Artificial Intelligent Technique based Double-Frequency Analysis on a Single-Phase Grid-connected Inverter

. Now a days more power losses can be seen in grid connected inverter. In order to reduce that double frequency in single phase grid inverter with Artificial Intelligent based fuzzy control is implemented. The inverter has two operating units High Frequency Unit (HFU) and Low Frequency Unit (LFU), low frequency reduce switching losses and high frequency suppress the symphonious currents. The fuzzy logic method expected towards deliver high yield, low total symphonious distortion, rapid response. Finally Total Symphonious Distortion (THD) contrasted among fuzzy including Integral controls (PI). The results are validated by using MATLAB/Simulink.


Introduction
The DC/AC Converter is always an important part of grid connected system [1]. Many switching symphonious are there in grid side current, to reduce that we will use passive filters like L or LCL filters to the grid [2][3][4]. The L filter has less complex structure, more reliability also have more inductance value and it has high voltage drop so it will reduce the system performance, instead of using L filter, LCL filter can be tried it has good capacity to reduce higher order symphonious [5], but it has the disadvantage of resonance. There are many new developments in semiconductor devices, that are widely used in many applications. These help to reduce the switching symphonious in a good way. Using these semiconductor devices in low and HFUs may add up some cost but the quality of the current will be good. The purpose of using controllers is when a system cannot fulfil the needs, then some variables will be used to achieve the wanted results.
The PLL (Phase Locked Loop) [6][7][8] is a closed loop system will generate an output frequency in relation with Phase and Magnitude of an input frequency it consists of variable oscillator and phase detector and feedback loop, these three are common parts of it. Through this process it will protect the grid from symphonious currents.
For controlling the inverters mostly PI controllers are used but to solve the mathematical model or transfer function will be complex to obtain that problem Fuzzy can be used. We can observe the importance of Fuzzy logic not only in computer science domain but also developing in industrial side [9][10][11], rocket engineering, and many domains. Fuzzy logic is a rule based controller, if any system uses fuzzy logic then it is called fuzzy model. We can observe some important applications of fuzzy in railway system, factories, air conditioner, camera control technique, in hospitals also while checking diagnostic procedure and diagnoses radiology and prostate cancer the machinery is installed with some of these fuzzy logics, washing machine controlling, vacuum cleaner, subway design for trains, it can tell the altitude of plane, range of it as this fuzzy is implemented in aerospace technology, traffic signal [12][13][14]. It has a good problem solving technique in the way its demand is increasing. Its decision making happens on three steps fuzzification, interfacing, and defuzzification. We can use this fuzzy in power electronics applications like controlling the speed of the motor, in electrical vehicles testing, this adds up a benefit to the systems. when compared to PI controllers this will be more beneficial because it thinks like human interface, it is faster and there is no mathematical approach to the fuzzy logic, it will show the results in the [0,1] format either the result produced will be false or true, it does not a give a situation in between them, and a membership graph will be seen with error and change in error it will relate those two graphs with rules that fuzzy had included in it. Fuzzy will simplify the data for itself to provide a valid reason to achieve the desirable output. A double frequency inverter proposed [15][16][17][18][19] will have two inverters used in different frequencies and achieves good performance and results. Here it will deal with two frequencies that are on either side of the grid system, doing two different functions [20][21][22][23]. In this paper the results Total Symphonious Distortion for the proposed converter using PI and Fuzzy Logic control are shown.

Proposed inverter
The inverter shown in Fig. 1 depicts proposed inverter's topography. It has LFU and HFU. These two units will have separate DC voltage of grid, Vdc1 and Vdc2 are low-frequency and high-frequency voltages. The inductances for two units will be La and Lb. The LFU will operate as inverter mode where electric energy goes to power grid. The HFU operates as rectifier mode which will eliminate symphonious currents came from LFU. It has four diodes and thyristors in low and HFUs. Grid voltage is connected across low and HFUs, VINV is the low frequency output voltage and VREC is high frequency output voltage. In low frequency IGBT are present and in high frequency MOSFET are present.

VLa = VINV -Vg
(1) error of SteadyState for current is ignored and ia_f is considered as i * g of the grid current, Therefore, symphonious current 1_h of the LFU can be calculated as ia_h = dt = dt (7) As the switching frequency will be higher in HFU they are ignored, ib can be calculated from the average of VREC in a high switching frequency.

