Improving reliability and efficiency of green energy with SVPWM current control techniques, part 2

Read part one of this article here.

Electrical energy generation is moving toward more environmentally friendly options, and solar and lead the pack. The problem is, these energy sources are transients, making them more susceptible to energy generation loss. In order to make these methods more viable, the efficiency of the energy between direct current () and alternating current (AC) must be improved. To achieve this, new inverter methods have been designed and implemented on both solar and wind plants, especially the neutral-point clamped (NPC) inverter. The NPC is applied to () panels and has several advantages over other methods, but it can be improved in several ways. Increasing its number of levels, implementing more complex control methods, and employing faster power control loops are proving essential in its implementation.

Many control methods can be implemented to operate a NPC inverter system based on multi-level space vector pulse-width modulation (SVPWM), with a general representation of such systems shown in Figure 1. Due to the wide spectrum of control methods, it is critical that the most appropriate technique be applied to a given inverter application.

[Figure 1 | Generalized SVPWM control method for the NPC topology.]

For improved grid parameters in photovoltaic (PV) systems that generate energy and feed it into the grid, three-phase, grid-connected PV inverters are suitable given the need for reactive power control. This control method allows the inverter to control DC power generated by the PV system as well as the transfer of that electrical energy to the grid, and also control active and reactive power in order to reduce losses in reactive regions of the system.

As motor drive control is similar to the control of an inverter, techniques such as those used for AC induction motor drives can also be adapted to PV inverters. In this way, the field-oriented control (FOC) technique – which operates by controlling the frequency, amplitude, and phase of the motor drive – can be adapted to a PV connected to the electric distribution network. This method controls the frequency of generated currents, their amplitude, and phase angle, and this information can then be used to generate SVPWM pulses that control the power inverter. Other advantages of the FOC technique include lower power consumption, higher efficiency, and lower operating and component costs.

Both methods can be combined and implemented on a PV multi-level diode NPC inverter with multi-level SVPWM to maximize a system’s performance. This approach to closed-loop control of a three-phase multi-level diode NPC inverter connected to the electrical grid is best described as follows:

  • First, the SVPWM control method receives the three-phase grid phase voltages and the phase “A” phase angle as inputs.
  • The three-phase voltages are then converted into a two-axis system through an alpha-beta-zero transformation.
  • Using the measured phase angle in a d-q-0 transformation, the two-axis coordinate system is rotated and aligned with the angle information.
  • The closed-loop inverter control method also uses the generated three-phase currents and applies the alpha-beta-zero and d-q-0 transformations, using the reference angle information to transform them.
  • After both the generated and reference signals are transformed, error signals are produced by subtracting one signal from the other. In order to improve the system’s stability, the error signals must go through classic proportional-integral (PI) control loops.
  • At this point, the system transforms the synchronous reference frame (the d-q-0) error signal generated by the PI controller using the stationary reference frame (the alpha-beta-zero frame). This step predicts the amount of error generated between the present voltage vector and the next voltage vector.
  • The two past steps eliminate or control the quadrature voltage (the q component) from the d-q-0 transformation, which represents the reactive power of a system.
  • Then, the alpha and beta components from the alpha-beta-zero transform go through a Cartesian to Polar coordinate transformation, yielding the magnitude and angle.
  • Finally, using the magnitude and angle information, the SVPWM calculates the reference vector, the region and sector in which this vector is located, the voltage vectors that comprise that area, the dwelling time for the switches, and lastly, the optimal switching sequence for the inverter. These are transmitted as pulses that drive the converter, generating the desired voltage and current values in the system.

A phase-locked loop (PLL) can be implemented to extract angle information from the phase “A” phase angle to perform the coordinate transformation, making the system adaptable to frequency variations in the input signals.

Control method implementation with positive-sequence voltage detector

In addition to the aforementioned adaptive frequency control method, a positive-sequence voltage detector (PSD) connected to the grid can be used to further improve system design (Figure 2). This additional measure can be used to detect further grid fault conditions (such as unbalanced and distorted grid circumstances) and to adapt a system to them, thus reducing power loss and improving the system’s efficiency. It is fundamental to control the power exchange between the inverter and the grid without tripping the converter’s protections in order to facilitate ride-through of transient faults and keep the system running according to the grid connection standards.

[Figure 2 | Complete control method for multi-level diode NPC and SVPWM implemented with PSD.]

