• Energy Research

Comprehensive global decarbonization will require that transportation services cease to rely on fossil fuels. Here we develop a generic life-cycle cost model to address two closely related questions central to the emergence of sustainable transportation: (i) the utilization rates (hours of operation) that rank-order alternative drivetrains in terms of their cost, and (ii) the cost-efficient share of clean energy drivetrains in a vehicle fleet of competing drivetrains. Calibrating our model framework in the context of urban transit buses, we examine how the comparison between diesel and battery-electric buses varies with the specifics of the duty cycle (route). We find that even for less favorable duty cycles, battery-electric buses will entail lower life-cycle costs once utilization rates exceed 20% of the annual hours. Yet, the current economics of that particular application still calls for a one-third share of diesel drivetrains in a cost-efficient fleet.

The recent sharp decline in the cost of renewable energy suggests that the production of hydrogen from renewable power through a power-to-gas process might become more economical. Here we examine this alternative from the perspective of an investor who considers a hybrid energy system that combines renewable power with an efficiently sized power-to-gas facility. The available capacity can be optimized in real time to take advantage of fluctuations in electricity prices and intermittent renewable power generation. We apply our model to the current environment in both Germany and Texas and find that renewable hydrogen is already cost competitive in niche applications (€3.23 kg−1), although not yet for industrial-scale supply. This conclusion, however, is projected to change within a decade (€2.50 kg−1) provided recent market trends continue in the coming years. Hydrogen fuel, produced from renewable power, could be critical in the decarbonization of the electricity and transportation sectors. Here, a thorough economic analysis shows that hydrogen obtained from wind power is already cost competitive in niche applications and may become widely competitive in the foreseeable future.

Rapid growth of intermittent renewable power generation makes the identification of investment opportunities in energy storage and the establishment of their profitability indispensable. Here we first present a conceptual framework to characterize business models of energy storage and systematically differentiate investment opportunities. We then use the framework to examine which storage technologies can perform the identified business models and review the recent literature regarding the profitability of individual combinations of business models and technologies. Our analysis shows that a set of commercially available technologies can serve all identified business models. We also find that certain combinations appear to have approached a tipping point toward profitability. Yet, this conclusion only holds for combinations examined most recently or stacking several business models. Many technologically feasible combinations have been neglected, indicating a need for further research to provide a detailed and conclusive understanding about the profitability of energy storage.

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.

AbstractThe pace of the global decarbonization process is widely believed to hinge on the rate of cost improvements for clean energy technologies, in particular renewable power and energy storage. This paper adopts the classical learning-by-doing framework of Wright (1936), which predicts that cost will fall as a function of the cumulative volume of past deployments. We first examine the learning curves for solar photovoltaic modules, wind turbines and electrolyzers. These estimates then become the basis for estimating the dynamics of the life-cycle cost of generating the corresponding clean energy, i.e., electricity from solar and wind power as well as hydrogen. Our calculations point to significant and sustained learning curves, which, in some contexts, predict a much more rapid cost decline than suggested by the traditional 80% learning curve. Finally, we argue that the observed learning curves for individual clean energy technologies reinforce each other in advancing the transition to a decarbonized energy economy.