Power Quality Improvement in Solar Fed Cascaded Multilevel Inverter With Output Voltage Regulation Techniques

ABSTRACT:

 

The presence of harmonics in solar Photo Voltaic (PV) energy conversion system results in deterioration of power quality. To address such issue, this paper aims to investigate the elimination of harmonics in a solar fed cascaded _fteen level inverter with aid of Proportional Integral (PI), Arti_cial Neural Network (ANN) and Fuzzy Logic (FL) based controllers. Unlike other techniques, the proposed FLC based approach helps in obtaining reduced harmonic distortions that intend to an enhancement in power quality. In addition to the power quality improvement, this paper also proposed to provide output voltage regulation in terms of maintaining voltage and frequency at the inverter output end in compatible with the grid connection requirements. The simulations are performed in theMATLAB / Simulink environment for solar fed cascaded 15 level inverter incorporating PI, ANN and FL based controllers. To exhibit the proposed technique, a 3 kWp photovoltaic plant coupled to multilevel inverter is designed and hardware is demonstrated. All the three techniques are experimentally investigated with the measurement of power quality metrics along with establishing output voltage regulation.

KEYWORDS:

1.      Harmonics

2.      intelligent control

3.      multilevel inverter

4.      photo voltaic's

5.      power quality

6.      voltage regulation.

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

FIGURE 1. Fuzzy logic control structure.

 EXPECTED SIMULATION RESULTS:

 

FIGURE 2. Variation of output voltage with respect of irradiance.

FIGURE 3. Fifteen level output voltage with variable irradiance.

FIGURE 4. Regulated fifteen level output voltage with PI controller.

FIGURE 5. FFT analysis for PI based voltage regulation.

FIGURE 6. Regulated fifteen level output with ANN based controller.

FIGURE 7. FFT analysis for ANN based voltage regulation.

FIGURE 8. Regulated fifteen level output voltage with FLC.

FIGURE 9. FFT analysis for FLC based voltage regulation.

CONCLUSION:

The voltage regulation topology along with power quality improvement is considered and implemented both in simulation and experimental setup for a solar fed 15 level inverter. While considering the results, it is found that FLC presents better results for VR while considering the variations at the input solar PV. Despite this, FLC is considered for the nine-level by [23], but the implementation is carried out with the DC power supplies without utilizing the solar panels. All the other methods are implemented for low power and lesser levels of MLI topology. Commercial utilization of MLI by providing the constant output voltage is investigated, and the experimental results prove the effectiveness of the proposed system. The method is applicable for the users require grid interaction along with the power quality improvement.

 REFERENCES:

[1] S. Karekezi and T. Ranja, Renewable technologies in Africa. London, U.K.: Zed Books, 1997.

[2] S. Karekezi and W. Kithyoma, ``Renewable energy strategies for rural africa: Is a PV-led renewable energy strategy the right approach for providing modern energy to the rural poor of sub-saharan africa?'' Energy Policy, vol. 30, nos. 11_12, pp. 1071_1086, Sep. 2002.

[3] S. Karekezi andW. Kithyoma, ``Renewable energy in Africa: Prospects and limits in Renewable energy development,'' Workshop Afr. Energy Experts Operationalizing NEPAD Energy Initiative, vol. 1, pp. 1_30, 2-4 Jun. 2003. Jun. 2017. [Online]. Available: https://sustainabledevelopment.un. org/content/documents/nepadkarekezi.pdf

[4] D.-R. Thiam, ``Renewable decentralized in developing countries: Appraisal from microgrids project in senegal,'' Renew. Energy, vol. 35, no. 8, pp. 1615_1623, Aug. 2010.

[5] F. Christoph, World Energy Scenarios: Composing energy futures to 2050. London, U.K.: World Energy Council, 2013.

