Power quality improvement in distribution network using DSTATCOM with battery energy storage system

ABSTRACT

The distribution static compensator (DSTATCOM) provides fast control of active and reactive powers to enable load compensation, harmonics current elimination, voltage flicker mitigation, voltage and frequency regulation. This paper presents power quality improvement technique in the presence of grid disturbances and wind energy penetration using DSTATCOM with battery energy storage system. DSTATCOM control is provided based on synchronous reference frame theory. A modified IEEE 13 bus test feeder with DSTATCOM and wind generator is used for the study. Power quality events during grid disturbances such as feeder tripping and re-closing, voltage sag, swell and load switching have been studied in association with DSTATCOM. The power quality disturbances due to wind generator outage, synchronization and wind speed variations have also been investigated. The study has been carried out using MATLAB/SIMULINK and the simulation results are compared with real time results obtained by the use of real time digital simulator (RTDS) for validating the effectiveness of proposed methodology. The proposed method has been proved to be effective in improvement of power quality with all disturbances stated above.

 

KEYWORDS

  1. Battery energy storage system
  2. Radial distribution feeder
  3. DSTATCOM
  4. Synchronous reference frame theory

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig.1. Proposed DSTATCOM with BESS.

 

SIMULATION RESULTS

Fig.2. Feeder tripping and re-closing without DSTATCOM in the network (a) RMS voltage at bus 632, (b) active power flow and (c) reactive power flow

Fig.3. Feeder tripping and re-closing with DSTATCOM in the network (a) RMS voltage at bus 632, (b) active power flow and (c) reactive power flow

Fig.4. Load switching without DSTATCOM in the network (a) RMS voltage at bus 632, (b) active power flow and (c) reactive power flow

Fig.5. Load switching with DSTATCOM in the network (a) RMS voltage at bus 632, (b) active power flow and (c) reactive power flow.

Fig.6. Voltage sag and swell (a) without DSTATCOM, (b) with DSTATCOM and (c) reactive power flow during voltage sag and swell.

Fig. 7 Wind synchronization (a) voltage without DSTATCOM, (b) voltage with DSTATCOM, (c) active power flow with DSTATCOM and (d) reactive power flow with DSTATCOM.

Fig. 8. Wind outage (a) voltage without DSTATCOM, (b) voltage with DSTATCOM, (c) active power flow with DSTATCOM and (d) reactive power flow with DSTATCOM

Fig. 9. Wind speed variation.

 

CONCLUSION

The proposed research work investigates into PQ events associated with distribution network due to grid disturbances such as voltage sag, swell, load switching, feeder tripping and re-closing. The DSTATCOM has been proposed to improve the power quality in the above events. The proposed DSTATCOM with SRF based control has been proved to be effective in improving the power quality in these events at grid level. The power quality events associated with wind operations such as wind generator outage, grid synchronization of wind generator and wind speed variations have been improved by the use of proposed DSTATCOM in the distribution network. From, these studies it has been established that the DSTATCOM can effectively be used to improve the power quality in the distribution network with wind generation and during grid disturbances. The results have been validated in real time utilizing RTDS. The real time results are very close to the simulation results which shows the effectiveness of proposed DSTATCOM with BESS for improvement of PQ in the distribution system.

 

REFERENCES

  • Ibrahim W, Morcos M. A power quality perspective to system operational diagnosis using fuzzy logic and adaptive techniques. IEEE Trans Power Deliv 2003;18(3):903–9. http://dx.doi.org/10.1109/TPWRD.2003.813885.
  • Ray P, Mohanty S, Kishor N. Classification of power quality disturbances due to environmental characteristics in distributed generation system. IEEE TransSust Energy 2013;4(2):302–13. http://dx.doi.org/10.1109/TSTE.2012.2224678.
  • Tascikaraoglu A, Uzunoglu M, Vural B, Erdinc O. Power quality assessment of wind turbines and comparison with conventional legal regulations: a case study in turkey. Appl Energy 2011;88(5):1864–72. http://dx.doi.org/10.1016/j. apenergy.2010.12.001.
  • Dash P, Padhee M, Barik S. Estimation of power quality indices in distributed generation systems during power islanding conditions. Int J Electr Power Energy Syst 2012;36(1):18–30. http://dx.doi.org/10.1016/j.ijepes.2011.10.019.
  • Mahela OP, Shaik AG, Gupta N. A critical review of detection and classification of power quality events. Renew Sust Energy Rev 2015;41(0):495–505. http:// dx.doi.org/10.1016/j.rser.2014.08.070.