The design of filter inductor
The inductance La value will be obtained from the ratio of VLa_f to the amplitude of Vg is taken as 0.2 La = = (13) Where f1 is the frequency for voltage of grid, Vg is the amplitude for voltage of grid, and IM is the LFU current amplitude. The inductor Lb function is to filter the symphonious at HFU so the capability to reduce the amplitude of a signal at the switching frequency is given below Value of Lb can be calculated by Lb =

Control system of the proposed inverter
From PLL at inverter side voltage Vg has a Phase angle , and the reference current amplitude will be , and ia is compared with the reference current from grid side , from Fig 3. The error signal from the current is i1_e is sent to fuzzy. Grid voltage recompense VCL is equal to Vg /Vdc1 which will reduce the effect of Vg. The adding of VCL and the end current of regulator will be the transition signal M1. The aim of the HFU is to maintain the DC voltage same Vdc2 of the system and produce current ib to discharge the symphonious currents of ia. is known as reference current value and will be solved by phase angle , current amplitude reference . The error of ig and is ig_e and as reference current value of loop. The voltage recompense VCH eliminates the symphonious component ia_h of LFU.
The standard of the LFU drive signal and the theory of single polar transition is shown below (17) The transition signal M2 of the HFU is the sum of VCH and fuzzy output. The HFU works in the rectifier mode. So, the DC capacitor voltage has to be adjusted to produce stabilize sufficient current to reduce the symphonious of the LFU. The expression for voltage of the grid and reference current is shown below Vg(t) = VGM cos( Here ω is the angular frequency of the Vg , θ is the phase difference of the Vg and the . Substituting (18) and (19) into (11), VREC can be calculated as cos( VINV (20) Where Vm = (21) (22) and d of the LFU. If SPWM is used in the LFU then, VREC is a square wave having amplitude Vdc1 , fs1 (frequency), and its polarity also same as Vg .The maximum possible value of VREC(t) will be Vm , Vdc1 and inductor ratio . |VREC_m| has two conditions now, |VREC_m| = (23) As HFU working in the rectifier mode, Vdc2 needs a good and stable design so that it can observe good results and restrict the saturation of the regulator. (24)

Fuzzy Logic Controller
Fuzzy which is an Artificial Intelligent (AI) technique is utilized effectively in different types of control applications. Pretty much every purchaser item has some sort of fluffy control. Controlling the room temperature with a forced air system, hostile to stopping mechanisms in vehicles, traffic signal control, clothes washers, etc are E3S Web of Conferences 309, 01144 (2021) ICMED 2021 https://doi.org/10.1051/e3sconf/202130901144 a few models. We will observe these things in daily life. We can utilize human information and experience to plan a regulator by utilizing fluffy rationale for control. The fuzzy control rules, or IF-THEN standards, are the awesome planning a control framework. Fuzzifier's responsibility is to change the fresh information esteems into fluffy ones. Fuzzy Knowledge the data pretty much every one of the info yield fluffy connections is put away in the base. It additionally indicates the fluffy principal base's information factors and the plant levelled out's yield factors. Fuzzy Rule Base It stores data about the space interaction's movement. Derivation Engine It fills in as the part for any FLC. Basically, it performs rough thinking to display human choices. Defuzzifier is to change over fluffy qualities acquired from the fluffy deduction motor into fresh qualities. PWM-controlled two level generator is used for carrier based two level PWM method where the fuzzy generated output will pass through it and current reference amplitude will be added to that.  Here we compare the Total Symphonious distortion of low and high frequency current using two controllers. As we can see from Fig 5 the THD of low frequency current is 9.67% and grid current is 3.80% measured through Fast Fourier Transform (FFT), It will provide the discrete Fourier in an efficient manner and will get the accurate results based on possible conditions. This type of representation carries information about magnitude and phase at each frequency, in this paper we took the frequency difference as 500Hz. For every frequency we took the magnitude, this magnitude will tell the power of frequency components.

Simulation Results and Discussions
While using PI we got magnitude Fig 5 max of 0.08 between the range (0,100) Hz fir current i1, when fuzzy is used magnitude of 0.03 between the range of (0,100) Hz in Fig 7 so

Conclusions
In this paper the difference of results between using PI controller and Fuzzy logic results are shown through FFT analysis. The main aim of this paper is to reduce the THD of LFU current and grid current and the current symphonious are eliminated by using SPWM technique. Hence Fuzzy logic meet quick reaction including least possible THD, results were analysed through MATLAB Simulink.