The value of hedging against energy storage uncertainties when designing energy parks
Max Langtry, Ruchi Choudhary
TL;DR
The paper assesses how uncertainty in bulk energy storage performance affects energy park design and whether preserving optionality in storage technology is economically advantageous. Using Bayesian decision analysis, VoI, and VoO within a two-stage stochastic programming framework, it analyzes a Rotterdam-based energy park co-located with a 250 MW hydrogen electrolyser. Key findings show that updating designs after storage information reduces costs by about 18% on average, while allowing optionality across storage technologies adds roughly another 13% in savings; deploying two storage technologies further lowers costs but diminishes the value of optionality. The results are robust to uncertainty reduction levels and price/carbon data variations, suggesting flexible contracting and multi-technology deployment can significantly reduce decarbonization costs. These insights support incorporating uncertainty analysis and design flexibility into energy park development practice, with potential applicability to other asset classes and locations.
Abstract
Energy storage is needed to match renewable generation to industrial loads in energy parks. However, the future performance of bulk storage technologies is currently highly uncertain. Due to the urgency of decarbonization targets, energy park projects must be designed and begun now. But, as uncertainty in storage performance reduces, a different technology than identified during initial design may turn out cheaper. Enabling flexibility so that design adaptations can be made as better information becomes available would lower the cost of decarbonizing industry. But having this flexibility is itself costly. This raises the question, "Is it worth it?" This study quantifies the benefit of retaining flexibility to adapt energy park designs and optionality over storage technology choice as uncertainty reduces, to determine whether it is economically worthwhile. It applies the Value of Information analysis framework to the sizing of wind, solar, and storage in an illustrative energy park model based on a real-world proposal near Rotterdam, considering uncertainty in storage efficiency, lifetime, and capital cost. Updating asset sizings after storage uncertainty reduced is found to reduce total costs by 18% on average. Having the option to switch storage technology choice as well reduces costs by a further 13%, which is substantially greater than the cost of providing storage optionality. Using two storage technologies in the energy park reduces costs by 14%, and in this case storage optionality is not worthwhile. These results are robust to the level of uncertainty reduction in storage performance, and the risk aversion of the system designer.