Modeling and Simulation of a Distribution STATCOM (D-STATCOM) for Power Quality Problems-Voltage Sag and Swell Based on Sinusoidal Pulse Width Modulation (SPWM)

ABSTRACT:

This paper presents the systematic procedure of the modeling and simulation of a Distribution STATCOM (DSTATCOM) for power quality problems, voltage sag and swell based on Sinusoidal Pulse Width Modulation (SPWM) technique. Power quality is an occurrence manifested as a nonstandard voltage, current or frequency that results in a failure of end use equipments. The major problems dealt here is the voltage sag and swell. To solve this problem, custom power devices are used. One of those devices is the Distribution STATCOM (D-STATCOM), which is the most efficient and effective modern custom power device used in power distribution networks. D-STATCOM injects a current in to the system to correct the voltage sag and swell.The control of the Voltage Source Converter (VSC) is done with the help of SPWM. The proposed D-STATCOM is modeled and simulated using MATLAB/SIMULINK software.

KEYWORDS:

  1. Distribution STATCOM (D-STATCOM)
  2. MATLAB/SIMULINK
  3. Power quality problems
  4. Sinusoidal Pulse  Width Modulation (SPWM)
  5. Voltage sag and swell
  6. Voltage  Source Converter (VSC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. Schematic representation of the D-STATECOM for a typical custom

power application.

EXPECTED SIMULATION RESULTS:

 Fig. 2. Voltage Vrms at load point, with three-phase fault: (a) Without DSTATCOM and (b) With D-STATCOM, 750I-lf .

Fig. 3. Voltage vrms at load point, with three phase-ground fault: (a)

Without D-STATCOM and (b) With D-STATCOM.

Fig. 4. Voltage Vrms at load point, with line-ground fault: (a) Without DSTATCOM and (b) With D-STATCOM.

Fig. 5. Voltage vrms at load point, with line-line fault: (a) Without DSTATCOM and (b) With D-STATCOM.

Fig. 6. Voltage vrms at load point, with line-line-ground fault: (a) Without

D-STATCOM and (b) With D-STATCOM.

CONCLUSION:

This paper has presented the power quality problems such as voltage sags and swell. Compensation techniques of custom power electronic device D-ST ATCOM was presented. The   design and applications of D-STATCOM for voltage sags, swells and comprehensive results were presented. The Voltage Source Convert (VSC) was implemented with the help of Sinusoidal Pulse Width Modulation (SPWM). The control scheme was tested under a wide range of operating conditions, and it was observed to be very robust in every case. For modeling and simulation of a D-ST ATCOM by using the highly developed graphic facilities available in MA TLAB/SIMULINK were used. The simulations carried out here showed that the D-STATCOM provides relatively better voltage regulation capabilities.

 REFERENCES:

[I] O. Anaya-Lara, E. Acha, “Modeling and analysis of custom power  systems by PSCAD/EMTDC,” IEEE Trans. Power Delivery, vol. 17, no .I, pp. 266-272, January 2002.

[2] S. Ravi Kumar, S. Sivanagaraju, “Simualgion of D-Statcom and DVR in  power system,” ARPN jornal of engineering and applied science, vol. 2,   no. 3, pp. 7-13, June 2007.

[3] H. Hingorani, “Introducing custom power”, IEEE Spectrum, vol. 32, no.6, pp. 41-48, June 1995.

[4] N. Hingorani, “FACTS-Flexible ac transmission systems,” in Proc. IEE 5th Int Conf AC DC Transmission, London, U.K., 1991, Conf Pub.  345, pp. 1-7.

[5] Mahesh Singh, Vaibhav Tiwari, “Modeling analysis and soltion to  power quality problems,” unpublished.

