Due to environmental concerns, offshore wind plant will play an important role in next decades for meeting the requirement of carbon emission and renewable energy target. The variable speed wind turbine will not have a load-frequency response similar with traditional synchronous generator which may cause the inertia less problems in the system. The UK National Grid has developed scenarios where high wind power penetration levels are considered which are likely to change the patterns of UK transmission network operation and dynamic performance. Therefore, it is necessary to develop an analytical capability which can assess the system dynamic performance ahead of the anticipated changes. Although some work has been reported in this area, the studies are either based on very simple network representations or involve very complex proprietary network modelling not publically available and with results which are often difficult to interpret. This thesis aims to develop appropriate ways of deriving a representative dynamic system model using UK transmission system as a benchmark. The methodology "Individual channel analysis and design (ICAD)" is utilized to realise the trade-off between plant dynamical requirements (feedback design) and the limitations (coupling effects) on achieving such requirements in multivariable system. A representative 21 bus dynamic model of the entire UK transmission system based on Ten Year Statement has been developed and implemented in Power System Simulator (PSS/E). A few recent system-wide events, captured by the existing Phasor Measurement Units (PMU), have been used to validate the frequency response of the model. Moreover, the General Electric (GE) type DFIG models are added for the purpose of analysing the future system performance with the increasing penetration levels of wind energy. The case study reveals that improvements are to be had by transmission line reinforcements under appropriate wind energy distribution scenarios with system transient stability largely improved. The impact of key influencing factors such as the size of the largest generating unit for n-1 contingency, amount of primary system response, frequency dependency of load, and others are presented. The study concludes that none of the individual factors can provide a complete solution and that careful cost benefit analysis is needed to determine the proper mix of services and reinforcements needed in the future.
|Date of Award||29 Apr 2015|
- University Of Strathclyde
|Supervisor||Adam Dysko (Supervisor) & Campbell Booth (Supervisor)|