Construction and Performance Investigation of Three-Phase Solar PV and Battery Energy Storage System Integrated UPQC

ABSTRACT:

 

 This study examines the use of Unified Power Quality Conditioner (UPQC) to mitigate the power quality problems existed in the grid and the harmonics penetrated by the non-linear loads. The UPQC is supported by the Photovoltaic (PV) and Battery Energy Storage System (BESS) in this work. Generally, the PV system supplies the active power to the load. However, if the PV is unable to supply the power then the BESS activates and provides power especially during the longer-term voltage interruption. The standalone PV-UPQC system is less reliable compared to a hybrid PV-BESS system because of its instability and high environment-dependency. Therefore, BESS will improve the voltage support capability continuously in the longer-term, reduce the complexity of the DC-link voltage regulation algorithm, and keep producing clean energy. The phase synchronization operation of the UPQC controller is directed by a self-tuning filter (STF) integrated with the unit vector generator (UVG) technique. Implementation of STF will make sure the UPQC can successfully operate under unbalanced and distorted grid voltage conditions. Thus, the requirement of a phase-locked loop (PLL) is omitted and the STF-UVG is utilized to produce the synchronization phases for the series and shunt active power filter (APF) compensator in UPQC controller. Finally, the proposed STF-UVG method is compared with the conventional synchronous references frame (SRF-PLL) method based UPQC to show the significance of the proposed technique. Several case studies are further considered to validate the study in MATLAB-Simulink software.

 KEYWORDS:

1.      Battery Energy Storage System (BESS)

2.      Power Quality

3.      Self-Tuning filter (STF)

4.      Solar Photovoltaic (PV)

5.      Unified Power Quality Conditioner (UPQC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

FIGURE 1. UPQC system configuratio

EXPECTED SIMULATION RESULTS:

 

FIGURE 2. Simulation waveform acquired under Case Study 1 for UPQC connecting with PV-BESS, with include (A) three-phase source voltage (B) Injection voltage of Series APF (C) Load Voltage (D) Load Current (E) Injection Current of Shunt APF (F) Source Current.

FIGURE 3. Simulation result acquired under Case Study 1 for UPQC connecting with PV-BESS, with include (A) DC-Link Voltage (B) Current of PV (C) Power of PV (D) Output power of DC-Link (E) Power of BESS (F) SOC of BESS

 

 FIGURE 4. Simulation findings acquired under Case Study 1 for UPQC connecting with PV-BESS, (A) THD for current under voltage harmonic condition (B) THD for current under voltage harmonic with sag condition (C) THD for voltage

 

FIGURE 5. Simulation findings obtained under Case Study 1 for UPQC connecting with PV-BESS (A) Total capacitor voltage (B) Total capacitor current

FIGURE 6. Simulation waveform acquired under Case Study 1 for UPQC connecting without PV-BESS, with include (A) three-phase source voltage (B) Injection voltage of Series APF (C) Load Voltage (D) Load Current (E) Injection Current of Shunt APF (F) Source Current

 

FIGURE 7. Simulation findings acquired under Case Study 1 for UPQC connecting without PV-BESS, (A) THD for current under voltage harmonic condition (B) THD for current under voltage harmonic with sag condition (C) THD for voltage

FIGURE 8. Simulation findings obtained under Case Study 1 for UPQC without PV-BESS (A) Total capacitor voltage (B) Total capacitor current

FIGURE 9. Simulation waveform acquired under Case Study 2: Scenario A for balance voltage swell and sag condition, with include (A) three-phase source voltage (B) Injection voltage of Series APF (C) Load Voltage (D) Load Current (E) Injection Current of Shunt APF (F) Source Current

FIGURE 10. Simulation finding showing the detected voltage magnitude under Case study 2: Scenario A for balance voltage sag and swell condition.

FIGURE 11. Simulation findings acquired under Case Study 2: Scenario A for balance voltage sag and swell condition, (A) THD for current under balance voltage sag condition (B) THD for current under balance voltage swell condition (C) THD for voltage under both conditions

FIGURE 12. Simulation result acquired under Case Study 2: Scenario A for balance voltage sag and swell condition, with include (A) DC-Link Voltage (B) Current of PV (C) Power of PV (D) Output power of DC-Link (E) Power of BESS (F) SOC of BESS

 

FIGURE 13. Simulation findings showing the detected synchronization reference phase value in 𝒔𝒊𝒏(𝝎𝒕) and 𝒄𝒐𝒔(𝝎𝒕) under Case study 2: Scenario A for balance voltage swell and sag condition, with include (A) Detection of synchronization phase by the STF-UVG (B) Detection of synchronization phase by the conventional SRF-PLL

FIGURE 14. Simulation waveform acquired under Case Study 2: Scenario B for unbalance voltage swell and sag condition, with include (A) three-phase source voltage (B) Injection voltage of Series APF (C) Load Voltage (D) Load Current (E) Injection Current of Shunt APF (F) Source Current.

