Dynamic Simulation and Intelligent Management of Distributed Generation

Significantly large integration of distributed generation (DG) is expected in future power systems. Paving the way are the encouraging government policies, great concerns on environment and optimising economic benefits. This large integration is however raising a lot of concern on stability, security and reliability of power system network which will create many challenges in operating the network due to different characteristics possessed by DG. These concerns and operating challenges need to be investigated to identify the possible problems that may arise and then followed by finding a countermeasure for mitigation. Research work in this thesis addresses most important issues and challenges in operating power system with large DG penetration. The following research areas are performed: • Modeling of distributed generation: New technology embraces by DG has totally different characteristics compared to conventional generation unit based on synchronous machine, thus making it necessary to perform integration studies on various operational aspects to assess the influence of this small scale generation unit on the power system network operation and control. The studies require an accurate and easy to understand dynamic model which closely imitates the dynamics of a real DG unit. In this thesis, development of different dynamic models of micro turbine generation system, fuel cell generation system and a generalized DG dynamic model to be used in power system studies is discussed. The performance of the model developed from the simulation results is found comparable to the reported performance in the literature. • DG fault ride-through capability: Due to different characteristics possessed by DG, power system operator imposed stringent requirements on the DG connected to the grid. During critical time DG has to be able to withstand a temporary voltage dip due to fault occurrence in the grid even when the voltage reaches zero at the point of connection. At the same time, during this fault ride-through DG must also help the grid by injecting reactive power to support power system voltage recovery. Different types of DG technologies are investigated if they are able to fulfil this requirement and if not exploring the necessary modifications which has to be made on the specific DG unit. The investigation results indicate that in fulfilling new grid code requirements, modification inside DG power electronic converter hardware and controller is necessary. iii • Grid support by DG: Massive DG integration in distribution network will interfere with current practices and control scheme inside the network. With appropriate coordination and control, this negative influence on network could be changed to positive. This thesis explores the possibility of participating DGs in voltage regulation and frequency control. Clearly the studies indicate that DG coupled to the grid through power electronic converter has potential to positively contribute to power system voltage regulation and frequency stabilisation. • Influence of DG on power system stability under new grid codes: Power electronic converter utilised in DGs makes them have different characteristics in responding to grid fault and they are also demanded to provide reactive support during this period. This characteristic and new rule is feared to negatively influence the stability of a power system as to where these DG units are connected to. In this thesis the most important types of stability are analysed with different levels of DG penetration and control options. It can be concluded that if DG is properly located and controlled, DG integration will significantly improve the stability of power system network. • Predictive var management inside future distribution network: Future distribution network will contain large number of DG units and the network will be integrated with advance communication facilities. This large number of DG will create technical challenges but the communication link available will provide the opportunity to control DG centrally in real time to optimise the benefits offered by DG integration. In this thesis, a predictive technique in managing DG reactive power to reduce power loss and to control the voltage inside a distribution network is proposed and discussed. The effectiveness of the proposed approach which are developed with two staged intelligent techniques namely, adaptive particle swarm optimisation and artificial neural network, is demonstrated and the results are quite promising.


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