| dc.description.abstract | High penetration of distributed generation (DG) is evident in the development of
modern power systems, and this trend is expected to continue growing. Grid
integration control strategies have been recognized as the main way to save
investment, reduce fossil fuel energy consumption, and improve the reliability and
flexibility of power systems. The distribution network itself is also a weak link that
causes the deterioration of power quality and affects the overall performance and
efficiency of the system. Therefore, smart distribution networks play a decisive
role in the overall concept of the smart grid. Smart inverter control is more
appreciated in the field of optimal operation of low voltage distribution networks
with high penetration of distributed generations, due to its advantages of high
flexibility, quick response time and low additional system cost.
The work presented in this PhD thesis aims to investigate the impact of high
penetration of distributed energy resource in the power system and develop a
multi-objective optimisation method to improve the distributed network performance.
This research studied the impact of the access of a large number of distributed
energy sources such as rooftop solar photovoltaics on low carbon power availability
and quality of supply within the distribution network. By looking for the best model composition, it created a distribution network model with highly
distributed photovoltaics.
The optimized maximum capacity and location of the solar energy configuration
in the distribution network are realized through voltage sensitivity and genetic
algorithm. The concept of adjusting reactive power output in distribution
network to affect system characteristics are based on the smart inverter functions
of distributed photovoltaics. To further conduct the multi-objective control,
this thesis proposed an adaptive particle swarm optimisation scheme. The
main algorithm based on multi-objective particle swarm optimization (MOPSO)
algorithm, which uses the concept of Pareto dominance to find solutions for multi-objective problems.
Through the investigation of the interactions of multiple effects such as voltage
fluctuations, system cost and CO2 emissions in a distributed network with
saturated PV penetration, with the advanced algorithm in planning photovoltaics
and further smart inverter volt/var control scheme, the generation cost and
GHG emission curve were improved and avoid the disturbance to customer
behaviours. This thesis also proposed an adaptive multi-objective control scheme
for distribution networks with photovoltaics infeed, on the basis of smart inverter
control. To cater for the fact that low voltage distribution network may face
problems such as voltage mitigation, system loss increase and customer also
requires to pay less bill. The method is designed to solve these multiple conflict
objectives. The correctness and validity of the proposed strategy are verified by
numerical examples in a radial large 149 bus system.
This thesis conducted detailed investigation of highly distribution network characteristics and proposed a process of multi-objective control scheme for the distribution network. It not only illustrated the control method, but also included
the implementation requirement and consideration beforehand and afterwards. In addition, unlike mostly previous work, the work presented in this thesis included
benefits of users as one of the optimisation goals. Therefore, this work can be
adopted and applied by DSO as a technical reference and for trade-off decision
makings in a highly distributed energy network. | en |
