In contrast with traditional approaches based either on the analysis of a small
specific area or on idealistic networks, the proposed methodology determines optimal
network design policies by evaluating alternative planning strategies on statistically similar
networks. The position of consumers influences the amount of equipment used to serve
them. Therefore, simple geometric models or randomly placed points used in previous
researches are not adequate. Using an algorithm based on fractal theory, realistic consumer
sets are generated in terms of their position, type and demand to allow statistical evaluation
of the cost of different design policies.
In order to systematically deal with the problem of determining justifiable network
investments, the concept of economically adapted distribution network was investigated and
applied in the context of a loss-inclusive design promoting efficient investment policies
from an overall social perspective.
The network’s components are optimized, after yearly load flow calculations, based
on the minimum life-cycle cost methodology, balancing annuitised capital investments and
maintenance costs against the cost of system operation. Evaluating the cost of each
particular design over statistically similar networks allows statistically significant
conclusions to be drawn.
The main results include the optimal number of substations for typical urban and
rural LV, HV and EHV distribution systems, network costs (investment, purchasing and
maintenance) and losses as well as the sensitivity of optimal network design to future energy prices and cost of equipment.
The impact of the increasing amount of microgeneration on networks has not been
fully addressed to date. There have not been clustering problems in existing networks as a
result of customers choosing to install microgenerators, either as a new device or as a
replacement of a previous heating system. The operation of microgeneration connected to
the distribution network can cause statutory voltage limits, recommended voltage unbalance
levels and switchgear fault ratings to be exceeded. However, there are a range of
distribution network designs and operating practices and thus the impact will vary
accordingly.
The operation of distribution networks is approached considering the existence of
single or three-phase loads and microgeneration. This would however cause the network to
be unbalanced and hence, traditional methods that consider a three-phase balanced system
would provide misleading results.
Every residential daily load’s behaviour shows rapid shifts from “load valleys” to
high peaks due to the random and frequent “switch on/off” of appliances. Modelling each
load individually will reveal problematic operating conditions which were not considered
when using a smooth load profile. Thus, each and every domestic load was represented by a
different load profile and the impact on losses was evaluated.
Relating losses, voltages, currents and load unbalance ratio leads to conclusions
about the way how to optimise the network with DG. The aim was to investigate and
develop methodology for evaluation of the long-term loss-inclusive optimal network design
strategies and to determine the effect of the penetration of microgeneration, such as CHP
and PV, in realistic distribution networks and optimal network planning. The need for
reinforcement of network components will depend on the level of generation and on the
extent to which reverse power flows occurs. In most parts of the network, microgeneration
exports will not be sufficient to result in any need for network investment. However, if the
network was to be planned accounting with DG, capital investment scenarios are presented
and compared to existing networks trying to accommodate clusters of microgeneration.