Hybrid controller-based solar-fuel cell-integrated UPQC for enrichment of power quality

1 Introduction

Power quality (PQ) difficulties are caused by large nonlinear loads, modern power electronics, and the integration of distributed generation. A modest increase in PQ increases equipment durability and performance. Flexible AC transmission system devices address PQ. The integration of dynamic voltage restorers with distribution static compensators decreases harmonic currents, voltage dips/spikes, and unbalanced loads. Design and controller selection influence unified power quality conditioner’s (UPQC’s) capacity to eliminate PQ issues.

UPQC compensates for voltage sags/swells, volt ampere reactive, and harmonic currents by combining series and shunt-active power filters (SAPFs and shunt active power filter [SHAPF]). ICT was employed [1]. In addition, the created architecture for UPQC can be coupled with SHAPF and SAPF using the sliding mode controller case implemented. Certainly, under the constraints imposed by the dynamic voltage regulator employed for SAPF voltage restoration in an imbalanced and controlled voltage state [2]. Techniques for voltage and current control (CC) adjust for harmonics and grid voltages [3].

SAPF and SHAPF were given an equal participation in UPQC, hence decreasing SHAPF’s rating and UPQC’s expenses [4]. Offline, an artificial neural network (ANN) was developed to perform CC for SHAPF of UPQC [5]. The linearized optimal control technique for UPQC was developed [6] in order to achieve angular location of optimal case within the losses attained by a converter designed according to the linearized optimal control technique. We studied compensation techniques and UPQC settings [7].

Taking into account power loss, voltage/current profiles, and investment rate, a differential evolution-based strategy for optimal UPQC placement was developed [8]; a three-based level for neutral point clamped with inverter-based integration of UPQC and a recommended fuzzy development to reduce harmonics caused by source currents [9] were used to determine optimal UPQC placement. photo voltaic (PV)-integrated UPQC lowers grid-voltage disturbances with load current and controls reactive-based powering harmonics [10].

Integral and sliding mode control (SMC)-based capacitor voltage regulator for UPQC exhibited minimum settling time and no peak overrun [11]. Harmonic analysis, mathematical modelling, and mitigation techniques are all examples of mitigation strategies according to the UPQC proposal for a PV/Wind/Fuel cell/Battery microgrid system [12,13]. UPQC was subsequently used with the metals sector to mitigate harmonics in the case of loading into the induction furnace system [14].

The hybrid controller of UPQC decreases total harmonic distortion (THD) distortions during grid voltage strategy analysis [15]. In order to eliminate mathematical calculations, reference signals, and DC-link voltage structure from the planned network, the ANN controller for a five-level UPQC was built [16]. Upon implementation of PV integrated into UPQC, an improved LCL-based filter with SHAPF configuration will be achieved [17].

Fuzzy-ANN control for five-level UPQC reduces THD and increases power factor [18]. SHAPF was created via firefly optimization based on the predator–prey model [19]. Pulse width modulation (PWM) and vector PWM deployment [20] can effectively control THD and other grid voltage-related problems may be alleviated by PV and battery-based UPQC [21].

Controllability of UPQC when improvising PQ [22] to alleviate PQ problems, UPQC with D-STATCOM of three-phase H-bridge topology has been investigated [23]. In contrast to two-level converters, multilevel DG feeds UPQC [24]. To evaluate real and reactive power management and THD reduction, UPQC was coupled to non-linear loads [25].

Khadkikar [26] examined the purturb & observe (P&O) and PSO algorithms for PV maximum power point utilizing solar irradiation. Frequency-dependent network equivalent was created utilizing digital simulators and online least squares [27]. Designed AC–DC converters with high voltage [28]. Munoz et al. [29] analyzed the implementation of a boost full-bridge DC–DC converter with active snubber-electrical circuitry configuration.

Maximum power point tracking (MPPT) integration of renewables into the microgrid has been investigated [30]. The algorithm for the most valuable player [31] solves multi-objective optimal power flow [32]. Pande and Chetty [33,34,35] use the Capsule Network for image processing, classification, and semantic analysis with the load flow optimisation plan of the transmission and distribution network system. This method could be used effectively while developing a controller for UPQC.

This study examines the method of fuzzy-integrated sliding mode-based hybrid controller (FISMHC) in the findings of UPQC for the fuel cell (FC) system and the solar system (SS). In addition, THD can be reduced by increasing power factor, eliminating voltage fluctuations, and maintaining constant DC-link voltage under minimal peak overshoot absence and settling time conditions. Consequently, testing with UPFC for FISMHC (U-FISMHC) was conducted within the system’s distributed load, supply voltage, and irradiations with PV system.