PV system fuzzy logic MPPT method and PI control as a charge controller

ABSTRACT:

This paper puts forward to Fuzzy Logic MPPT (Maximum Power Point Tracking) method applied photovoltaic panel sourced boost converter, under variable temperature (25–60 °C) and irradiance (700–1000 W/m2) after that the PI control was applied buck converter to behave as a charge controller. The voltage and current of PV panels are nonlinear and they depend on environmental conditions such as temperature and irradiance. Variable environmental conditions cause to change voltage, current and also cause to change maximum available power of PV panels. To increase efficiency and decrease payback period of the system, it needs to operate PV panels at maximum power point (MPP). Under any environment conditions there is unique MPP. To operate PV panels at that point (MPP) there are many MPPT method in literature, FLC MPPT method was preferred in this study because, its rapid response to changing environmental conditions and not affecting by change of circuit parameters. The accuracy of FLC MPPT method used in this system to find MPP changes, from 94.8% to 99.4%. To charge a battery there are two traditional methods which are constant current (CC), and constant voltage (CV) methods. For fast charging with low loss constant current and voltage source is a need. One of the methods providing constant is PI control which used in this study. PI control is not only well developed and a simple technique but also it provides satisfactory results. The goal of this study is operating PV panel at maximum power point under variable environment conditions to increase efficiency and reduce cost and also provide appropriate current and voltage for charging battery to charge quickly, reduce losses and also increase life cycle of battery. This system was established and analyzed in MATLAB/Simulink.

 KEYWORDS:

  1. PV systems
  2. MPPT methods
  3. DC-DC converters
  4. PI control
  5. Charge controllers

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. PV system MPPT algorithm and PI control charge circuit.

 EXPECTED SIMULATION RESULTS:

 Fig. 2. The Power of PV panel.

Fig. 3. The Voltage of PV panel and load of boost converter.

Fig. 4. The duty cycle regulated by FLC MPPT.

Fig. 5. The load voltage of buck converter.

Fig. 6. The load current of buck converter

Fig. 7. The power regulated by PI control.

CONCLUSION:

The proposed system has been studied under four different conditions. Responses of system under varying radiation and temperature was observed. The accuracy of the MPPT algorithm to find MPP varied from 94.8% to 99.4%. The load current and voltage of buck converter remained constant level until end time of system (2.39 A, 15.03 V respectively shown in Table 3). The efficiency we wanted to get from the system has been reached to a great extent. In some cases the efficiency of buck converter can be low but the desired point to be reached in this system is getting the maximum yield from the PV panel to reduce cost and to charge the battery with constant current and appropriate voltage to reduce losses, fast charge and increase life cycle of battery. If there is a meaningful support to the material, the system will be realized in real life.

 REFERENCES:

[1] Takun P, Somyot Kaitwanidvilai S, Jettanasen C. Maximum power point tracking using fuzzy logic control for photovoltaic systems” 2011 preceedings of the international multiconference of engineer and computer scientist 2011. IMECS 2011;vol II:1–3.

[2] Vasantharaj S, Vinodhkumar G, Sasikumar M. Development of a fuzzy logic based, photovoltaic maximum power point tracking control system using boost converter, In: Proceedings of the third international conference onsustainable energy and intelligent system (SEİSCON 2012), VCTW, Tiruchengode, Tamilnadu, India; 27– 29 December, 2012. p. 2–5.

[3] Roy CP, Vijaybhaskar C, Maity T. Modellıng of fuzzy logıc controller for varıable step MPPT ın photovoltaıc system. Int J Res Eng Technol 2013;2(8):426–8, eıssn: 2319-1163 pıssn: 2321-7308.

[4] Subudhi B, Raseswari Pradhan R. A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Trans Sustain Energy 2013;4:89–97.

[5] Kolsi S, Samet H, Ben Amar M. Design analysis of DC-DC converters connected to a photovoltaic generator and controlled by MPPT for optimal energy transfer throughout a clear day. J Power Energy Eng 2014;2:27–34.