FIGURE 15. Simulation findings acquired the detected voltage magnitude under Case study 2: Scenario B for unbalance voltage sag and swell condition.

FIGURE 16. Simulation result acquired under Case Study 2: Scenario B for unbalance voltage sag and swell condition, with include (A) DC-Link Voltage (B) Current of PV (C) Power of PV (D ) Output power of DC-Link (E) Power of BESS (F) SOC of BESS

FIGURE 17. Simulation findings acquired under Case Study 2: Scenario B for unbalance voltage swell and sag condition, (A) THD for current under unbalance voltage swell condition (B) THD for current under unbalance voltage sag condition (C) THD for voltage under both condition

 

 

 FIGURE 18. Simulation findings of the detected phase value of synchronization reference in 𝐬𝐢𝐧(𝛚𝐭) and 𝐜𝐨𝐬(𝛚𝐭) under Case study 2: Scenario A for unbalance voltage swell and sag condition, with include (A) Synchronization phase detected by the STF-UVG (B) Synchronization phase detected by the conventional SRF-PLL

 

FIGURE 19. Simulation waveform acquired under Case Study 3: Scenario A for voltage interruption condition, with include (A) three-phase source voltage (B) Injection voltage of Series APF (C) Load Voltage

FIGURE 20. Simulation findings acquired the detected voltage magnitude under Case study 3: Scenario A for voltage interruption condition

FIGURE 21. Simulation result acquired under Case Study 2: Scenario A for voltage interruption condition, with include (A) DC-Link Voltage (B) Current of PV (C) Power of PV (D) PV Irradiance (E) PV temperature panel (F) Output power of DC-Link (G) Power of BESS (H) SOC of BESS

CONCLUSION:

The construction of three-phase UPQC has been investigated considering the condition of complex power quality problems which are an amalgamation of harmonics, voltage swell, and sags, and voltage interruption under unbalanced and distorted voltage grid condition. Integrating the BESS and PV with the UPQC provides active power capability to the network. The main benefit of BESS integrated with UPQC is that it makes the system capable of supplying and absorbing active power from the PV. Since renewable energy is not completely reliable because of its environment-dependent feature, integrating a BESS will solve the lack of renewable energy resources. Finally, it can be figured that the BESS and PV attached with UPQC can be a good alternative in the distributed generation to upgrade the power quality of the contemporary distribution system. The DC-link voltage is stable because of the continuous supply from the PV-BESS system. Therefore, it can reduce the complexity of the DC-link voltage regulation algorithm. The STF-UVG technique for synchronization phases is applied successfully in the shunt and series APF compensator to generate reference current and voltage. Thus, the UPQC is designed without relying on the PLL components, and mitigation of current and voltage are achieved successfully following the grid condition to ensure the system stability and to achieve almost unity power factor. The implementation of the proposed technique has confirmed that the grid current harmonics follow the IEEE-519 standard. Finally, it is worth mentioning that the proposed system can enhance the overall efficiency of the grid power system.

REFERENCES:

[1] IEEE Standards Coordinating Committee 22 on Power Quality, IEEE Recommended Practice for Monitoring Electric Power Quality, vol. 2009, no. June. 1995.

[2] D. De Yong, S. Bhowmik, and F. Magnago, “Optimized Complex Power Quality Classifier Using One vs. Rest Support Vector Machines,” Energy Power Eng., vol. 09, no. 10, pp. 568–587, 2017.

[3] A. Javadi, A. Hamadi, L. Woodward, and K. Al-Haddad, “Experimental Investigation on a Hybrid Series Active Power Compensator to Improve Power Quality of Typical Households,” IEEE Trans. Ind. Electron., vol. 63, no. 8, pp. 4849–4859, 2016.

[4] A. Javadi, L. Woodward, and K. Al-Haddad, “Real-Time Implementation of a Three-Phase THSeAF Based on a VSC and a P+R Controller to Improve the Power Quality of Weak Distribution Systems,” IEEE Trans. Power Electron., vol. 33, no. 3, pp. 2073–2082, 2018.

[5] M. A. Mansor, M. M. Othman, I. Musirin, and S. Z. M. Noor, “Dynamic voltage restorer (DVR) in a complex voltage disturbance compensation,” Int. J. Power Electron. Drive Syst., vol. 10, no. 4, pp. 2222–2230, 2019.

