Optimising DERs in energy service networks: a case study - Modelling Distributed Energy Resources in Energy Service Networks - page 120

£7.65 per PU of natural gas. This cost differential clearly demonstrates the value of
how the aggregation of controllable DER technologies can influence DNO operating
costs. If these marginal cost differentials consider the thousands of existing networks,
the incremental cost benefits could be considerable. Also, this example could be used
to argue for different retail tariff schemes for consumers by rewarding shifting load;
these plans would be more sophisticated than the economy 7 tariffs currently avail-
able and would most likely focus on reflecting the real-time pricing of energy. Thus,
load flexibility needs to be incentivised in order to achieve an intelligent manage-
ment of energy infrastructures.

6.2.3 Natural gas network
From the analysis of the TCOPF results, it can be stated that natural gas networks
show that the presence of cogeneration technologies has mild effects on key operating
parameters when compared to the reference case. In general for these case studies,
the influence of CHP devices on natural gas demand is small. This is because dur-
ing winter time the conventional demand is very high, which makes the additional
demand from cogeneration almost negligible. However, it can be assumed that for
other seasonal periods this condition will not be as evident. Furthermore, although
the CHP effects are not pronounced, the various operating strategies modelled by
the TCOPF program do alter the operating parameters of the assets. Consequently,
Tables 6.8 and 6.9 describe the technical and economic natural gas network results
for the case studies conducted.
The following conclusions can be drawn from the technical results:

Since CHP technologies follow thermal demand in cases 2-4, their base load is
not as high as for the rest of the cases where CHPs are not constrained in their
operation;

●

The plug-and-forget simulations clearly show a slight increase in the peak demand,
while cases 4-7 curve the peak due to the incentives of their formulations;

●

The load factor is enhanced (to varying degrees) in all the simulations since the
average load increases while the peak load tends to be reduced, thus improving
the utilisation of the infrastructure;

●

Table 6.8 Technical results of the natural gas network

TCOPF Base load Peak load Load factor Slack Losses

case (MW th ) (MW th ) (%) (MWh th ) (MWh th )

1 0.60 27.17 43.92 286.43 11.14

2 0.53 27.32 44.41 291.22 11.76

3 0.48 27.32 45.83 290.89 11.67

4 1.02 25.57 48.58 289.33 10.11

5 2.52 25.70 49.71 298.18 8.92

6 1.58 26.64 48.99 303.16 11.26

7 1.73 26.37 49.42 303.05 11.15