Speed response of brushless DC motor using fuzzy PID controller under varying load condition

ABSTRACT

The increasing trend towards usage of precisely controlled, high torque, efficient and low noise motors for dedicated applications has attracted the at tention of researcher in Brushless DC (BLDC) motors. BLDC motors can act as an acceptable alternative to the conventional motors like Induction Motors, Switched Reluctance Motors etc. This paper presents a detailed study on the performance of a BLDC motor supplying different types of loads, and at the same time, deploying different control techniques. An advance Fuzzy PID controller is compared with the commonly used PID controller. The load variations considered are of the most common types, generally encountered in practice. A comparison has been carried out in this paper by observing the dynamic speed response of motor at the time of application as well as at the time of removal of the load. The BLDC motors suffer from a major drawback of having jerky behavior at the time of load removal. The study reveals that irrespective of the type of controller used, the gradual load variation produces better results as against sudden load variations. It is further observed that in addition to other dynamic features, the jerks produced at the time of load removal also get improved to a large extent with Fuzzy PID controller. The speed torque characteristics un raveled the fact that the jerks are minimum at the time of gradual load removal with Fuzzy PID controller in place. An attempt has been made to define these jerks by ‘Perturbation Window’.

KEYWORDS:

  1. BLDC motor
  2. Proportional-integral-derivative (PID) controller
  3. Fuzzy (FL) controller
  4. MATLAB/SIMULINK

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:


 Fig.1.Block diagram of BLDC motor drive.

  EXPERIMENTAL RESULTS:

Fig.2.(a) Speed response curve (b) current response curve (c) torque response curve with PID controller under gradual application and removal of load.

Fig.3.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under sudden application and removal of load.

Fig.4.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller. under sudden application and removal of load

Fig.5.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under sudden application and removal of load.

Fig.6.(a) Speed response curve (b) current response curve (c) torque response curve with Fuzzy PID controller under gradual application and removal of load.

CONCLUSION

A model is developed in this paper for BLDC Drive using MATLAB/SIMULINK to analyze its performance with PID controller and with Fuzzy PID Controller when the motor is subjected to the most commonly encountered sudden load variations as well as gradual load variations under constant speed operation. The BLDC drive gives better performance if the load is changed gradually. Further, it is found that the transient response of the drive in terms of overshoot, under shoot, peak time and settling time are improved with the use of FPID. Speed torque characteristics of The drive are also used for all the conditions to assess the overall behavior of the machine. The commonly experienced major drawback of the jerks of BLDC motors at the time of load removal has been found to get reduced by 50% incase of sudden load removal and by about 80% incase of gradual load removal by applying FPID controller as against the use of classical PID controller.

REFERENCES

Arulmozhiyal, R., Kandiban, R., 2012. Design of Fuzzy PID controller for Brushless DC motor. In: International conference on Computer Communication and Informatics (ICCCI—2012), Jan.10–12, Coimbatore, INDIA.

Baldursson,S.,2005. BLDC Motor Modelling and Control—A MATLAB/Simulink Implementation, Master Thesis.

Dorf,C.,Richard,C.,Robert Bishop,H.,2001.Modern control systems,9thed.Prentice Hall Inc.,New Jersey-07458,USA,Chapters 1,5,pp.1–23,pp.173–206.

Farouk,Naeim,Bingqi,Tian,2012.Application of self-tuning Fuzzy PID controller on the AVR system. In: IEEE Conference of Mechatronics and Automation,August5–8,Chengdu,China.

Gupta,D.,2016.Speed control of Brushless DC motor using Fuzzy PID controller.11–12 March KNIT, IndiaIn: IEEE conference on Emerging trends in Electrical, Electronics & Sustainable Energy System,Volume2,pp.221–224.

Modeling And Simulation For Voltage Sags/Swells Mitigation Using Dynamic Voltage Restorer (Dvr)

ABSTRACT

 This project describes the problem of voltage sags and swells and its severe impact on non linear loads or sensitive loads. The dynamic voltage restorer (DVR) has become popular as a cost effective solution for the protection of sensitive loads from voltage sags and swells. The control of the compensation voltages in DVR based on dqo algorithm is discussed. It first analyzes the power circuit of a DVR system in order to come up with appropriate control limitations and control targets for the compensation voltage control. The proposed control scheme is simple to design. Simulation results carried out by Matlab/Simulink verify the performance of the proposed method .