With the purpose of achieving fast and precise detection of unbalanced, distorted, or unstable grid conditions, it is also necessary to add two other blocks to the architecture of a system that includes a PSD. These are a quadrature-signal generator (QSG) implemented with a second-order generalized integrator (SOGI) that brings harmonic blocking capability to the system, as well as a positive-sequence calculator (PSC). The system described is usually implemented in conjunction with a PLL, however, as a PLL is already in use in the d-q-0 transformation, another PLL is not be required and information of the existing PLL in the system can be used. In this way, the three-phase grid voltages on the alpha-beta reference frames can be filtered by the QSG, rendering components shifted 90 degrees from the original alpha-beta voltages. These signals are then run through the PSC, which uses instantaneous symmetrical components to successfully detect positive-sequence components on the alpha-beta-zero voltages. At length, the transformed positive-sequence components go through a d-q-0 transformation, which uses PLL angle information employed in the previous iteration to maintain the system frequency and phase adaptation, generating the d-q-0 components.

After completing the entire process of acquiring and transforming positive-sequence components from the grid’s voltage, the system continues as described before. These components are subtracted from the generated currents and run through the PI control loop following the method described previously, and, therefore, although the system still performs the same control method steps, it also now has an adaptive reaction to unbalanced and distorted grid conditions.

Simulation in the Simulink environment

The system can be successfully simulated in MathWorks’ Simulink environment. The full system comprises a grid-connected multi-level diode NPC inverter topology controlled by a multi-level SVPWM technique and closed-loop reactive power control method, adapted into an FOC technique and implemented with a PSD.

Simulink simulation shows that the system presented stability in the case of large grid impedance variations, ride-through grid voltage disturbances, adaptation to grid voltage variations, and operation at the unity power factor as required by standards. While designing the system, some additional parameters, such as switching frequency, distortion, losses, harmonic generation, and speed of response were heavily considered when selecting a modulation strategy.

Figures 3 through 5 demonstrate the performance of the system. In the simulation, the grid begins as fully functional while the system has to be turned on at 0.0 seconds. When the simulation reaches 0.06 seconds, which represents three full periods of grid voltage (indicating that the system is already stable), there are drops in each grid voltage that last for 0.04 seconds, returning to normal after 0.1 seconds of simulation.

The results without a PSD demonstrate good performance before grid failure, however the grid failure represents a big voltage drop in the system and subsequently unbalanced generated currents. Figure 5, with the PSD, takes roughly one period (0.02 seconds) to stabilize, but adapts better to faulty grid conditions than the system without a PSD and demonstrates fully balanced generated currents. When the system with the PSD reaches 0.18 seconds it is turned off so that the middle switches of the diode NPC open and interrupt any current generation with the exception of a brief period where capacitors and inductors are discharged.

[Figure 3 | Three-phase grid voltages.]

[Figure 4 | Three-phase five-level generated currents without PSD implementation.]

[Figure 5 | Three-phase five-level generated currents with PSD implementation.]

The SVPWM pulses that are modulating the inverter’s phase “A” are presented in Figure 6, with the NPC switches running at 100 kHz. The switching frequency of the NPC can be easily selected, and the system operates satisfactorily at a very wide range of frequency values, from 20 kHz to 300 kHz.

[Figure 6 | Five-level phase “A” switching pulses.]

The results show that the system has several advantages over other methods and can be implemented in several ways, such as increasing its number of levels, implementing grid fault adaptive systems, more complex control methods, and employing faster power control loops, thus rendering more efficient, less expensive, smaller, and more intelligent systems for green energy production in the modern world.

Martin Murnane is a member of the Solar PV Team at in Limerick, Ireland. Prior to joining ADI, he worked in several roles involving application development in energy recycling systems (Schaffner Systems), Windows-based application software/database development (Dell Computers), and product development using strain gage technology (BMS). He holds an electronic engineering degree and an M.B.A. from the University of Limerick.

Igor Esdras Silva Ono is currently working toward his B.E. in electrical engineering at the Federal University of Mato Grosso do Sul (UFMS) in Brazil. In 2015, he was granted a 14-month scholarship to attend an electronic engineering course at Trinity College Dublin (TCD). During this time, Igor worked at Analog Devices as a PV inverter systems cooperative engineer in the Energy Business Unit.

Analog Devices





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