Risk-Averse Markov Decision Processes: Applications to Electricity Grid and Reservoir Management

Arash Khojaste; Jonathan Pearce; Daniela Pucci de Farias; Geoffrey Pritchard; Golbon Zakeri

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arXiv · 2601.02207

Risk-Averse Markov Decision Processes: Applications to Electricity Grid and Reservoir Management

Arash Khojaste·Jonathan Pearce·Daniela Pucci de Farias·Geoffrey Pritchard·Golbon Zakeri

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Abstract

This paper develops risk-averse models to support system operators in planning and operating the electricity grid under uncertainty from renewable power generation. We incorporate financial risk hedging using conditional value at risk (CVaR) within a Markov Decision Process (MDP) framework and propose efficient, exact solution methods for these models. In addition, we introduce a power reliability-oriented risk measure and present new, computationally efficient models for risk-averse grid planning and operations.

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Arash Khojaste, Jonathan Pearce, Daniela Pucci de Farias, Geoffrey Pritchard, Golbon Zakeri. 2026-01-05. Risk-Averse Markov Decision Processes: Applications to Electricity Grid and Reservoir Management. https://arxiv.org/abs/2601.02207

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