KEYWORDS

  1. DVR
  2. Voltage sags
  3. Voltage swells
  4. Sensitive load

 

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM

 DVR

Figure 1: Schematic diagram of DVR

 

FLOWCHART:

  

Fig.2 Flow Chart Of Feed forward Control Technique For DVR Based Ob DQO Transformation

Three-phase voltages sag:

Figure 3. Three-phase voltages sag: (a)-Source voltage,(b)-Injected voltage, (c)-Load voltage

Single-phase voltage sag

Figure.4. Single-phase voltage sag: (a)-Source voltage, (b)-Injected voltage, (c)-Load voltage

Three-phase voltages swell

Figure.5.Three-phase voltages swell: (a)-Source voltage, (b)-Injected voltage, (c)-Load voltage

Two-phase voltages swell

Figure. 6. Two-phase voltages swell: (a)-Source voltage, (b)-Injected voltage, (c)-Load voltage

 

CONCLUSION:

 The modeling and simulation of a DVR using MATLAB/SIMULINK has been presented. A control system based on dqo technique which is a scaled error of the between source side of the DVR and its reference for sags/swell correction has been presented. The simulation shows that the DVR performance is satisfactory in mitigating voltage sags/swells.

 

REFERENCES:

  • G. Hingorani, “Introducing Custom Power in IEEE Spectrum,” 32p, pp. 4l-48, 1995.
  • IEEE Std. 1159 – 1995, “Recommended Practice for Monitoring Electric Power Quality”.
  • Boonchiam and N. Mithulananthan, “Understanding of Dynamic Voltage Restorers through MATLAB Simulation,” Thammasat Int. J. Sc. Tech., Vol. 11, No. 3, July-Sept 2006.
  • G. Nielsen, M. Newman, H. Nielsen,and F. Blaabjerg, “Control and testing of a dynamic voltage restorer (DVR) at medium voltage level,” IEEE Trans. Power Electron., vol. 19, no. 3,p.806, May 2004.
  • Ghosh and G. Ledwich, “Power Quality Enhancement Using Custom Power Devices,” Kluwer Academic Publishers, 2002.
  • Modeling And Simulation For Voltage Sags/Swells Mitigation Using Dynamic Voltage Restorer (Dvr)

Improved Particle Swarm Optimization For Photovoltaic System Connected To The Grid With Low Voltage Ride Through Capability

 ABSTRACT:

 Grid connected photovoltaic (PV) system encounters different types of abnormalities during grid faults; the grid side inverter is subjected to three serious problems which are excessive DC link voltage, high AC currents and loss of grid-voltage synchronization. This high DC link voltage may damage the inverter. Also, the voltage sags will force the PV system to be disconnected from the grid according to grid code. This paper presents a novel control strategy of the two-stage three-phase PV system to improve the Low-Voltage Ride-Through (LVRT) capability according to the grid connection requirement. The non-linear control technique using Improved Particle Swarm Optimization (IPSO) of a PV system connected to the grid through an isolated high frequency DCeDC full bridge converter and a three-phase three level neutral point clamped DC-AC converter (3LNPC2) with output power control under severe faults of grid voltage. The paper, also discusses the transient behavior and the performance limit for LVRT by using a DC-Chopper circuit. The model has been implemented in MATLAB/SIMULINK. The proposed control succeeded to track MPP, achieved LVRT requirements and improving the quality of DC link voltage. The paper show

KEYWORDS:

  1. Particle swarm optimization
  2. Maximum power point tracking
  3. PV system
  4. High frequency isolated converter
  5. Low voltage ride through
  6. Grid

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

 

Fig. 1. Block diagram of the PV system connected to the grid.

EXPECTED SIMULATION RESULTS:

Fig. 2. PV module characteristics (a) Current-voltage characteristics (b) power-voltage characteristics.

Fig. 3. Behavior of PV array under normal condition using IPSO.

Fig. 4. DC-link voltage under normal condition using IPSO.

Fig. 5. Behavior of PV array under normal condition using IC.

Fig. 6. DC-link voltage under normal condition using IC.

Fig. 7. Behavior of grid connected inverter system under normal operation.

 

Fig. 8. The grid voltage fault.

Fig. 9. Behavior of PV array under fault condition.

Fig. 10. DC-link voltage under fault condition.

Fig. 11. Behavior of grid connected inverter system under fault condition.

Fig. 12. Behavior of PV array with LVRT capability.

Fig. 13. DC-link voltage during a grid fault with LVRT capability.

Fig. 14. Behavior of grid connected inverter system with LVRT capability.

