• Energy Research

Abstract Background Many governments take the view that voluntary national targets to reduce greenhouse gas emissions are sufficient to avoid negative climate effects. In the absence of independent verification, however, pledges are unlikely to be sufficient for a rapid and strong reduction of emissions. It is often claimed that a global carbon tax could be an effective instrument. However, such a tax is difficult to set and to collect, especially in countries with poor administrative infrastructure. Results Here, we formulate and discuss a novel approach, the Global Carbon Surcharge (GCS), that mimics a carbon tax but does not require tax collection by governments. We define GCS as a requirement or a voluntary commitment encompassing all companies extracting carbon-carrying raw materials, namely coal, oil, gas and limestone, with the aim to burden their extraction with costs proportional to their carbon intensity. GCS mandates all companies to store these materials immediately after mining for a given period of time in the vicinity of the production site. Thereby, GCS generates additional costs that propagate through all sectors of the global economy. We elucidate how the investment costs for the storage infrastructure translate into surcharges on the raw materials. Conclusions We show that by a proper choice of the storage time and the size of the storage unit, GCS becomes equivalent to a carbon tax in the range between 50 and 100 € per ton of CO2 that is assumed to be necessary for the transition to a carbon-neutral energy system. An attractive feature of GCS is that it can be verified, in particular by citizens themselves, using publicly available satellite data. Finally, if compulsory storage is coupled to blockchain-based smart contracts and a mandatory (expensive) mining of cryptocurrency, GCS can be operated without governmental protectionism, corruption and fraud. However, the main uncertainties of the GCS approach lie in the substantial expansion of infrastructure and the fact that the induced price effects must be sufficient to achieve a rapid and far-reaching substitution of fossil fuels.

While investments in renewable energy sources (RES) are incentivized around the world, the policy tools that do so are still poorly understood, leading to costly misadjustments in many cases. As a case study, the deployment dynamics of residential solar photovoltaics (PV) invoked by the German feed-in tariff legislation are investigated. Here we report a model showing that the question of when people invest in residential PV systems is found to be not only determined by profitability, but also by profitability's change compared to the status quo. This finding is interpreted in the light of loss aversion, a concept developed in Kahneman and Tversky's Prospect Theory. The model is able to reproduce most of the dynamics of the uptake with only a few financial and behavioral assumptions

PV-battery systems are currently not operated in an energy system optimal way as their operation heuristic (maximization of self-consumption) is generally unaffected by competitive market signals. To evaluate potential regulatory intervention, we propose a market alignment indicator which measures the relative economic efficiency of a prosumer battery compared to a benchmark system that is completely responsive to wholesale market prices. Investigating the case of PV-battery systems in Germany, we find that scarcity signals transmitted to prosumers improve the market alignment of PV-battery systems while retaining similar levels of self-consumption and autarky rates. Both dynamic prices for generation (time-varying feed-in remuneration) and consumption (real-time electricity prices) can improve welfare, that is lowering consumer expenditures for electricity at the wholesale market. The effectiveness of the respective instrument mix depends on the relative levels of the feed-in tariff, the grid consumption to be saved and the solar generation costs. Accordingly, increasing fixed network charges can have a significant positive impact on the market alignment of prosumer batteries if combined with dynamic prices, as they change the relative composition of retail prices.

Wind and solar energy play a pivotal role in deep decarbonization pathways for the future. However, energy scenario studies differ substantially in the contribution of these technologies, as the technology selection in models strongly depends on the choice of techno-economic parameters. In this article, we systematically compare the cost assumptions for solar and wind technologies in global, regional and national energy scenario studies with costs observed in reality and with recent remuneration from market auctions. Specially, we compared the capital expenditure (CAPEX) and the levelized cost of electricity (LCOE) towards the year of 2050 when available with historical market prices and auction prices. Our results indicate that the trend of rapid cost declines has been structurally underestimated in virtually all future energy scenario analyses and suggest that even the most recent studies refer to obsolete or very conservative values. This leads to underestimating the future role and level of deployment of renewable technologies. We recommend an open database for costs of renewable technologies to enhance the accuracy and transparency of future energy scenarios.

Wind and solar power play a pivotal role in deep decarbonization pathways. However, energy scenario studies differ substantially in the absolute and relative contribution of these technologies, as the technology choice in model assessments depends strongly on the choice of certain techno-economic parameters. In this presentation we systematically compare cost assumptions for variable renewable energy sources (VRE) in global energy scenarios with recent remuneration levels determined via market-based auction mechanisms. Our results indicate that the rapid cost decline of renewables has been structurally underestimated and suggest that many current studies refer to obsolete or very conservative literature values and status-quo bias, potentially significantly underestimating future deployment levels of VRE and their decarbonization potentials.