We analyze how tariff design incentivizes households to invest in residential photovoltaic and battery systems, and explore selected power sector effects. To this end, we apply an open-source power system model featuring prosumage agents to German 2030 scenarios. Results show that lower feed-in tariffs substantially reduce investments in photovoltaics, yet optimal battery sizing and self-generation ...
DIETER is an open-source power sector model designed to analyze future settings with very high shares of variable renewable energy sources. It minimizes overall system costs, including fixed and variable costs of various generation, storage and sector coupling options. Here we introduce DIETERpy that builds on the existing model version, written in the General Algebraic Modeling System (GAMS), and ...
There is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. To this end, various types of energy models depend on meaningful input parameters, in particular on time series of BEV motor electricity consumption, grid availability, and grid electricity demand. As the availability of such data is highly limited, we introduce the open-source ...
We analyze the interactions between different renewable support schemes and the benefits of real-time pricing (RTP) using a stylized economic model with a detailed demand-side representation calibrated to the German market. We find that there are considerable differences between a market premium on energy and capacity regarding wholesale prices, support levies and market values, which are all related ...
The Dispatch and Investment Evaluation Tool with Endogenous Renewables (DIETER) has been developed in the research project StoRES to study the role of power storage and other flexibility options in a greenfield setting with high shares of renewables. The model determines cost-minimizing combinations of power generation, demand-side management, and storage capacities and their respective dispatch. DIETER ...