CONCLUSION:

Based on the existing grid requirements, this paper discussed the potential of a two-stage three-phase grid-connected PV system operating in grid fault condition. The power control method proposed in this paper is effective when the system is under grid fault operation mode. It can be concluded that the future three-phase grid-connected PV systems are ready to be more active and more “smart” in the regulation of power grid.

Non-linear robust control technique using IPSO control is implemented for MPPT of 100.7 kW PV system connected to the grid. Complete control of both active and reactive powers is implemented using Matlab/Simulink with complete simulation under severe faults of grid voltage. The results show superior behavior of the IPSO; it has a faster dynamic response and better steady-state performance than the traditional algorithm; IC method, thus improving the efficiency of the photovoltaic power generation system. The use of full bridge single phase inverter with a high frequency transformer which combines the advantages of 60 Hz technology and transformer- less inverter technology, achieved MPPT requirements with IPSO. Also, this system overcomes the drawbacks of DC-chopper parameters design.

Two loops of control for the utility-connected 3LNPC2 are implemented which improve the performance of inverter and reduces the harmonics in output voltage. This control, also, increases the power injected to the grid and consequently increases the total efficiency of the system. The results show that the DC chopper circuit is capable of reducing the DC-link voltage below threshold values during the fault and protect it from failure or damage. The IPSO is capable of tracking MPP with LVRT capability included.

An anti-wind up conditioned strategy is used in order to improve the quality on the DC link voltage during and after the grid fault. It succeeds to stop accumulation of the integral part during fault, which helps system to follow up pre-faults values rapidly after clearing the fault. Finally, simulated results have demonstrated the feasibility of the IPSO algorithm and capability of MPPT in grid-connected PV systems with LVRT enhancement.

REFERENCES:

[1] Ramdan B.A. Koad, Ahmed. F. Zobaa, Comparison between the conventional methods and PSO based MPPT algorithm for photovoltaic systems, Int. J. Electr. Electron. Sci. Eng. 8 (2014) 619e624.

[2] Ali Reza Reisi, Mohammad Hassan Moradi, Shahriar Jamas, Classification and comparison of maximum power point tracking techniques for photovoltaic system: a review, Renew. Sustain. Energy Rev. 19 (2013) 433e443.

[3] N.H. Saad, A.A. Sattar, A.M. Mansour, Artificial neural controller for maximum power point tracking of photovoltaic system, in: MEPCON’2006 Conference, II, El-MINIA, Egypt, 2006, pp. 562e567.

[4] Raal Mandour I. Elamvazuthi, Optimization of maximum power point tracking (MPPT) of photovoltaic system using artificial intelligence (AI) algorithms, J. Emerg. Trends Comput. Information Sci. 4 (2013) 662e669.

[5] Saeedeh Ahmadi, Shirzad Abdi, Maximum power point tracking of photovoltaic systems using PSO algorithm under partially shaded conditions, in: The 2nd Cired Regional Conference, Tehran, Iran, 14, 2014, pp. 1e7.

Maximum Power Point Tracking Using Fuzzy Logic Controller under Partial Conditions

Scientific Research Publishing, Smart Grid and Renewable Energy, 2015.

Maximum Power Point  ABSTRACT: This study proposes a fuzzy system for tracking the maximum power point of a PV system for solar panel. The solar panel and maximum power point tracker have been modeled using MATLAB/Simulink. A simulation model consists of PV panel, boost converter, and maximum power point tack MPPT algorithm is developed. Three different conditions are simulated: 1) Uniform irradiation; 2) Sudden changing; 3) Partial shading. Results showed that fuzzy controller successfully find MPP for all different weather conditions studied. FLC has excellent ability to track MPP in less than 0.01 second when PV is subjected to sudden changes and partial shading in irradiation.

KEYWORDS:

  • Fuzzy Logic Controller
  • Maximum Power Point
  • Photovoltaic System
  • Partial Shading

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

Figure 1. Schematic diagram of PV system with MPPT.

EXPECTED SIMULATION RESULTS:

 

Figure 2. P-V characteristics at different irradiations.

Figure 3. P-V characteristics when partial shading from 1000 to 600 Watt/m2.

Figure 4. Output of fuzzy at1000 Watt/m2.

