Many new and renewable forms of electricity generation are small scale and geographically
constrained by the resource they use. They are connected into the local electricity
distribution network rather than the national transmission network and are known as Distributed
Generators (DGs). The developers (or owners) of such DG choose the location
and capacity of their plant to maximise the economic benefit that arises. However, the
distribution network was not planned and designed to accommodate such DG and various
problems can arise such as voltage magnitude disturbance, excessive power flow in certain
lines, excess fault levels, reverse power flows through the Grid Supply Point (GSP)
transformers and increased power losses. For this reason, the Distribution Network Operator
(DNO) may limit the capacity of plant built or constrain its output under certain
operating conditions. Such constraints clearly affect the economic case for the plant. Traditionally,
the economic and technical aspects of DG plant planning have been carried out
sequentially and not in an integrated fashion. This thesis investigates how to combine the
two sets of analysis such that both sets of influences are brought to bear in one process in
choosing an optimum plant capacity. By using the proposed methodology, the interests of
both the DG owner and the DNO are served. The proposed Techno-Economic assessment
tool has been developed for an example case of a biomass fuelled generator. The key factors
considered in the economic analysis are biomass yield density, transportation costs,
capital costs of plant and the value of unit electricity. An economically optimum plant can
be found based on the optimum radius of collection area. The issue of network constraints
have been investigated by using load flow analysis techniques with various case study networks.
The networks are real examples from the UK distribution network, chosen to give
a variety of meshed and radial structures and load densities. From the load flow analysis,indications of breaches of network constraints are generated and sensitivity indices are
produced which allow the proposed DG plants within the area to be constrained in various
ways depending on the optimisation objectives chosen. Conclusions are also drawn
on the extent to which the network structure and the geographic arrangement of load in
a network affect the siting and sizing of the optimal DG plant. Further factors that affect
the economics of a biomass plant are also considered. These include an analysis of the
effect of the physical shape as well as the location of the collection area. Other potential
sources of revenue in addition to the sale of electrical energy, include incentives for renewable
energy including carbon trading and Renewable Obligation Certificates (ROCs)
and the potential to provide various ancillary services to the network. The effect that these
additional sources of revenue may have on the Techno-Economic feasibility analysis have
also been investigated.