Abstract
The high penetration of photovoltaic (PV) systems and fast communications networks increase the potential for PV inverters to support the stability and performance of microgrids. PV inverters in the distribution network can work cooperatively and follow centralized and decentralized control commands to optimize energy production while meeting grid code requirements. However, there are older autonomous inverters that have already been installed and will operate in the same network as smart controllable ones. This paper proposes a decentralized optimal control (DOC) that performs multi-objective optimization for a group of PV inverters in a network of existing residential loads and autonomous inverters. The interaction of independent DOC groups in the same network is considered. The limit of PV inverter power factor is included in the control. The DOC is done by the power flow calculation and an autoregression prediction model for estimating maximum power point and loads. Overvoltage caused by prediction errors resulting in non-optimal commands from the DOC is avoided by switching to autonomous droop control (ADC). The DOC and ADC operate at different time scales to take account of communication delays between PV inverters and decentralized controller. The simulation of different scenarios of network control has proved the effectiveness of the control strategies.
Highlights
Integrating photovoltaic (PV) energy into the low-voltage distribution system increases network voltage stability issues
When all predicted voltage values are under 1.095 pu, the decentralized optimal control (DOC) only commands the PV inverters to run the maximum power point (MPP) with the unity power factor, as seen in block 7b
The reactive power consumption of PV inverters is proportional to the voltage level; in other words, the higher the voltage, the higher the consumption of reactive power
Summary
Integrating photovoltaic (PV) energy into the low-voltage distribution system increases network voltage stability issues. A different time scale of the PV inverter operation time and the controller computing period is proposed to address the effect of a communication delay. In the proposed control method, the PV inverters control both active and reactive power by applying multi-objective optimization and prediction. An autonomous droop control (ADC) and decentralized optimal control (DOC) are designed for the PV inverters to solve all the problems outlined above Both control algorithms are designed to always keep the network voltage under the specified value. The ADC and DOC control strategies perform their control in different time scales to account for communication and computation time delay while ensuring effective voltage management.
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