Search

Biogasproduktion wird in Deutschland mit dem Ziel des Klima- und Umweltschutzes sowie der Substitution fossiler Energieträger durch das Erneuerbare-Energien-Gesetz (EEG) gefördert. Dieser Beitrag analysiert quantitativ durch Kopplung eines Agrarsektor- und eines Standortmodells die Novellierung des EEGs in 2008. Die Ergebnisse zeigen, dass die Novellierung durch einen verstärkten Ausbau der Energieerzeugung durch Biogas zur weiteren Substitution fossiler Energieträger beiträgt, allerdings auch zu höheren Kosten pro erzeugter Einheit Strom. Die Flächeneffizienz sinkt, während Transportemissionen ansteigen. Eine alternativ untersuchte Ausgestaltung einer anlageunabhängigen Vergütung im EEG zeigt die höchste Subventionseffizienz, bei allerdings niedrigerer Flächeneffizienz und höheren Transportemissionen im Vergleich zum EEG vor der Novellierung. The Renewable-Energy-Source-Act (EEG) promotes German biogas production in order to substitute fossil fuels, protect the environment and prevent climate change. In this paper we quantitatively analyse the EEG-reform in 2008. Results imply that the reform contributes to an expansion of biogas electricity generation and thus to substitution of fossil fuels. However, subsidies, land and transport emissions per unit of electricity produced increase. An alternative analysis shows that an EEG with tariffs independent from plant-types would provide the highest subsidy-efficiency, lower land requirements and higher transport emissions compared to EEG before its reformation.

The location of first generation processing plants for biogas using bulky inputs is a prominent example of locational decisions of plants that face high per unit transport costs of feedstock and simultaneously depend to a large extent on feedstock availability. Modelling the resulting regional feedstock markets then requires a spatially explicit representation of demand. With production capacities of plants small in comparison to market size, large numbers of possible type-location combinations need to be considered, requiring considerable computation time under existing integer programming-based approaches. Therefore, in this paper we aim to present an alternative, faster and more flexible iterative solution approach to simulate location decisions for processing plants. And with greater flexibility, this approach is able to take into account spatially heterogeneous transport costs depending on total demand. The approach is implemented in a modelling framework for biogas production from green maize in Germany, which currently accounts for ca. five percent of Germany's agricultural area. By modifying green maize prices, demand functions are derived and intersected with regional supply functions from an agricultural model to simulate market clearing prices and quantities. The application illustrates that our approach efficiently simulates markets characterised by small-scale demand units and high, spatially heterogeneous transport costs.