Optimization and Implementation of the Proportional-Resonant Controller for Grid-Connected Inverter With Significant Computation Delay

Husev, Oleksandr; Roncero‐Clemente, Carlos; Makovenko, Elena; Pimentel, Sérgio Pires; Vinnikov, Dmitri; Martins, João

doi:10.1109/tie.2019.2898616

Cited by 84 publications

(41 citation statements)

References 31 publications

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“…Finally, the current controller compares reference and measured values of the converter output current and it obtains the modulating signal for the converter switching by means of another PR controller with k P-PR = 20 and k R-PR = 2000. The voltage and the current PR controller coefficients were both tuned by means of the guidelines provided in [30]. Figure 3 depicts these control loops, where u ci is the measured voltage signal in the filter capacitor of the ith converter and i L1 is the current in the inverter-side reactance of the LCL filter.…”

Section: Power Converter Inner Voltage and Current Control Loopsmentioning

confidence: 99%

Secondary Control for Storage Power Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing

et al. 2020

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It is usual in literature that power sharing among grid-forming sources of an isolated microgrid obeys their energy rating, instead of economic agreements between stakeholders, and circulating energy among them is usually avoided. However, these energy interchanges make strong sense and classical power sharing methods must be reformulated in the context of prosumer-based microgrids. This paper proposes a secondary control method for a prosumer-based low-voltage nanogrid that allows for energy interchange between prosumers, where storage systems, together with PV generators, are the controllable grid-forming sources. A power flow technique adapted to islanded microgrids is used for secondary control algorithm and the whole hierarchical control strategy for the prosumer converter is simulated and validated. This hierarchical control consists of three stages: tertiary control plans the energy interchange among prosumers, secondary obtains different voltage and power setpoints for each of the grid-forming sources, and, finally, primary control guarantees stable voltage and frequency values within the nanogrid with droop rules. Inner control loops for the power converter are also defined to track setpoints and assure stable performance. Simulation tests are carried out, which prove the stability of the proposed methods and the accuracy of the setpoint tracking.

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Section: Power Converter Inner Voltage and Current Control Loopsmentioning

confidence: 99%

Secondary Control for Storage Power Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing

et al. 2020

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“…The modulation signal enabled the switching signals for the gates in the DC/AC converter by means of a sinusoidal pulse width modulation (SPWM) technique. In this figure, i out is the measured output current, and k P and k R (20 and 2000 are the respective values, tuning guidelines for PR controllers can be found in [34]) are the controller constants.…”

Section: Simulation Of the Nanogridmentioning

confidence: 99%

“…In this figure, iout is the measured output current, and kP and kR (20 and 2000 are the respective values, tuning guidelines for PR controllers can be found in [34]) are the controller constants.…”

Section: Simulation Of the Nanogridmentioning

confidence: 99%

Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting

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Energy efficiency and consumers’ role in the energy system are among the strategic research topics in power systems these days. Smart grids (SG) and, specifically, microgrids, are key tools for these purposes. This paper presents a three-stage strategy for energy management in a prosumer nanogrid. Firstly, energy monitoring is performed and time-space compression is applied as a tool for forecasting energy resources and power quality (PQ) indices; secondly, demand is managed, taking advantage of smart appliances (SA) to reduce the electricity bill; finally, energy storage systems (ESS) are also managed to better match the forecasted generation of each prosumer. Results show how these strategies can be coordinated to contribute to energy management in the prosumer nanogrid. A simulation test is included, which proves how effectively the prosumers’ power converters track the power setpoints obtained from the proposed strategy.

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“…Hysteresis [19], predictive [20,21] and dead beat controller [22][23][24] types belong to the first controller's group, presenting high robustness and fast dynamic response. On the other hand, linear current controllers such as proportional-integral (PI) based, PR based or repetitive controller based have been successfully used [25][26][27][28]. The PR controller, first proposed in [26], is quite a simple and attractive solution in the case of abc-naturally or αβ-stationary reference implementation frames because it can overcome two well-known drawbacks of the conventional PI controller: Inability to track a sinusoidal reference with zero steady-state error and poor disturbance rejection capability.…”

Section: Voltage Source Operation Of the Output Invertermentioning

confidence: 99%

Voltage Source Operation of the Energy-Router Based on Model Predictive Control

et al. 2019

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The energy router (ER) is regarded as a key component of microgrids. It is a converter that interfaces the microgrid(s) with the utility grid. The energy router has a multiport structure and bidirectional energy flow control. The energy router concept can be implemented in nearly zero energy buildings (NZEB) to provide flexible energy management. We propose a concept where ER is working as a single grid-forming converter with a predefined voltage reference. The biggest challenge is to maintain regulated voltage and frequency inside the NZEB in the idle operation mode, where traditional regulators, e.g., proportional-resonant (PR), proportional-integral-derivative (PID), will not meet the control design requirements and could have unstable behavior. To gain the stability of the system, we propose model predictive control (MPC). The design of the MPC algorithm is explained. A simulation software for power electronics (PLECS) is used to simulate the proposed algorithm. Finally, the simulation results are verified on an experimental prototype.

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Optimization and Implementation of the Proportional-Resonant Controller for Grid-Connected Inverter With Significant Computation Delay

Cited by 84 publications

References 31 publications

Secondary Control for Storage Power Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing

Secondary Control for Storage Power Converters in Isolated Nanogrids to Allow Peer-to-Peer Power Sharing

Demand and Storage Management in a Prosumer Nanogrid Based on Energy Forecasting

Voltage Source Operation of the Energy-Router Based on Model Predictive Control

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