Design and Hardware Implementation of New Adaptive Fuzzy Logic-Based MPPT Control Method for Photovoltaic Applications

ABSTRACT:

 

An adaptive fuzzy logic (FL)-based new maximum power point (MPP) tracking (MPPT) methodology for controlling photovoltaic (PV) systems is proposed, designed, and implemented in this paper. The existing methods for implementing FL-based MPPTs lack for adaptivity with the operating point, which varies in wide range in practical PV systems with operating irradiance and ambient temperature. The new proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility veri_cations of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. In addition, the simpli_ed implementation of the proposed algorithm is carried out using C-block in PSIM software environment, wherein the proposed algorithm and system are simulated. Additionally, experimental results are performed using a _oating-point digital signal processing (DSP) controller (TMS320F28335) for verifying the feasibility of the proposed AFL-MPPT methodology. The results of simulations and experimental prototypes show great consistency and prove the capability of the newAFL-MPPT methodology to extract MPPT rapidly and precisely. The newproposed AFL-MPPT method achieves accurate output power of the PV system with smooth and low ripple. In addition, the new proposed AFL-MPPT method bene_ts fast dynamics and it reaches steady state within 0.01 s.

KEYWORDS:

1.      DSP controller

2.      energy eficiency

3.      fuzzy logic (FL)

4.      MPPT

5.      photovoltaic systems

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

FIGURE 1. Schematic diagram of PV system and control method.

 EXPECTED SIMULATION RESULTS:

 

FIGURE 2. Simulation results for the new proposed AFL-MPPT method at

transient starting.

FIGURE 3. Simulation results for the new proposed AFL-MPPT method at

step change in the radiance.

 

FIGURE 4. Simulations results of the new proposed AFL-MPPT method

at slow tracking response of the radiance.

 CONCLUSION:

This paper presented a new modi_ed controller and design method for FL-based MPPT tracking for PV systems. The newproposed method represents an adaptive FL-based MPPT (AFL-MPPT method). The main advantages in the proposed AFL-MPPT method are accurate and adaptive tracking performance of the operating maximum power extraction point of the solar PV system, and the mitigation of power _uctuations in transient and steady state operating points. Moreover, the proposed AFL-MPPT method achieves faster MPPT convergence with simple implementation. The proposed AFL-MPPT controller can effectively overcome the demerits of the existing MPPT methods in the literature. The proposed AFL-MPPT method has been implemented using C-block in PSIM environment and veri_ed by experimental prototyping of 75-watt PV module. The obtained experimental results coincide with the obtained simulation results, which verify the superior performance for the new proposed control method and design procedures over the conventional MPPT extraction schemes in the literature. The new proposed AFL-MPPT method bene_ts high tracking ef_ciency and fast dynamics by reaching steady state point within 0.01 seconds. Additionally, the new proposed implementation method can be easily integrated with the existing global MPPT searching algorithms.

REFERENCES:

[1] (2015). REN21_Renewables 2016 Global Status Report. [Online]. Available: http://www.ren21.net/status-of-renewables/global-status-report/

[2] A. Elmelegi, M. Aly, E. M. Ahmed, and A. G. Alharbi, ``A simpli-_ed phase-shift PWM-based feedforward distributed MPPT method for grid-connected cascaded PV inverters,'' Sol. Energy, vol. 187, pp. 1_12, Jul. 2019.

[3] M. B. Shadmand, M. Mosa, R. S. Balog, and H. A. Rub, ``Maximum power point tracking of grid connected photovoltaic system employing model predictive control,'' in Proc. IEEE Appl. Power Electron. Conf. Expo. (APEC), Mar. 2015, pp. 3067_3074.

[4] M. Aly, E. M. Ahmed, and M. Shoyama, ``Modulation method for improving reliability of multilevel T-type inverter in PV systems,'' IEEE J. Emerg. Sel. Topics Power Electron., to be published.

[5] K. S. Tey and S. Mekhilef, ``Modi_ed incremental conductance algorithm for photovoltaic system under partial shading conditions and load variation,'' IEEE Trans. Ind. Electron., vol. 61, no. 10, pp. 5384_5392, Oct. 2014.

