Risk-constrained stochastic scheduling of multi-market energy storage systems

Gabriel D. Patr\'on, Di Zhang, Lavinia M. P. Ghilardi, Evelin Blom, Maldon Goodridge, Erik Solis, Hamidreza Jahangir, Jorge Angarita, Nandhini Ganesan, Kevin West, Nilay Shah and Calvin Tsay

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Abstract: Energy storage can promote the integration of renewables by operating with charge and discharge policies that balance an intermittent power supply. This study investigates the scheduling of energy storage assets under energy price uncertainty, with a focus on electricity markets. A two-stage stochastic risk-constrained approach is employed, whereby electricity price trajectories or specific power markets are observed, allowing for recourse in the schedule. Conditional value-at-risk is used to quantify tail risk in the optimization problems; this allows for the explicit specification of a probabilistic risk limit. The proposed approach is tested in an integrated hydrogen system (IHS) and a battery energy storage system (BESS). In the joint design and operation context for the IHS, the risk constraint results in larger installed unit capacities, increasing capital cost but enabling more energy inventory to buffer price uncertainty. As shown in both case studies, there is an operational trade-off between risk and expected reward; this is reflected in higher expected costs (or lower expected profits) with increasing levels of risk aversion. Despite the decrease in expected reward, both systems exhibit substantial benefits of increasing risk aversion. This work provides a general method to address uncertainties in energy storage scheduling, allowing operators to input their level of risk tolerance on asset decisions.

Date: 2025-10
New Economics Papers: this item is included in nep-ene, nep-reg, nep-rmg and nep-upt
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