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

Autor:	Wogrin, Sonja, Tejada-Arango, Diego A., Bachhiesl, Udo, Hobbs, Benjamin F.
Rok vydání:	2021
Předmět:	Mathematics - Optimization and Control Computer Science - Computational Engineering Finance and Science Computer Science - Mathematical Software Electrical Engineering and Systems Science - Systems and Control
Druh dokumentu:	Working Paper
Popis:	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. Comment: out of date
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2109.01368 Zobrazit plný text záznamu View this record from Arxiv