Optimal placement and effect of a wind farm on load flow and protection systems in a municipal distribution network

Much research has been done on the effects of distributed generation on network characteristics. However, little research has been done on the effects of this distributed generation on current network protection schemes. An IPP has approached a South African municipality regarding the connection of a wind farm that would be connected to the municipality’s existing grid. This presented a unique opportunity to simulate and study the impact and effect that this wind farm would have on a real-life network in terms of network operation and protection schemes. This also presents the possibility of connecting the wind farm in a different configuration, possibly resulting in better network operation at a lower cost. The network optimisation in this research was done using the probability-based incremental learning (PBIL) and differential evolution (DE) optimisation techniques. These algorithms were programmed and modelled according to the desired IPP wind farm requirements using the MATLAB and MATPOWER simulation packages. The networks used in these algorithms were modelled in the text-based MATPOWER format. This research goes on to study a modified 14-bus IEEE test network in terms of network characteristics and protection performance so that an idea of the performance of the optimisation algorithms can be obtained. Protection data for the IEEE network was not available. The network was thus graded for use in this study. The research then continues to model the existing and proposed network configuration, and proposes various other points of connection to the municipal network using the PBIL and DE algorithms. These studies were conducted using the DIgSILENT PowerFactory simulation package, with the networks and protection data being modelled in this package. Network and protection performance results were recorded for each case in both networks under study. The results show that in the case of the modified IEEE network, the DE algorithm provides a better solution in terms of improving power losses while the PBIL algorithm provides a better solution in terms of improving the voltage profile. In the case of the municipality network, the DE algorithm provides the best performance, with the DE result managing to reduce power losses by 83.89% compared to the current and proposed network configurations. The overall voltage profile was also seen to improve by over 23%. The research also found that the change in fault level for the various cases are minimal. This is due to the limitation in fault current contribution imposed by the use of an inverter system connecting the wind farm to the grid. This means that, as the results shows, network grading is not very much affected by the addition of the wind farm connections. However, it is seen that the municipal network is not optimally graded in the base case. Finally, it is also seen that, though not often used in research, the MATPOWER package works well as a network simulation tool. A costing analysis was also conducted and shows that the DE solution is the most cost-effective solution, in addition to being the best-performing solution. The study recommends that the results produced by the DE algorithm be implemented instead of the proposed implementation. The municipal network should also be regraded and new protection settings should be implemented.

Grantor

Department of Electrical Engineering

Year dc:date.issued

2019

Author dc:creator

• Martin, Mogamat Noer

Advisor dc:contributor.advisor

• Awodele, Kehinde O.

• Wind farm
• economic analysis
• evolutionary algorithm
• optimisation
• municipal network
• distribution

Handle dc:identifier.uri

http://hdl.handle.net/11427/31005

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/31005