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Smart Inverters For Distributed Pv Network Management
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Securing a sustainable decarbonised economy involves moving towards a decentralised power system with increasing penetration levels of distributed photovoltaics (PVs) within the low voltage distribution network (LVDN). Increasing penetration levels of PV systems pose challenges for maintaining grid voltage and frequency stability. Thus requires studies and simulations to estimate the needs and technical requirements to overcome the challenges and maximise the opportunities. These simulations require time-domain system models with a high dynamic resolution such as electromagnetic transient (EMT) simulations with small-time steps that capture the required performance with large numbers of network elements. However, the small-time step implies a high computational burden that results in long simulation times. In order to address the computational burden associated with investigating the dynamic interactions between PV systems and the network, this research creates a linearised state-space (LSS) model suitable for MPP operation. The LSS model includes both the DC/DC, DC/AC converters and controllers, parasitic components, system losses, and an efficient PV array model. The LSS model is expanded for off maximum power point (MPP) modelling by creating a linear parameter varying (LPV) model, which is a combination of multiple LSS models linearised at various operating points. The LPV model enables frequency support studies with active power curtailment. In addition, the LPV model can investigate voltage rise due to the possibility of reverse active power when providing frequency support. The EMT, LSS and LPV models are validated with measured experimental data for dynamic response and steady-state operating points at various irradiation levels. The developed models are implemented on a 20 bus radial European benchmark LVDN with high penetrations of PV. The results demonstrate a computational burden reduction of 132:1 for the LSS and LPV models compared to the EMT model, for frequency support analysis without loss of accuracy. In order to increase the hosting capacity of the LVDN, a hierarchical optimisation strategy is proposed to control PV system outputs in a coordinated manner. The proposed strategy is based on a decentralised iii control architecture where full network information is known. The decentralised power dispatch controller (DCPDC) seeks an optimal power flow solution that maximises active power generation and minimises reactive power consumption without exceeding local voltage limits. Comparison studies over 24 hours with measured irradiance data and a resolution of 5 minutes are performed using phasor analysis with the decentralised power dispatch controller and an overvoltage controller (OVC) that disconnects any PV system where the voltage exceeds the voltage threshold. The DCPDC generates 43.1 % more active power than OVC. Network simulations using the developed full EMT, LSS, LPV and phasor models demonstrate that the developed models provide more system information than phasor analysis by including time domain transients.
Title: Smart Inverters For Distributed Pv Network Management
Description:
Securing a sustainable decarbonised economy involves moving towards a decentralised power system with increasing penetration levels of distributed photovoltaics (PVs) within the low voltage distribution network (LVDN).
Increasing penetration levels of PV systems pose challenges for maintaining grid voltage and frequency stability.
Thus requires studies and simulations to estimate the needs and technical requirements to overcome the challenges and maximise the opportunities.
These simulations require time-domain system models with a high dynamic resolution such as electromagnetic transient (EMT) simulations with small-time steps that capture the required performance with large numbers of network elements.
However, the small-time step implies a high computational burden that results in long simulation times.
In order to address the computational burden associated with investigating the dynamic interactions between PV systems and the network, this research creates a linearised state-space (LSS) model suitable for MPP operation.
The LSS model includes both the DC/DC, DC/AC converters and controllers, parasitic components, system losses, and an efficient PV array model.
The LSS model is expanded for off maximum power point (MPP) modelling by creating a linear parameter varying (LPV) model, which is a combination of multiple LSS models linearised at various operating points.
The LPV model enables frequency support studies with active power curtailment.
In addition, the LPV model can investigate voltage rise due to the possibility of reverse active power when providing frequency support.
The EMT, LSS and LPV models are validated with measured experimental data for dynamic response and steady-state operating points at various irradiation levels.
The developed models are implemented on a 20 bus radial European benchmark LVDN with high penetrations of PV.
The results demonstrate a computational burden reduction of 132:1 for the LSS and LPV models compared to the EMT model, for frequency support analysis without loss of accuracy.
In order to increase the hosting capacity of the LVDN, a hierarchical optimisation strategy is proposed to control PV system outputs in a coordinated manner.
The proposed strategy is based on a decentralised iii control architecture where full network information is known.
The decentralised power dispatch controller (DCPDC) seeks an optimal power flow solution that maximises active power generation and minimises reactive power consumption without exceeding local voltage limits.
Comparison studies over 24 hours with measured irradiance data and a resolution of 5 minutes are performed using phasor analysis with the decentralised power dispatch controller and an overvoltage controller (OVC) that disconnects any PV system where the voltage exceeds the voltage threshold.
The DCPDC generates 43.
1 % more active power than OVC.
Network simulations using the developed full EMT, LSS, LPV and phasor models demonstrate that the developed models provide more system information than phasor analysis by including time domain transients.
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