Energy Strategy Reviews (Nov 2019)
Improved representation of investment decisions in the German energy supply sector: An optimization approach using the TIMES model
Abstract
The German energy supply sector is becoming diverse and dispersed due to the variety of actors investing in energy generation technologies and spatially variable renewable resources, which bring about increased heterogeneity in the investment decisions of actors. Therefore, the effective utilization of renewable resources towards a cost-optimal achievement of the “Energy Transition” goals is becoming more complex. We argue that addressing these complexities requires a method, which, in addition to a fine technological and regional characterization, takes into account the heterogeneity of the investment decisions of actors while optimizing the total system. This paper describes methodological improvements via the well-known energy system optimization model generator called The Integrated MARKAL-EFOM System (i.e. TIMES), which enhances the representation of the actors' investment realities regarding wind and photovoltaic technologies applied to the case of the German supply sector. Firstly, the actors are disaggregated by their main economic features, including cost of capital, representing their different investment valuations and budget restrictions. Then, Germany is divided into four regions to reflect the spatially variable renewable resources and electricity demand affecting actors’ optimal decisions. Lastly, the grid development costs and losses are considered, especially for power transmission across the regions. The newly developed TIMES Actors Model (TAM) incorporating these improvements is then tested to separately study the impact of CO2 taxes as a policy instrument and a national renewable quota as a target for the sector. The results showed that CO2 taxes and renewable targets affect the system quite differently, specifically regarding the optimal role that actors are expected to play within regions to meet the objectives of energy transitions at least system costs as well as regarding the power transmission between the regions. By means of these findings, actors can be targeted more properly by actor- and region-specific policy instruments demonstrating which actor should invest where and into which technology, so that the energy transition can take place more quickly and at lower system costs. A comparison of the improved versus original versions of the model reveals the potential contribution of improving the representation of actors that have been so far overlooked in the energy system modelling practice. Keywords: TIMES model generator, Energy system optimization, Supply sector, Actor heterogeneity, Investment decisions