组承诺到长期发电和输电扩展规划。基本的建模理念是：模块化和灵活性。其独特的时间结构允许 LEGO 使用按时间顺序排列的每小时数据或各种具有代表性的时期。乐高还由主题模块组成，这些模块可以根据研究范围通过数据选项轻松添加或从模型中删除。这些模块包括：单位承诺约束；DC- 或 AC-OPF 配方；电池退化；频率惯性约束的变化率；需求侧管理；或氢行业。LEGO 还提供大量模型输出（原始和双重），这是技术和经济分析的基础。据我们所知，没有任何模型可以结合所有这些功能，我们特此向科学界免费提供这些功能。