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New energy efficiency policies have been introduced around the world. Historically, most energy models were reasonably equipped to assess the impact of classical policies, such as a subsidy or change in taxation. However, these tools are often insufficient to assess the impact of alternative policy instruments. We evaluate the so-called engineering economic models used to assess future industrial energy use. Engineering economic models include the level of detail commonly needed to model the new types of policies considered. We explore approaches to improve the realism and policy relevance of engineering economic modeling frameworks. We also explore solutions to strengthen the policy usefulness of engineering economic analysis that can be built from a framework of multidisciplinary cooperation. The review discusses the main modeling approaches currently used and evaluates the weaknesses in current models. We focus on the needs to further improve the models. We identify research priorities for the modeling framework, technology representation in models, policy evaluation, and modeling of decision-making behavior.
In the coming years, we must set a course that will allow as to protect our climate, reduce resource consumption, and preserve biodiversity. A profound ecological system change is on the horizon in all central areas of action of the economy and society, or transformation arenas.
Digitalisation is a prerequisite for the success in this change and will impact these arenas at multiple levels: Digital technologies and applications will make it possible to improve current procedures, processes, and structures (Improve) and help us take the first steps towards new business models and frameworks (Convert). Despite this, digitalisation itself must be effective enough to facilitate a complete ecological restructuring of our society and lives to achieve more far-reaching economic transformation and value creation (Transform).
The ability to obtain, link, and use data is a basic prerequisite for tapping into the potential of digitisation for sustainability transformation. However, data is not a homogeneous raw material. Data only gains value when we know the context in which it was collected and when we can use it for a specific purpose.
The discussion on what structures and prerequisites are necessary for the system-changing use of data has only just begun. This study was conducted to serve as a starting point for this discussion as it describes the opportunities and prerequisites for a data-based sustainability transformation. This study focuses on environmental data, data from plants, machines, infrastructure, and IoT products. Our task will be to increase the use this data for systemic solutions (system innovation) within transformation arenas where different stakeholders are working together to initiate infrastructure, value chain, and business model transformation.
Considering the enormous ecological and economic importance of the transport sector the introduction of alternative fuels - together with drastic energy efficiency gains - will be a key to sustainable mobility, nationally as well as globally. However, the future role of alternative fuels cannot be examined from the isolated perspective of the transport sector. Interactions with the energysystem as a whole have to be taken into account. This holds both for the issue of availability of energy sources as well as for allocation effects, resulting from the shift of renewable energy from the stationary sector to mobile applications. With emphasis on hydrogen as a transport fuel for private passenger cars, this paper discusses the energy systems impacts of various scenarios introducing hydrogen fueled vehicles in Germany. It identifies clear restrictions to an enhanced growth of clean hydrogen production from renewable energy sources (RES). Furthermore, it points at systems interdependencies that call for a priority use of RES electricity in stationary applications. Whereas hydrogen can play an increasing role in transport after 2030 the most important challenge is to exploit short–mid-term potentials of boosting car efficiency.