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Robust Control Strategies For Optimal Operation Of Distributed Generation In Smart Microgrids
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The high penetration of PV systems and fast communications networks increase the potential for PV inverters to support the stability and performance of smart grids and 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 research 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 optimization of maximizing energy yield from the PV inverters is done by the power flow calculation and an autoregression prediction model for estimating solar and load profiles. The interaction of independent DOC groups in the same network is also considered. The control strategies in this research take into account not only the limit of inverter apparent power capacity but also the limit of commercial power factor range. Overvoltage at the PV buses caused by prediction errors resulting in nonoptimal commands from the DOC is avoided by switching to autonomous droop control (ADC). The DOC and ADC operate at different time-scale for voltage management and to take account of the mismatch between the DOC computing time and the inverter operating time. The research considers not just the balanced 3-phase or single-phase system but also the unbalanced 3-phase network including unbalanced 3-phase distribution lines and the mixture of single-phase and 3-phase connections. The formulas of power flow analysis of unbalanced 3-phase network are rearranged in matrix form for the simulation and optimization calculation. The simulation was carried out using MATLAB/Simulink showing different scenarios of network control. The simulated results have proved the proposed control strategies keep voltage under the required limit and increase the energy yield of the network in both balanced and unbalanced 3-phase networks.
Title: Robust Control Strategies For Optimal Operation Of Distributed Generation In Smart Microgrids
Description:
The high penetration of PV systems and fast communications networks increase the potential for PV inverters to support the stability and performance of smart grids and 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 research 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 optimization of maximizing energy yield from the PV inverters is done by the power flow calculation and an autoregression prediction model for estimating solar and load profiles.
The interaction of independent DOC groups in the same network is also considered.
The control strategies in this research take into account not only the limit of inverter apparent power capacity but also the limit of commercial power factor range.
Overvoltage at the PV buses caused by prediction errors resulting in nonoptimal commands from the DOC is avoided by switching to autonomous droop control (ADC).
The DOC and ADC operate at different time-scale for voltage management and to take account of the mismatch between the DOC computing time and the inverter operating time.
The research considers not just the balanced 3-phase or single-phase system but also the unbalanced 3-phase network including unbalanced 3-phase distribution lines and the mixture of single-phase and 3-phase connections.
The formulas of power flow analysis of unbalanced 3-phase network are rearranged in matrix form for the simulation and optimization calculation.
The simulation was carried out using MATLAB/Simulink showing different scenarios of network control.
The simulated results have proved the proposed control strategies keep voltage under the required limit and increase the energy yield of the network in both balanced and unbalanced 3-phase networks.
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