The full Low-carbon Expansion Generation Optimization (LEGO) model

TL;DR

The LEGO model is a comprehensive, flexible, and modular optimization tool for energy sector planning, capable of addressing short-term and long-term issues with various modules and data structures.

Contribution

This paper presents LEGO, a novel, all-in-one energy optimization model that integrates multiple modules and features, unavailable in existing models.

Findings

Supports diverse energy sector analyses

Offers extensive output options for technical and economic insights

Combines multiple functionalities in a single open-source tool

Abstract

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.