Environmental Engineering Reference
In-Depth Information
Aside from case 2 where losses slightly increase, losses are decreased for the
rest of the cases. Oddly enough, the minimum value is obtained when the whole
energy system is operated based on the real-time costs of the grid (
i.e.
cases 6
and 7) and not when energy losses are minimised (
i.e.
case 5); this is because
case 5 gives the same PU 'value' to thermal and electrical power losses;
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During the load flow calculations, cases 2 and 3 employ the OLTC device only
at moments of peak demand. For the rest of the cases the OLTC mechanism is
constantly used despite voltage levels never being near operating limits; this
condition is because the constraint allows us to reduce voltage drops when
possible;
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If this was solely a common electrical engineering exercise, the omission of not
evaluating the impacts cogeneration and PHEV have on operating costs of natural
gas and electrical networks would probably lead stakeholders to believe case 6
is the preferred scenario due to its technical virtues.
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The following conclusions can be drawn from the economic results:
The fuel costs for running the electrical network are higher in cases 2-4 because
of the incursion of PHEV load and low use of CHP; however, in cases 4-7 CHPs
produce more electricity and the operating costs are considerably reduced;
●
The energy costs results at spot market prices correlates to the fuel costs obtained;
thus, cases 6 and 7 are the most attractive for electric DNOs; this condition is
due to the fact that flexible load is supplied during low prices of energy;
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Taking the node furthest away from the slack as an example, the minimum LMC
increases slightly in most cases as a result of a higher base demand, while the
maximum LMC value tends to decrease as DER technologies are used to reduce
peak demand; overall, the difference between upper and lower LMCs is reduced.
●
Figures 6.23 and 6.24 characterise, based on the TCOPF case scenario imple-
mented, the electric power demand variations seen from the supply point. As
depicted by the figures, the introduction of DER devices has the potential of drasti-
cally changing the demand profile DNOs have become accustomed to expect in local
networks. In general terms, the simulations show the tendency of the TCOPF solver
to coordinate the resources in favour of an increase in the base load and a reduction
in the peak load.
As the above figures show, for case 1 the electric power demand has an early
low peak in the morning and then a high peak which occurs at 7 p.m., while the base
demand happens at 12:30 a.m., representing just 22.1% of the peak load. Therefore,
there is a peak-to-base load demand ratio of 4.52. Similarly, Table 6.14 details the
peak-to-base load demand ratio for all case studies. Despite the presence of DER
technologies with storage capabilities and although the peak demand is reduced, peak
times remain unchanged despite different formulations being applied.
The following conclusions can be drawn from the load profile results:
Case 3 yields the best utilisation of the infrastructure since the vehicles are only
allowed to charge at night time. Also in cases 2 and 3 utilities need to adapt to
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