Voltage Sag Enhancement of Grid Connected Hybrid PV-Wind Power System Using Battery and SMES Based Dynamic Voltage Restorer

 ABSTRACT:  

Renewable energy sources; which are abundant in nature and climate friendly are the only preferable choice of the world to provide green energy. The limitation of most renewable energy sources specifically wind and solar PV is its intermittent nature which are depend on wind speed and solar irradiance respectively and this leads to power fluctuations. To compensate and protect sensitive loads from being affected by the power distribution side fluctuations and faults, dynamic voltage restorer (DVR) is commonly used. This research work attempts to withstand and secure the effect of voltage fluctuation of grid connected hybrid PV-wind power system. To do so battery and super magnetic energy storage (SMES) based DVR is used as a compensating device in case of voltage sag condition. The compensation method used is a pre-sag compensation which locks the instantaneous real time three phase voltage magnitude and angle in normal condition at the point of common coupling (PCC) and stores independently so that during a disturbance it used for compensation. Symmetrical and asymmetrical voltage sags scenario are considered and compensation is carried out using Power System Computer Aided Design or Electro Magnetic Transient Design and Control (PSCAD/EMTDC) software.

KEYWORDS:

1.      Dynamic voltage restorer (DVR)

2.      Energy storage

3.      Intermittent

4.      Power quality

5.       Voltage sag compensation

 

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

 

Figure 1. The Proposed Bes-Smes Based Dvr For On Grid Pv-Wind Hybrid System

EXPERIMENTAL RESULTS:

 

(a)

(b)

(c)

Figure 2. Simulation Results And Dvr Response For 25% Symmetrical Voltage Sag Case (A) Load Voltage Without Dvr, (B) Dvr Injected Voltage And (C) Load Voltage With Dvr

 

(a)

(b)

(c)

Figure 3. Simulation Results And Dvr Response For 12% Symmetrical Voltage Sag Case (A) Load Voltage Without Dvr, (B) Dvr Injected Voltage And (C) Load Voltage With Dvr

(a)

(b)

(c)

Figure 4. Simulation Results And Dvr Response For 25% Asymmetrical Voltage Sag Case (A) Load Voltage Without Dvr, (B) Dvr Injected Voltage And (C) Load Voltage With Dvr

 

(a)

                                          

(b)

                                           

(c)

Figure5. Simulation Results And Dvr Response For 35% Asymmetrical Voltage Sag Case (A) Load Voltage Without Dvr, (B) Dvr Injected Voltage And (C) Load Voltage With Dvr

 CONCLUSION:

In this paper, a voltage sag enhancement of sensitive load which gets power from grid connected PV-wind power system is demonstrated using HES based DVR. The proposed DVR targets to protect the sensitive load from being affected by any voltage fluctuation which arise either from fault condition or unstable power output of PV-wind system. The control and operations of BES and SMES devices is developed by observing voltage condition of the grid at the PCC and the SOC levels of battery and SMES. In addition to this, for full realization of the proposed DVR system the control and operation of the VSC is developed by observing the voltage level at the PCC. The pre-sag compensation strategy is selected based on the capability of both magnitude and phase jump restoration. Based on the conditions, three operating states of the HES based DVR are defined, which are normal (idle state), charging state and discharging state. The effectiveness of the proposed operating states has been demonstrated in realistic cases. In the simulation, different voltage sag depth scenarios are considered for both symmetrical and asymmetrical voltage imbalances and the HES based DVR works well. A combination of voltage sag, voltage swell and harmonics scenarios will be demonstrated in the future works.

REFERENCES:

[1] BP Statistical Review of World Energy, 68th ed. 2019.

[2] M. R. Banaei and S. H. Hosseini, “Verification of a new energy control strategy for dynamic voltage restorer by simulation,” vol. 14, pp. 112–125, 2006.

[3] IRENA, Future of wind: Deployment, investment, technology, grid integration and socio-economic aspects (A Global Energy Transformation paper). International Renewable Energy Agency, Abu Dhabi, 2019.

[4] IRENA, Future of Solar Photovoltaic: Deployment, investment, technology, grid integration and socio-economic aspects (A Global Energy Transformation: paper). International Renewable Energy Agency, Abu Dhabi, 2019.

[5] H. M. Al-masri, S. Member, M. Ehsani, and L. Fellow, “Feasibility Investigation of a Hybrid On-Grid Wind Photovoltaic Retrofitting System,” IEEE Trans. Ind. Appl., vol. 52, no. 3, pp. 1979–1988, 2016.