PyPSA-USA: A flexible open-source energy system model and optimization tool for the United States

Abstract

Developing effective energy policies is crucial for achieving emissions reduction targets, planning new infrastructure, adapting to evolving energy landscapes, and responding to emerging risks. Modern electricity systems require modeling frameworks that can capture complex interactions across generation, storage, and transmission infrastructure, as well as the effects of climate variability and extreme events. In this paper, we introduce PyPSA-USA, a novel, flexible, open-source model framework designed for power system planning in the continental United States. Built on the Python for Power System Analysis (PyPSA) framework, PyPSA-USA is highly configurable to support system operations and planning research at variable spatial and temporal scales. The framework offers flexible transmission representation by allowing users to select nodal resolution and power-flow representation, providing higher flexibility in the spatial domain than other open-source U.S. models. It integrates comprehensive data sources—including over 60 years of climate reanalysis data for renewable resource variability, detailed generator and storage unit characteristics, and policy constraints to support diverse research goals. Alongside the model, we additionally study the impacts of transmission expansion under differing decarbonization pathways, and highlight the value expansion plays in reducing system costs and driving renewable integration. 

Keywords: Energy Systems, Electricity System Planning, Capacity Expansion, Renewable Energy, Optimization