Review of Core Process Representation in Power System Operational Models: Gaps, Challenges, and Opportunities for Multisector Dynamics Research

Abstract

Power grid operations increasingly interact with environmental systems and human systems such as transportation, agriculture, the economy, and financial markets. Our objective is to discuss the modelling gaps and opportunities to advance the science for multisector adaptation and tradeoffs. We focus on power system operational models, which typically represent key physical and economic aspects of grid operations over days to a year and assume a fixed power grid infrastructure. Due to computational burden, models are typically customized to reflect regional resource opportunities, data availability, and applications of interest. While there are model intercomparison papers, there is however no model-agnostic characterization and systematic overview of the state-of-the-art process representations in operational power system models. To address our objective, we conceptualize power system operational models with four core processes: physical grid assets (generation, transmission, loads, and storage), model objectives and purpose, institutions and decision agents, and performance metrics. We taxonomize the representations of these core processes based on a review of 23 existing open-source and commercial models. As we acknowledge the computational burden of certain representations, we leverage this taxonomy to describe tradeoffs in process fidelity and tractability that have been adopted by the research community to address interactions between the power grid and hydrometeorological uncertainties, global change, and/or technological innovation. The core process taxonomy along with the existing computational tradeoffs are used to identify technical gaps and recommend future model development needs and research directions to better represent power grid operations as part of integrated multisector dynamics modeling and interdisciplinary research.