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Synthesizing energy system investment portfolio performance across climate models to address the practitioner’s dilemma

CSS Publication Number
CSS26-04
Full Publication Date
January 2, 2026
Abstract

Alternative but equally plausible future climate realizations can necessitate different energy system investments, posing a dilemma to practitioners when making investment decisions. Addressing this dilemma requires quantitative methods to synthesize information across climate realizations, which are lacking in the energy systems community. This research presents a decision-making framework that centers a variability index to quantify resource adequacy (RA) contributions of investments across potential climate realizations. The research framework is applied to the Western U.S. power system, with a focus on California RA outcomes, by integrating dynamically downscaled data from five climate models with an RA model that simulates generator outages and optimizes transmission and storage operations. This framework finds investment portfolios can have highly variable RA contributions between climate models. For instance, a wind-and-battery portfolio reduces expected unserved energy by 78% in one climate model but by only 47% in another. This range of behaviors yields a variability index of 0.65 for the wind-and-battery investment, much higher than a variability index of 0.2 for a solar-only investment portfolio that achieves more consistent RA reductions. By combining the variability index with a benefit metric, this work shows a frontier of investment options that illuminate trade-offs for decision-makers and synthesize outcomes across plausible climate realizations.

Research Areas
Framework, Methods & Tools
Energy Systems
Keywords

Energy system investment portfolio performance, climate models, practitioner’s dilemma, resource adequacy (RA)

Publication Type
Journal Article
Digital Object Identifier
10.1088/1748-9326/ae2f74
Full Citation

Christino, M. & Craig, M. T. (2026). Synthesizing energy system investment portfolio performance across climate models to address the practitioner’s dilemma. Environ. Res. Lett. 21, 014016. CSS26-04.