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Synergistic Value in Vertically Integrated Power‐to‐Gas Energy Systems

In vertically integrated energy systems, integration frequently entails operational gains that must be traded off against the requisite cost of capacity investments. In the context of the model analyzed in this study, the operational gains are subject to inherent volatility in both the price and the output of the intermediate product transferred within the vertically integrated structure. Our model framework provides necessary and sufficient conditions for the value (NPV) of an integrated system to exceed the sum of two optimized subsystems on their own. We then calibrate the model in Germany and Texas for systems that combine wind energy with Power‐to‐Gas (PtG) facilities that produce hydrogen. Depending on the prices for hydrogen in different market segments, we find that a synergistic investment value emerges in some settings. In the context of Texas, for instance, neither electricity generation from wind power nor hydrogen production from PtG is profitable on its own in the current market environment. Yet, provided both subsystems are sized optimally in relative terms, the attendant operational gains from vertical integration more than compensate for the stand‐alone losses of the two subsystems.
- Technical University of Munich Germany
- Massachusetts Institute of Technology United States
- Stanford University United States
- University of Mannheim Germany
power-to-gas, 330 Wirtschaft, operational volatility, renewable energy, vertical integration, ddc: ddc:330
power-to-gas, 330 Wirtschaft, operational volatility, renewable energy, vertical integration, ddc: ddc:330
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).20 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
