Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

Power Quality Improvement for Grid-Connected Photovoltaic Panels Using Direct Power Control

This chapter displays a control strategy for a photovoltaic system (PV) linked to the network with two phases of a PWM converter, where the first phase is a DC-DC converter linked among the photovoltaic source and the DC-AC converter. The second phase is a DC-AC converter linked to the grid. The maximum power point (MPP) is tracked by DC-DC converter, which increases the DC bus voltage. The P&O (perturbation and observation) technique is utilized as a direct current (DC-DC) converter controller to make the PV arrays work at greatest value of power under changing weather conditions. The DC-AC converter transfers the maximum power extracted from the PV cell into the grid. To improve the energy quality produced by the photovoltaic field other than the performance of the pulse width modulation (PWM) inverter, direct power control (DPC) is used to achieve these improvements. The simulation results showed a good performance of the suggested controller. Decoupled power control is achieved successfully, and a good power quality with low harmonic distortion rate (THD) is obtained.

Module trainer of photovoltaic integrated low voltage grid (PV-LV grid) with a variety load

This research is a simulation of the penetration of renewable energy at the primary source. The entire system is a compound system, especially on the load. Load types provide different voltage and current treatment. The simulation is carried out with a mini-grid device consisting of five buses with interface sensors to monitor voltage and current. Photovoltaic grid module (PV)-LV as a trainer, uses two power sources to supply the load to the voltage distribution network module. The loading scenario h two plans, where the difference lies in the type of inductive load (scenario A) and capacitive (scenario B). The types of load consist of incandescent lamps, fluorescent lamps, energy-saving lamps, drilling machines, and soldering tools. Variations in this load to meet predetermined loading scenarios. The PV measurement results show maximum power generation at noon and flowed to the load trainer via a 300W grid-tie inverter of 191.1W. The average load bus voltage increases for scenario A and scenario B by 1.045% and 1.36%, respectively. The result indicates that the integration of PV in low voltage systems positively impacts the voltage profile for both inductive and capacitive loads. The amount of voltage improvement depends on the value of the active power injection of the PV and the load supplied by the system.

Research on Voltage Stabilizing Control Strategy of Critical Load in Unplanned Island Based on Electric Spring

Aiming to solve the problem of voltage fluctuation of critical load caused by lack of control when an unplanned island occurs in a microgrid, a voltage stabilizing control strategy of critical load based on electric spring is proposed in this paper. When unplanned islanding occurs in a microgrid system, the system bus voltage fluctuates dramatically due to instantaneous power imbalance, compromising the power supply safety of important loads on the bus. In this paper, the electric spring control mode is integrated into the voltage stabilizing control strategy of critical loads in an unplanned island for the first time to realize the protection of critical loads. First of all, a model of an optical storage AC/DC hybrid microgrid is built, the overall system architecture is determined, and the microgrid is divided into four working states. Second, the working principle of electric spring is introduced, and a decoupling control strategy based on double closed loop is proposed. Finally, the experimental simulation of the proposed control strategy is experimentally simulated in Matlab/Simulink environment. The simulation findings show that when the bus voltage and current of microgrid change due to an unplanned island, the proposed control strategy based on electric spring may achieve the stability of voltage and current on critical loads.

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

Online Adaptation of Two-Parameter Inverter Model in Sensorless Motor Drives

<div>This paper designs parameter adaptation algorithms for online simultaneous identification of a two-parameter sigmoid inverter model for compensating inverter nonlinearity to reduce the voltage error in flux estimation for a position sensorless motor drive. The inverter model has two parameters, a2 and a3, where a2 is “plateau voltage”, and a3 is a shape parameter that mainly accounts for the stray capacitor effect. Parameter a3 is identified by the (6k ± 1)-th order harmonics in measured current. Parameter a2 is identified by the amplitude mismatch of the estimated active flux. It is found that the classic linear flux estimator, i.e., the hybrid of voltage model and current model, cannot be used for a2 identification. This paper proposes to use a saturation function based nonlinear flux estimator to build an effective indicator for a2 error. The coupled identifiability of the two parameters is revealed and analyzed, which was not seen in literature. The concept of the low current region where the two-way coupling between a2 and a3 occurs is established. In theory, it is suggested to stop the inverter identification in the low current region. However, the experimental results in which dc bus voltage variation and load change are imposed, have shown the effectiveness of the proposed online inverter identification and compensation method, even in low current region.</div>

Input-Series-Output-Parallel DC Transformer Impedance Modeling and Phase Reshaping for Rapid Stabilization of MVDC Distribution Systems

This paper focuses on the instability problem of the medium-voltage DC (MVDC) distribution system and proposes an impedance phase reshaping (IPR) method. To obtain the load impedance model of the MVDC distribution system, the input impedance of the input-series-output-parallel (ISOP) DC transformer (DCT) is derived by the generalized average modeling (GAM). Based on the obtained model, the traditional ISOP DCT controller optimization (IDCO) approach is discussed and the IPR method is developed. An impedance phase controller is introduced based on the original control method. According to the optimized impedance stability criterion, the parameters of the impedance phase controller are determined. Compared with the IDCO approach, the proposed method weakens the negative resistance characteristic of the load impedance at the resonant frequency. Therefore, the MV bus voltage oscillation is rapidly mitigated. Besides, the dynamic performance of the system using the IPR method can be classified as good. The simulation results show that the mathematical model is correct, and the proposed method is effective for the rapid stabilization of MVDC distribution systems.