In my previous blog post, I had described how trying to approximate a differential of Ldi/dt with a linear model is probably impossible. However, there was a flaw in the first linear model that I attempted between the filter capacitor voltage, the grid current and the grid voltage. I had chosen a case where the grid current were always in quadrature to the grid voltage and the filter capacitor voltage has the same template as the grid voltage.

So, to check out if the flaw would result in any improvement, I used a training model where the filter capacitor voltages were different from the grid voltages both by magnitude and by phase. The result was an equally flawed linear model.

vcf = -0.2091*igrid_ref + 1.1028*vgrid

As is evident, this model is even worse that the previous one. Because of the phase angle variation, the model has chosen a larger multiplying factor for the grid voltage of 1.1028 but has tried to compensate with a larger resistance of 0.2091 which is useless in the face of the multiplying factor to the grid voltage.

So, the conclusion is that trying to approximate a differential in this manner by a linear model using linear regression is quite useless. So, I need to step back and figure out what the major challenge with controlling the current through the grid inductor of a LCL filter is.

The transfer function between the inverter and the final grid current is a 3rd order polynomial. Physically, the challenge is in accurately regulating the filter capacitor voltage so as to regulate the grid current to a desired value. The simplest control that can be achieved in this case is controlling the current immediately at the output of the inverter. In that cases, the transfer function between the inverter current and the inverter voltage (or modulation index) is a first order polynomial.

The problem is that inverter output current and the grid current will differ by a current that flows through the filter capacitor. Again, the problem would boil to estimating the current flowing through the filter capacitor. So, to avoid any form of estimation either of current or of voltages, how do we achieve a closed loop control of the final grid current without any synchronous transformation?

The reason why I avoid synchronous transformation is that it transforms the grid current to dc values. This assumes that there are no harmonics are intended to be injected in the grid currents because if the converter is a harmonic filter and is expected to inject harmonics into the grid, the synchronous transformation will have to be performed for every harmonic.

So with these objectives laid out, I will find better ways to control the inverter with advanced concepts of machine learning.

So, to check out if the flaw would result in any improvement, I used a training model where the filter capacitor voltages were different from the grid voltages both by magnitude and by phase. The result was an equally flawed linear model.

vcf = -0.2091*igrid_ref + 1.1028*vgrid

As is evident, this model is even worse that the previous one. Because of the phase angle variation, the model has chosen a larger multiplying factor for the grid voltage of 1.1028 but has tried to compensate with a larger resistance of 0.2091 which is useless in the face of the multiplying factor to the grid voltage.

So, the conclusion is that trying to approximate a differential in this manner by a linear model using linear regression is quite useless. So, I need to step back and figure out what the major challenge with controlling the current through the grid inductor of a LCL filter is.

The transfer function between the inverter and the final grid current is a 3rd order polynomial. Physically, the challenge is in accurately regulating the filter capacitor voltage so as to regulate the grid current to a desired value. The simplest control that can be achieved in this case is controlling the current immediately at the output of the inverter. In that cases, the transfer function between the inverter current and the inverter voltage (or modulation index) is a first order polynomial.

The problem is that inverter output current and the grid current will differ by a current that flows through the filter capacitor. Again, the problem would boil to estimating the current flowing through the filter capacitor. So, to avoid any form of estimation either of current or of voltages, how do we achieve a closed loop control of the final grid current without any synchronous transformation?

The reason why I avoid synchronous transformation is that it transforms the grid current to dc values. This assumes that there are no harmonics are intended to be injected in the grid currents because if the converter is a harmonic filter and is expected to inject harmonics into the grid, the synchronous transformation will have to be performed for every harmonic.

So with these objectives laid out, I will find better ways to control the inverter with advanced concepts of machine learning.