Section 2 describes SS-FC UPQC. Section 3 explains the controller part. Section 4 describes the simulation outcomes. Section 5 ends with the discussions.

2 Structure for the proposed method of UPQC

Figure 1 depicts the three-phase FC and SS UPQC. With connection between SS and FC by deployment of UPQC's based DC-link using boost converter architecture. The fuzzy integrated SMC-based FISMHC is presented in this paper. SAPF and SHAPF are SAPF and SHAPF, respectively. SAPF reduces voltage across grid through compensatory injection for the isolation transformer within the system network (Tables 1 and 2).

Figure 1

Configuration of proposed U-FISMHC.

2.1 DC-link external featuring

As per UPQC’s modules depicted in Figure 2, DC–DC boost converters connect MPPT SS to DC-link capacitor. Eq. (1) gives the model’s power balance.

(1) P P V + P f c – P L o a d D C - L i n k = 0 .

Figure 2

External connection for DC-Link assistance modules.

2.1.1 SS

Solar PV generates electricity from sunlight. Figure 3 shows SS’s PV panel, boost converter, and MPPT controller. Solar energy powers PV cells. Given irradiance and temperature, MPPT maximizes PV output voltage. Figure 4 shows the PV cell circuitry. The PV panel output is evaluated based on the formulation of the following equation:

(2) P P V = V P V ⁎ i P V .

Figure 3

SSs with controller.

Figure 4

Flow chart for MPPT algorithm.

PV panel’s current and voltage are represented as i _pv and v _pv.

In this study, MPPT uses P&O to manage boost converter duty cycle (D). P and V estimate D. Voltage rises as power rises (Figure 5).

Figure 5

Controller integrated to FC.

2.1.2 FC

FCs produce electricity from chemical energy. Electrolyzing H₂ and O₂ produces electricity. High-voltage FC stacks increase FC voltage. Figure 6 shows the FC booster controller. I _refdc reduces V _dc,err by using a proportional integral controller (PIC).

(3) V dc , err ( t ) = V dc ref − V dc .

(4) i dc ref = K p , 1 V dc,err ( t ) + K i , 1 ∫ 0 t V dc,err ( t ) dt .

Figure 6

Shunt-VSC controller.

3 Control strategy

Faults change DC-link capacitor voltage. System stability is restored by restoring capacitor voltage. FISMHC controls series and shunt PWM voltage and hysteresis voltage source converters (VSCs). The proposed control structure includes the following.

3.1 Shunt-VSC

Shunt-VSC reduces DC-link current THD. FISMHC controllers generate reference currents and maintain DC-link voltage. SHAPF’s hybrid controller isolates load current’s active component. Phased locked loop (PLL) collects grid voltages to convert load currents to d-q-0. FISMHC generates currents that are transferred within the domain feasible into the a-b-c configuration to derive the system's reference point currents. Comparing with the hysteresis based PWM generation for sensing the currents subjected to shunt converter generation into the pulses gating with signal represented through Sa1, Sa2, Sb1, Sb2, Sc1, and Sc2 scenarios. Shunt-VSC Controller is depicted in Figure 7.

Figure 7

Membership function for error.

3.1.1 Implementation of fuzzy controller

With the control of the fuzzy logic controller (FLC) into DC-link voltage control by injecting the FLC inputs further with the analysis of output for E and CE into outputs duty cycle (D). Figures 8–10 show FLC E, CE, and D membership functions. E, CE, and D have positive high, positive medium, positive low, zero, negative low, negative medium and high negative. Table 3 lists the variables for fuzzy “IF-THEN” rules. Adding more rules increases the control system’s data size, execution time, and complexity.

Figure 8

Membership function for change in error.

Figure 9

Membership function for duty cycle.

Figure 10

Series VSC controller.

Table 3

Rules for fuzzy-if–then conditions

E	CE
	POH	POM	POL	ZO	NGL	NGM	NGH
NGH	ZO	NGL	NGM	NGB	NGH	NGH	NGH
NGL	POM	PSL	ZO	NGS	NGM	NGH	NGH
NGM	POL	ZO	NGL	NGM	NGH	NGH	NGH
ZO	POH	PSM	PSL	ZO	NGL	NM	NGH
POM	POH	PSH	PSH	PSM	PSL	ZO	NGL
POL	POH	PSH	PSM	PSL	ZO	NGL	NM
POH	POH	PSH	PSH	PSH	PSM	PSL	ZO

3.1.2 ISMC controller

Power converters designed in proposed study use improved SMC. This ISMC aims to slide the Surface control and propose sliding surface, check for sliding mode, and analyze surface stability.

