Grid connected PV system analysis and performance for the sliding mode control

Abstract

For a grid-connected photovoltaic (PV) system based on cascaded two-level inverters, a new sliding-mode (SM) controller is introduced (CTLI). Through modelling and design, a grid-connected photovoltaic system based on CTLI was created that uses solar radiation to generate both active and reactive electricity. When developing a vector controller, consideration is given to the PV's capacity to provide its maximum power. When constructing SM controllers for similar operating conditions, two distinct switching processes were examined and taken into account. The proposed SM controller operates using a simple PWM modulation technique in place of the previously mentioned space vector pulse width modulation (PWM) method. Adaptive hysteresis band calculation is used to improve the SM controller's efficiency. The controller's performance is rated as excellent for both systems operating in the simulated scenario with the specified load and different levels of isolation.

Specification

Description:Abstract
For a grid-connected photovoltaic (PV) system based on cascaded two-level inverters, a new sliding-mode (SM) controller is introduced (CTLI). Through modelling and design, a grid-connected photovoltaic system based on CTLI was created that uses solar radiation to generate both active and reactive electricity. When developing a vector controller, consideration is given to the PV's capacity to provide its maximum power. When constructing SM controllers for similar operating conditions, two distinct switching processes were examined and taken into account. The proposed SM controller operates using a simple PWM modulation technique in place of the previously mentioned space vector pulse width modulation (PWM) method. Adaptive hysteresis band calculation is used to improve the SM controller's efficiency. The controller's performance is rated as excellent for both systems operating in the simulated scenario with the specified load and different levels of isolation.

INTRODUCTION
Globally, solar photovoltaic (SPV) systems are growing in popularity as a dependable and affordable method of producing electricity. The capacity of SPV systems to generate clean energy from renewable resources without the need for fuel other than enough sunshine is one of their main advantages. The SPV systems can generate proportionate amounts of electrical power based on the amount of solar radiation or its intensity. They don't require as much run-time monitoring as other power-producing systems. The amount of electricity generated by the SPV power conversion system is determined by the ambient temperature and solar irradiation, both of which are influenced by the environment.

The two environmental factors alter the internal characteristics of the SPV system and have a major effect on its aspects. A maximum power point tracking (MPPT) system is therefore required. Since the goal of the proposed endeavor is to improve the power quality of the system, THD, loss reduction, and PWM techniques are given priority. The Standard test conditions (STC), which are 25 °C and 1000W/m2 of radiation, are used for all investigations. Whei-Min Lin et al. used the MPPT technique to ensure that the maximum amount of electricity was collected for the given solar irradiation and temperature. Among the most popular MPPT techniques are Sliding Mode Controller (SMC), Learned Incremental Conductance (LIC), Incremental Conductance (INC), and Perturb and Observe (P&O). Reddy, K. Jyotheeswara, and associates There are more MPPT strategies that rely on soft computing. The SPV-based electrical power generating technology produces dc output, however the majority of applications require ac. An inverter must be used in conjunction with the SPV system to provide an ac voltage or current source with the appropriate amplitude, phase, and frequency.
Two different SPV system configurations are available: one with and without a battery backup. Standalone systems that require continuous power sources employ battery backup. Systems that incorporate collected electricity into the grid do not require backup measures. Mahfuz-Ur-Rahman, A. M., et al (2020), Depending on the situation, grid integrated systems usually inject electricity into the grid using a variable current method against a fixed voltage ac bus bar. Grid integration is possible for single-phase or three-phase systems. Transformers are placed between the integrating ac bus bar and the generated ac voltage source in order to attain the necessary voltage levels.

When the source side voltage level is high enough in relation to the integrating bus bar, transformer-less systems are also used. , Abdeslem Sahli and associates The main issues with solar power generation are the MPPT system, power conversion efficiency, and power quality. These three important aspects have been the subject of countless research projects, and various approaches to solving the problem have been put forth. Among the numerous research topics are topological variations, different PWM approaches, and different control schemes.
Lahab, Abderezak, and others , Research on topological variants specifically addresses issues such as augmentable modular switching units, isolated DC sources derived from a single renewable energy source for cascaded multi-level inverters, and similar problems for modular multi-level inverters. Some of the PWM systems that have been thoroughly studied include the various multicarrier sinusoidal PWM schemes, the space vector PWM schemes, and the step modulation schemes with selective harmonic removal. The control subsystems further regulate the management of the entire operation, from the gathering of renewable energy sources through the various phases of power conversion until the electricity is ultimately integrated into the grid.


Claims
1.Superior Performance of CTLI-based SM Controller: The CTLI-based Sliding Mode (SM) controller significantly outperforms other SMC control strategies (Schemes I and II) in terms of grid-tied device control, ensuring reliable active and reactive power separation under varying conditions, such as fluctuating solar radiation and load increases.
2.Effective Power Generation and Voltage Regulation: The proposed SM controller maintains optimal DC link voltage for both control schemes, thus enhancing the power production of solar PV modules, even in the presence of changing solar irradiance and varying inverter input power, as well as load fluctuations.



