Degree Name

Doctor of Philosophy


School of Electrical, Computer and Telecommunications Engineering


There is already strong evidence that rooftop solar photovoltaic (PV) units at low voltage (LV) distribution networks are creating major impacts on the operation of the electricity networks, both at the low and medium voltage (MV) levels. With the proliferation of solar PV penetration, LV distribution grids are experiencing the issues of reverse power flow and voltage rise. As a result, the hosting capacities of many distribution feeders are already close to their maximum limit. This prompts many utilities to impose a barrier to the installation of new solar PV units at the LV distribution level and to reduce the PV size allocated for household. In addition, fluctuations in PV power output due to passing clouds can result in significant voltage fluctuation, especially in weak distribution grids. With an unbalanced allocation of single phase PV units, 4-wire LV distribution networks can experience an increase of neutral current and therefore the neutral potential (or neutral-to-ground voltage) can exceed the acceptable limit.

In the context of the problems outlined above, an accurate assessment of the impact of solar PV on distribution networks is becoming necessary so that effective mitigation actions can be taken, and the PV penetration level can be increased. With such a background, this thesis aims at: developing a comprehensive and realistic assessment approach for the impact of solar PV on distribution networks, analysing the impact using the developed approach in real network environment with smart grid measurements, and proposing mitigation strategies for the particular problems identified above.

First, this thesis has developed a comprehensive modelling and analysis approach for integrated medium voltage (MV) and multigrounded low voltage (LV) distribution networks for an accurate assessment of solar PV impact. Using this approach, PV integrated networks can be modelled by retaining their wiring configurations, such as 3- wire configurations for MV networks and 4-wire configurations for LV networks, including the delta-wye transformers and neutral grounding impedances in the LV networks. The three-phase modelling capabilities cater for load and network unbalances and asymmetries. A voltage dependent load modelling approach has been adopted. Capabilities have been incorporated to model solar PV resources based on PV panel I-V characteristics using PV panel parameters, inverter efficiency, irradiance and ambient temperature data. With such a detailed modelling capability, this approach is able to provide an accurate assessment of solar PV impact on the LV and upstream MV networks compared to other methods where such details are not considered.

An intelligent approach has been developed to analyse solar PV impact with a proposed power flow approach using smart grid measurements in a computationally efficient manner. A time series approximation technique in combination with datamining techniques has been proposed for extraction of the dataset that is more effective for PV impact analysis from a large volume of smart-grid measurements.

An on-line approach has been proposed to assess the PV impact using real-time models of distribution networks constructed using on-line network data so that a more accurate analysis of the impact could be performed under the varying load and network conditions. In addition, a dynamic type “what-if” analysis feature has been proposed to investigate the network behaviour in a potential PV generation scenario and also to understand the effectiveness of a prospective mitigation action.

This thesis has proposed new mitigation strategies against the particular PV impacts identified.

A versatile reactive power control strategy has been proposed in this thesis that is suitable to provide appropriate network support under various conditions associated with PV power generation. In addition to a dynamic reactive power compensation for voltage support during low or no PV period, the proposed strategy is able to mitigate voltage rise during excess PV generation period using a reverse power flow based droop characteristic, and to provide a fast and appropriate reactive power support using a ramp-rate based approach for voltage fluctuation mitigation during cloud passing.

To effectively utilise limited capacities of energy storage devices for PV impact mitigation and evening peak load support, a new charging/discharging control strategy has been developed in this thesis. Unlike the traditional constant rate strategy, the proposed strategy can control the shape of the charging/discharging profile to ensure an effective use of the storage capacity. The charging rate is also adjusted dynamically to consider the effect of unstable weather conditions to ensure that the available capacity is exploited wisely.

This thesis has proposed a new strategy where the PV inverter ramp-rate can be controlled to a desired level by deploying energy storage. Traditionally, energy storage devices are used to smooth PV output fluctuations using moving average control. However, moving average does not control the ramp-rate directly; rather the ramp-rate depends on previous values of the PV output. According to the proposed strategy, the desired ramp-rate during the ramping event is governed by controlling the energy storage based on an inverse relationship with the PV panel output ramp-rate to improve the fluctuation mitigation performance. In contrast to the moving average method, the proposed strategy is able to control the desired ramp-rate, independent of the past history of the PV panel output, and therefore a storage device is operated for a comparatively small amount of time.

Finally, in the context of exacerbated neutral current and neutral potential problems under a high penetration of single phase PV systems allocated in an unbalanced pattern, and the limitations of the traditional mitigation strategies against these impacts, this thesis has proposed new mitigation strategies using energy storage. Distributed storage connected to each PV system, and a central community storage system for the whole feeder, both have been considered as potential strategies. A power balancing algorithm has been developed to balance the net power exchange with the grid utilising the minimum amount of storage power. A control strategy has been developed based on the balancing algorithm to control the energy storage devices to provide an appropriate balancing effect under varying load and PV unbalance.