3.2 Series VSC

With the injecting voltage associated to SAPF will stabilize certainly the voltage under load and unloaded conditions in the grid. Figure 11 depicts SAPF’s command structure. A PLL extracts grid voltage to form the d-q-0 reference axis. Reference load voltage is derived from the PLL phase and frequency data. Source, load, and reference voltages become d-q-0. The FISMHC controller translates the load–grid voltage difference into d-q-0. PWM voltage controller uses final output to generate series VSC pulses for triggering the signal, for instance, with the scenarios of Sa1a, Sa2a, Sb1a, Sb2a, Sc1a, and Sc2a cases.

Figure 11

Proposed FISMHC Simulink model for control of DC-link voltage.

4 Findings and analyses

The distribution network utilized for U-FISMHC simulations is displayed in Table 3. The Simulink model of the test system was designed in Matlab 2018a. The system was affected by variations in voltage, supply voltage, load, solar irradiance, and temperature. There are three PQ case studies listed in Table 4. Methods PIC, FLC, and SMC are compared.

Case studies 1 and 2 were in equilibrium, but 3 was not. Voltage decreased and increased in examples 1 and 2, respectively. THD and power factor of the proposed UPQC were compared to those of the existing PIC, FLC, and SMC.

PV panel output current and voltage, solar irradiation waveforms during steady state and sag/swell, and U-FISMHC disturbance situations were detected (Figure 12).

Figure 12

Proposed system waveform under case 1. (a) Source voltage, injected voltage, load voltage under steady state, (b) source current, injected current, load current under steady state, and (c) PV panel output current, PV panel voltage, DC-link voltage, solar irradiation.

Case 1: Balanced voltage. The supply voltage dipped 0.15–0.25 s, grew 0.35–0.45 s, and fluctuated 0.55–0.65 s at 1,000 irradiance at 250 C. SAPF maintained grid voltage by injecting the compensation. SHAPF kept current analysis under the grid simulation with sinusoidal pattern. Figure 13 depicts the load currents following the non-sinusoidal analysis. Furthermore, the source current and load voltage associated with THDs can be gained for 1.59 and 4.71%, respectively, within well-defined analysis gained at 14 and 23.5%, well within IEEE-519 limits. Without UPQC, the power factor is 0.7144.

Figure 13

Proposed system waveform under case 2. (a) Source voltage, injected voltage, load voltage under steady state, (b) source current, injected current, load current under steady state, and (c) PV panel output current, PV panel voltage, DC-link voltage, solar irradiation.

Case 2: Figure 14 shows U-dynamic FISMHC at 250 C with solar irradiation from 1,000 to 400. PV output voltage and current decreased as irradiation decreased, from 19 to 8 V and 14.87 to 5.95 A. SHAPF reduced load harmonics and FC reduced PV current. Figure 15 compares U-THD FISMHCs with load voltage and source current under Non-sinusoidal and harmonically balanced load conditions. Without UPQC, the power factor is 0.8552. SAPF improves power factor by compensating voltage sags/swells and disturbances.

Figure 14

Proposed system waveform under case 3. (a) Source voltage, injected voltage, load voltage under steady state, (b) source current, injected current, load current under steady state, and (c) PV panel output current, PV panel voltage, DC-link voltage, solar irradiation.

Figure 15

Current % THD under case 1.

Case 3: Figure 16 shows U-FISMHC at 250 C with unbalanced supply. Compensatory voltages and currents sinusoidalized unbalanced supply voltages and load currents. Normal THD power factor neared 1 after compensation (Table 5).

Figure 16

THD comparison bar chart.

Figures 13, 14, 16(c) show 700 V with a 0.05 s settling time and no overshoot. Table 6 compares the proposed controller settling time within the scheme developed to PIC, FLC, and SMC. Figures 17, 18 show FFT source current analysis for UPQC cases 1–3. All THDs are IEEE compliant.

Figure 17

Current % THD under case 2.

Figure 18

Current % THD under case 3.

5 Conclusion

A three-phase system of SS-FC U-FISMHC method has been designed as part of the research investigation. In addition, three different test cases were utilized to evaluate the effectiveness of the suggested strategy. Studies have shown that U-FISMHC can improve PQ. The proposed controller provides configuration of a particular likely system of consistent development in DC-link voltage through minimal time specifications, which include settling time with lessened changes in voltage. This is accomplished through the use of minimal time. Consequently, this compensates for the unequal power supplies.