Environmental Engineering Reference
In-Depth Information
Table 16.2 Typical combustion data of natural gases distributed in Germany, H-
gas grade
North
Sea/
Dornum
Dong
gas
(DK)
RWE
South
Waidhaus
(CIS)
Philips
Emden H ¨ nxe
H-gas
Density
0.8086
0.8099 0.8202 0.7464
0.8300
0.8103
Relative density, d
0.6254
0.6264 0.6344 0.5773
0.6419
0.6267
Superior heating value
H
s
, STP (kWh/m
3
)
11.492
12.076 11.337 11.226
12.028
11.551
Inferior heating value
H
i
, STP (kWh/m
3
)
10.381
10.919 10.244 10.126
10.878
10.437
Superior Wobbe index,
W
s
, STP (kWh/m
3
)
14.531
15.258 14.234 14.775
15.013
14.591
Source: Senner et al. (2011).
Table 16.3 The main advantages and disadvantages of LPG addition to
biomethane to achieve pipeline quality requirements in Germany
Advantages
Disadvantages
• Method is relatively easy to apply
• Can be applied on all network levels
without requiring different equipment
• Very high operating costs due to high
LPG input
• As the addition of LPG is limited, gas
compatibility cannot be obtained with
some gas grades (North Sea gases I
and II)
The computer-based heating value reconstruction method is applied.
.
Network zoning into districts with fixed heating value is defined.
.
.
Biogas is fed-in as additional gas.
Fuel gas conditioning with LPG, even if practised by many gas network
operators, entails very high operating costs. Therefore, the feasibility of the
other network compatibility measures should also be considered. Table 16.3
summarises the main advantages and disadvantages for LPG additions to
biomethane in the context of Germany.
16.4.2 Computer-based heating value reconstruction method
The heating value can subsequently be determined for any discharge point
from a network with a computer-based heating value reconstruction method
or heating value tracking system (REKO system). This method helps to
avoid high investment costs in measurement equipment at the feeding and
transfer points and high conditioning costs at biogas feeding points.
The computer-based heating value reconstruction system is a mathema-
tical model that creates a dynamic image of a complete network or network
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