Geographical balancing of wind power decreases storage needs in a 100% renewable European power sector.

To reduce greenhouse gas emissions, many countries plan to massively expand wind power and solar photovoltaic capacities. These variable renewable energy sources require additional flexibility in the power sector. Both geographical balancing enabled by interconnection and electricity storage can provide such flexibility. In a 100% renewable energy scenario of 12 central European countries, we investigate how geographical balancing between countries reduces the need for electricity storage. Our principal contribution is to separate and quantify the different factors at play. Applying a capacity expansion model and a factorization method, we disentangle the effect of interconnection on optimal storage capacities through distinct factors: differences in countries' solar PV and wind power availability patterns, load profiles, as well as hydropower and bioenergy capacity portfolios. Results indicate that interconnection reduces storage needs by around 30% in contrast to a scenario without interconnection. Differences in wind power profiles between countries explain around 80% of that effect.

Renewable energy targets and unintended storage cycling: Implications for energy modeling.

To decarbonize the economy, many governments have set targets for the use of renewable energy sources. These are often formulated as relative shares of electricity demand or supply. Implementing respective constraints in energy models is a surprisingly delicate issue. They may cause a modeling artifact of excessive electricity storage use. We introduce this phenomenon as "unintended storage cycling", which can be detected in case of simultaneous storage charging and discharging. In this paper, we provide an analytical representation of different approaches for implementing minimum renewable share constraints in energy models, and show how these may lead to unintended storage cycling. Using a parsimonious optimization model, we quantify related distortions of optimal dispatch and investment decisions as well as market prices, and identify important drivers of the phenomenon. Finally, we provide recommendations on how to avoid the distorting effects of unintended storage cycling in energy modeling.

Optimal supply chains and power sector benefits of green hydrogen.

Green hydrogen can help to decarbonize parts of the transportation sector, but its power sector interactions are not well understood so far. It may contribute to integrating variable renewable energy sources if production is sufficiently flexible in time. Using an open-source co-optimization model of the power sector and four options for supplying hydrogen at German filling stations, we find a trade-off between energy efficiency and temporal flexibility. For lower shares of renewables and hydrogen, more energy-efficient and less flexible small-scale on-site electrolysis is optimal. For higher shares of renewables and/or hydrogen, more flexible but less energy-efficient large-scale hydrogen supply chains gain importance, as they allow to temporally disentangle hydrogen production from demand via storage. Liquid hydrogen emerges as particularly beneficial, followed by liquid organic hydrogen carriers and gaseous hydrogen. Large-scale hydrogen supply chains can deliver substantial power sector benefits, mainly through reduced renewable curtailment. Energy modelers and system planners should consider the distinct flexibility characteristics of hydrogen supply chains in more detail when assessing the role of green hydrogen in future energy transition scenarios. We also propose two alternative cost and emission metrics which could be useful in future analyses.

An open tool for creating battery-electric vehicle time series from empirical data, emobpy.

There is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses. They depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricity consumption, grid availability, or grid electricity demand. As the availability of such data is highly limited, we introduce the open-source tool emobpy. Based on mobility statistics, physical properties of battery-electric vehicles, and other customizable assumptions, it derives time series data that can readily be used in a wide range of model applications. For an illustration, we create and characterize 200 vehicle profiles for Germany. Depending on the hour of the day, a fleet of one million vehicles has a median grid availability between 5 and 7 gigawatts, as vehicles are parking most of the time. Four exemplary grid electricity demand time series illustrate the smoothing effect of balanced charging strategies.

Practicalities of individual producer responsibility under the WEEE directive: experiences in Germany.

In theory, individual producer responsibility (IPR) creates incentives for 'design-for-recycling'. Yet in practice, implementing IPR is challenging, particularly if applied to waste electric and electronic equipment. This article discusses different options for implementing IPR schemes under German WEEE legislation. In addition, practical aspects of a German 'return share' brand sampling scheme are examined. Concerning 'new' WEEE put on the market after 13 August 2006, producers in Germany can choose between two different methods of calculating take-back obligations. These can be determined on the basis of 'return shares' or 'market shares'. While market shares are regularly monitored by a national clearing house, the 'return share' option requires sampling and sorting of WEEE. Herein it is shown that the specifics of the German WEEE take-back scheme require high sample sizes and multi-step test procedures to ensure a statistically sound sampling approach. Since the market share allocation continues to apply for historic waste, producers lack incentives for choosing the costly brand sampling option. However, even return share allocation might not imply a decisive step towards IPR, as it merely represents an alternative calculation of market shares. Yet the fundamental characteristics of the German take-back system remain unchanged: the same anonymous mix of WEEE goes to the same treatment operations.