SYSTEM CONFIGURATION
"SYSTEM MATHEMATICAL MODELING."
The PV cells' characteristic equation is provided by

I =I_ph-I_s [〖e 〗^q((V+IR_s)/nkT ) -1]-(V+IR_(s ))/R_sh - (1)
The simulation model in FIG (1) uses the one from FIG 2. The values of the parameters are 323 and 0.4, respectively. By joining M single PV strings in parallel, a PV array of (M N) PV modules can be created. A multidimensional array model's general equation is provided.



I=N_p [I_ph-I_s (e^(q((V/N_s )+(1/N_p ) R_s )/KT)-1)-((V/N_s )+(1/N_p ) R_s)/R_sh ] - (2)

Under normal solar radiation circumstances in India, the maximum number of cells connected in parallel to form a series and the maximum number of cells linked in series to make a set are both found to be 48V. The estimated power rating of the inverter is 2.5 kW. The available output power at various output voltages is shown in Fig. 2
In this case, the continual exposure to sunlight maintains the constant maximum output power of 48V. As shown in Fig. 1, the regulators are designed to keep the combined PV output voltage of the two inverters at 96V in order to maximize system efficiency.
ModelCTLI For the power system in question, the voltage across the a, b, and c windings is as follows:

e_a =2/3 (e_a1-e_a2 )-1/3 (e_b1-e_b2 )-1/3 (e_c1-e_c2 ) - ( 3)

e_(b = -1/3) (e_a1-e_a2 )+ 2/3 (e_b1 -e_b2 ) -1/3 (e_c1 -e_c2 ) - ( 4)


e_c = -1/3 (e_a1 -e_a2 )-1/3 (e_b1 -e_b2 )+2/3 (e_c1 -e_c2 ) - (5)

In this case, ea1, eb1, and ec1 are the first inverter pole voltages, and ea2, eb2, and ec2 are the second. The output voltage of CTLI for idealized power switches can be represented in matrix form using (3)-(5).


[■(e_a@e_b@e_c )] = 1/3 [■(2&-1&-1@-1&2&-1@-1&-1&2)] [■(e_a1@e_b1@e_c1 )]-1/3 [■(2&-1&-1@-2&2&-1@-1&-1&2)] [■(e_a2@e_b2@e_c2 )] - ( 6)

In both the gripping and gliding phases, the SMC design ought to function well . The control rule listed below defines a button, also referred to as the switching function sij: The following is how to obtain the six switching functions, ij, I 1, 2, and j 1, 2, 3:

γ_ij={ █(1, &if S_ij is ON S ̅_(ij is OFF) @@0 ,if S_(IJ is OFFS ̅_(ij is ON) ) )┤ - (7)

The three-phase output voltages of the CTLI were so connected.
Vector control A two-axis representation of the supply voltages could be made as
[■(v_α@v_β )] =2/3 [■(1&-1/2&-1/2@0&-√3/2&√3/2)][■(v_a@v_b@v_c )] - ( 8)

Consequently, (10) can be written as

[■(v_α@v_β )]=2/3 [■(1&(-1)/2&(-1)/2@0&-√3/2&-√3/2)][■(γ_1a@γ_1γ )] V_dc1 -2/3 [■(1&(-1)/2&(-1)/2@0&(-√3)/2&√3/2)][■(γ_2a@γ_2γ )] V_dc2 - ( 9 )
Vdc1 = Vdc2 = 48 V in this case. The direct axis (d-axis) and the quadrature axis (q-axis) of the employed vector control are calculated following Fig. 4, and found as:".


[■(V_d@V_q )] =[■(sin⁡ωt&cos⁡ωt@cos⁡ωt&〖-sin〗⁡ωt )][■(〖V_m sin〗⁡ωt@V_m sin⁡ωt )] - ( 10)

FIG shows a circuit that is equivalent to a phase. Va stands for the mains voltage, R for the loss resistance, L for the transformer winding's leakage inductance, and n for the transformer's primary voltage (ea1 ea2). The turns ratio of a step-up transformer is 1:1. Phases A, B, and C of KVL implementation.

n(e_a1 -e_a2 )=R_a i_a+L_a 〖di〗_a/dt +V_a - (11)
n(e_b1 -e_b2 )=R_b i_b +L_b 〖di〗_b/dt+V_b -( 12)
n(e_c1 -e_c2 )=R_c i_c+L_C 〖di〗_c/dt+V_c - (13)


The intermediate circuit voltage controller creates the set point for the d-axis current. The reference value for both DC voltages in this investigation is maintained at 96 V.
Sliding-Mode Control
The SMC's continuous state feedback control rule can rapidly transition between continuous structures based on the status of the state variables in the state space. To carry out the desired and planned actions, the system's dynamics must be controlled. SMC is distinguished in particular by the following salient characteristics: Adapting the on/off behaviour of circuit breakers, reducing system order, and being resilient are all crucial. One of the most important features of the SM regime in VSS is the ability to change responses regardless of system properties. It is possible to perform basic SM control with HB without the need for additional hardware or calculations. For HM-based SM controllers, there are three basic methods to keep the switching frequency constant.

