Towards the development of high fidelity harmonic models for solar farms: Existing knowledge



Publication Details

S. Korale Liyanage, S. Perera, D. Robinson, D. Muthumuni, H. C. Peiris & M. Vilathgamuwa, "Towards the development of high fidelity harmonic models for solar farms: Existing knowledge," in Australasian Universities Power Engineering Conference, AUPEC 2018, 2019,


2018 IEEE. The unprecedented growth of solar photovoltaic (PV) generation at both small (domestic/commercial) and largescale (farm level) is evident from around the world including Australia. This growth has brought about significant technical challenges that are being addressed progressively by network operators and owners. As an example, the steps being taken to address these issues is evident in Australia with the release of several documents by the Australian Energy Market Operator recently and the Standards Australia. In relation to large solar farms, among the technical issues of concern, power quality is a significant issue of concern. In this regard, the attention paid to harmonics has taken a prominent position in power quality studies associated with the connection of large solar plants. The large inverters in these plants tend to produce both characteristic and uncharacteristic harmonics of low order. These harmonics are seen to arise and/or amplify due to a number of reasons including non-ideal behaviour associated with inverter operation, grid conditions, associated control systems, control interactions and network resonance. The networks to which these plants are connected need to be managed using existing harmonic management techniques and the connection studies require reliable and reasonably robust models of the inverters and the associated networks. It is vital that these models are used with greater understanding so that resulting harmonics can be effectively managed. It is evident that the network connection studies are currently carried out using vendor provided models of inverters. Although these models may be representing worst case behaviours, it is important to develop a deeper understanding of the sensitivity of these models to the various influencing factors. The aim of this paper is to develop this understanding which can be used as a foundation to develop high fidelity solar plant models.

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