28.02.2013 Aufrufe

Potentiale zur energetischen Nutzung von Biomasse in der ... - EPFL

Potentiale zur energetischen Nutzung von Biomasse in der ... - EPFL

Potentiale zur energetischen Nutzung von Biomasse in der ... - EPFL

MEHR ANZEIGEN
WENIGER ANZEIGEN

Sie wollen auch ein ePaper? Erhöhen Sie die Reichweite Ihrer Titel.

YUMPU macht aus Druck-PDFs automatisch weboptimierte ePaper, die Google liebt.

GIS model 185<br />

Bundesamt für Energie BFE<br />

subject to the marg<strong>in</strong>al cost (maximum unit price) of the specified amount of delivered biomass. Details<br />

of this methodology are given below.<br />

First, the type and quantity of available energy biomass resources and its respective farm-gate prices are<br />

def<strong>in</strong>ed for each pixel. Then each pixel is assigned to its nearest node (n) on the road network through<br />

the use of “near<strong>in</strong>g” algorithm with<strong>in</strong> GIS software (Figure 48). Assum<strong>in</strong>g that the centre po<strong>in</strong>t of each<br />

pixel (i) represents the whole pixel, one can obta<strong>in</strong> a straight-l<strong>in</strong>e distance from any pixel to its nearest<br />

road node. The distance between two nodes on the road network can be computed us<strong>in</strong>g the “shortest<br />

path” method. The total distance between supply po<strong>in</strong>t i and demand po<strong>in</strong>t j can be calculated as the<br />

sum of three components: (1) the straight-l<strong>in</strong>e distance from biomass supply po<strong>in</strong>t i to its nearest road<br />

network node n1, (2) the shortest path distance across the network from the node nearest to the supply<br />

pixel n1 to the node nearest to the dest<strong>in</strong>ation pixel n2, and the straight-l<strong>in</strong>e distance from the<br />

dest<strong>in</strong>ation po<strong>in</strong>t j to its nearest node n2.<br />

Figure 48 Assessment of biomass supply cost; Source: Noon et al., 2002<br />

The next step is to calculate the total transportation cost per unit of biomass. It is assumed that the local<br />

road segments from supply po<strong>in</strong>t to node and from node to the f<strong>in</strong>al dest<strong>in</strong>ation po<strong>in</strong>t would be<br />

travelled with lower speed than the distance from node to node. Hence, the total transportation cost<br />

will also depend on the travell<strong>in</strong>g time parameter <strong>in</strong> addition to the overall distance between supply and<br />

demand po<strong>in</strong>ts. The distance dependent cost parameter is <strong>der</strong>ived from empirical data on track costs<br />

such as fuel, lubrication, ma<strong>in</strong>tenance, repairs and tires. The time dependent cost parameter is <strong>der</strong>ived<br />

from empirical data related to driver labour costs, vehicle depreciation, <strong>in</strong>surance and fees. The travell<strong>in</strong>g<br />

time is estimated by summ<strong>in</strong>g fast and slow segments’ distances divided by respective segments’ travel<br />

speed.<br />

The delivered cost of a unit of biomass from supply po<strong>in</strong>t i to demand po<strong>in</strong>t j can be calculated by<br />

summ<strong>in</strong>g the farm-gate price at po<strong>in</strong>t i, the total transportation cost per unit of biomass and specific<br />

load<strong>in</strong>g/secur<strong>in</strong>g/unload<strong>in</strong>g costs accord<strong>in</strong>g to the follow<strong>in</strong>g equation:

Hurra! Ihre Datei wurde hochgeladen und ist bereit für die Veröffentlichung.

Erfolgreich gespeichert!

Leider ist etwas schief gelaufen!