Functions of a well-designed timing controller or constant ramp. Under all operating conditions, this control method adjusts the ramping/timing function to regulate a predetermined switching frequency. 2) Adaptive control combined with HM-based SM control to lessen switching frequency divergence 3) PWM may be used in conjunction with HM to provide SM controls with a steady switching frequency. Basic methods for developing SMCs for CTLI are presented in this work. A cascade control structure made up of an outer voltage control loop and an inner current control loop may be used to solve the control issue. Control implementation is made further simpler by using a cascade control strategy to take use of the motion separation feature of power converters.
Power converters use the loop current and output voltage dynamics to control fast and slow motion, respectively. Since power converters are switching devices by nature, they offer continuous regulation. Current controls are usually built using traditional vector control techniques, while voltage controls are commonly designed using SM-PWM or hysteresis control. In this case, the current error is regulated using the SM approach. Maintaining the voltage control mechanism of the inverter capacitors is the control objective.
Active and reactive power generation in the grid can be controlled. Because it aligns with the characteristics of SM controllers like B, this control strategy was selected. Its rapid response time and robustness against external disturbances are making it a competitive alternative to conventional ones. When building this SMC, consideration is given to a control rule that notifies the planning interface of the system's state before the selected planning interface. The gate signals for the first and second inverters are supplied by two switching techniques, each of which is described in detail below using the HM methodology.

I Two-Level Circuit Diagram The bipolar modulation inverter in this system has two output levels: 1 and 1. Fig. 1 illustrates the switching logic.



Depending on the two inverters' phases, two switches are turned on throughout each cycle, while the other two remain inactive. PINv = k fsw, where fsw is the frequency-dependent on-off switching loss with value k. The total variable loss is 2PInv. Variable structural control (u) is defined as

u={█(+1,&if S_e>+HB@-1,if S_e<-HB)┤ - ( 14)


Se is the term used here to describe the discrepancy between the actual value of the state variable and the relevant reference value. In each shift, K is larger than the knob (Sk), and S satisfies the SM theorem's conditions. As indicated before, Scheme I is depicted in Figure 1. Schedule II: FORCING SWITCH FIG. 2 The plan is referenced in Scheme II. The switching frequency can be approximated by comparing the switching function with a fixed-frequency carrier signal. The carrier signal has a triangle-like form. The amplitude of the triangle wave is HB. This technique achieves a constant switching frequency while maintaining the hysteresis controller's strong characteristics. The carrier signal is also limited to a minimum amplitude at specific frequencies.
If the inverter is small, it could go into complex states. As container capacity increases, tracking inaccuracy and settlement time increase as well. Therefore, it is necessary to identify the appropriate carrier size. When creating an SM controller, the SMC's characteristics regarding response time and shock resistance are taken into account . We use a canonical phase model to describe the relative degrees of the controlled state variables id and iq. Since the id and iq variables are directly proportional to the feedback errors of the state variables, it is now possible to design sufficient slip surfaces to manage them. The feedback error is the difference between the current references Ia, Ib, and Ic and the actual current.

CONCLUSION
In this work, a new, reliable CTLI-based SM controller is used to control grid-tied devices. CTLI performs better than the other two SMC control techniques in this situation. The HM and zero mean current error approaches are used to generate the gate signals in Schemes I and II, respectively. It is undoubtedly possible to separate active and reactive power, both with and without solar radiation. A controller is demonstrated that will boost the power generated by solar PV modules by keeping the DC connection voltage at the ideal level for both schemes. Performance has been demonstrated to be reliable even when subjected to varied inverter input power, fluctuating solar irradiance, and a 50% increase in load.
The study found that the THD of the grid-connected PV system is significantly lower than the switch-off limit. While reactive power is provided to the grid in distributed STATCOM mode without solar radiation, both control systems maintain the DC connection voltage. The proposed SM controller allows the PV system to produce both active and reactive electricity. , Claims:Claims
1.Superior Performance of CTLI-based SM Controller: The CTLI-based Sliding Mode (SM) controller significantly outperforms other SMC control strategies (Schemes I and II) in terms of grid-tied device control, ensuring reliable active and reactive power separation under varying conditions, such as fluctuating solar radiation and load increases.
2.Effective Power Generation and Voltage Regulation: The proposed SM controller maintains optimal DC link voltage for both control schemes, thus enhancing the power production of solar PV modules, even in the presence of changing solar irradiance and varying inverter input power, as well as load fluctuations.

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