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Gewählte Doctoral Thesis:

Christian Kanzian (2017): Towards eco-efficient design of regional forest energy supply networks using mathematical optimization methods.
Doctoral Thesis - Institut für Forsttechnik (FT), BOKU-Universität für Bodenkultur, pp 162. UB BOKU obvsg

Data Source: ZID Abstracts
To reduce greenhouse gas emissions, the EU has ambitious goals, where energy wood (EW) is considered as an important resource for renewable energy production. The supply of EW is challenging because of high supply costs, rapidly increasing demand and a heterogeneous structure of landownership, contractors and energy producers. A framework to optimize forest energy supply networks has been proposed. Taking (1) demand, (2) amount of EW available, (3) terminals, (4) supply chain alternatives, (5) procurement strategies and (6) spatial data into account, mixed integer programming models were formulated and solved for different study regions to figure out optimal supply areas, transport distances and derive cost supply curves. A multi-criteria optimization problem (MOP) has been designed to determine the tradeoff between revenues maximization and emissions minimization. The MOP decides about chipping locations, transport modes and volumes and terminals used. The weighted sum approach was used to solve and apply the MOP to large-scale networks of 10,000 sources, 356 terminals, 119 freight stations and 228 plants. In an effort to minimize emissions, 30% of the EW should be delivered chipped from terminals and more than 50% chipped from forest, at emissions of 24.3 kg/t and a profit of 3.0 EUR/t. By changing the weight to maximize the profit, emissions will only increase by 4.5 %, whereas the profit more than doubles from 3.0 to 7.4 EUR/t. The average transport distance increases from 45.7 to 48.1 km and 73% of all terminals are used. Using the MOP influences of moisture content (MC) on revenues, demand and emissions has been studied. A decrease of 10% in MC from 40 to 30% will more than double the profit from 5.10 to 12.00 EUR/t. As expected, emissions will decrease with a decreasing MC. However, the effect on emissions is less prominent than on profit. Reducing MC from 40 to 30% will save approximately 4% of the GHG per t.

Betreuer: Stampfer Karl
1. Berater: Gronalt Manfred
2. Berater: Sterba Hubert

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