Figure 5. Output of fuzzy controller. (a) Full shading from 600 to 300 Watt/m2; (b) Full shading from 700 to 400 Watt/m2; (c) Full shading from 900 to 400 Watt/m2; (d) Increasing shading from 300 to 800 Watt/m2.

Figure 6. Comparison between fuzzy and P & O partial shading (partial shading 1000 to 800 Watt/m2).

CONCLUSION:

 In this study, FLC has been developed to track the maximum power point of PV system. PV panel, boost converter with FLC connected to a resistive load has been simulated using Matlab/Simulink. Simulation results have been compared to nominal power values. The proposed system showed its ability to reach MMP under uniform irradiation, sudden changes of irradiation, and partial shading. Simulation results have shown that using FLC has great advantages over conventional methods. It is found that Fuzzy controller always finds the global MPP. It is found that fuzzy logic systems are easily implemented with minimal oscillations with fast convergence around the desired MP

 REFERENCES:

 [1] Devabhaktuni, V., Alam, M., Reddy Depuru, S.S.S., Green II, R.C., Nims, D. and Near, C. (2013) Solar Energy: Trends and Enabling Technologies. Renewable and Sustainable Energy Reviews, 19, 555-556. http://dx.doi.org/10.1016/j.rser.2012.11.024

[2] Bataineh, K.M. and Dalalah, D. (2012) Optimal Configuration for Design of Stand-Alone PV System. Smart Grid and Renewable Energy, 3, 139-147. http://dx.doi.org/10.4236/sgre.2012.32020

[3] Bataineh, K. and Dalalah, D. (2013) Assessment of Wind Energy Potential for Selected Areas in Jordan. Journal of Renewable Energy, 59, 75-81.

[4] Bataineh, K.M. and Hamzeh, A. (2014) Efficient Maximum Power Point Tracking Algorithm for PV Application under Rapid Changing Weather Condition. ISRN Renewable Energy, 2014, Article ID: 673840. http://dx.doi.org/10.1155/2014/673840

[5] International Energy Agency (2010) Trends in Photovoltaic Applications. Survey Report of Selected IEA Countries between 1992 and 2009. http://www.ieapvps.org/products/download/Trends-in Photovoltaic_2010.pdf

Maximum Power Point

Dynamic voltage restorer employing multilevel cascaded H-bridge inverter

IET Power Electronics, 2016

ABSTRACT: This study presents design and analysis of a dynamic voltage restorer (DVR) which employs a cascaded multilevel inverter with capacitors as energy sources. The multilevel inverter enables the DVR to connect directly to the medium voltage networks, hence, eliminating the series injection transformer. Using zero energy compensation method, the DVR does not need active energy storage systems, such as batteries. Since the energy storage system only includes capacitors, the control system will face some additional challenges compared with other DVR systems. Controlling the voltage of capacitors around a reference voltage and keeping the balance between them, in standby and compensation period, is one of them. A control scheme is presented in this study that overcomes the challenges. Additionally, a fast three-phase estimation method is employed to minimize the delay of DVR and to mitigate the voltage sags as fast as possible. Performance of the control scheme and estimation method is assessed using several simulations in MATLAB / SIMULINK environments.

KEYWORDS:

  1. Multilevel inverter
  2. cascaded H-bridge inverter
  3. Dynamic Voltage Restorer

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

 Multilevel inverter

 Fig. 1 DVR strcuctures  a) Conventional DVR b) CHB-based DVR

 EXPECTED SIMULATION RESULTS:

Fig. 2 Three-phase voltage sag a) Network voltage b) Injected voltage by the DVR c) Load-side voltage

 Fig. 3 Unbalanced voltage sag (a 20% voltage sag on phase A) a) Source voltage b) Injected voltage by the DVR c) Load-side voltage

Fig. 4 Voltages of the DC link capacitors

Fig. 5 Three-phase 20% voltage sag with voltage harmonics a) Network voltage b) Injected voltage by the DVR c) Load-side voltage

 

CONCLUSION:

This paper presented design and performance assessment of a DVR based on the voltage sag data collected from MWPI. Using a multilevel converter, the proposed DVR was capable of direct connection to the medium voltage-level network without a series injection transformer. In addition, development of zero active power compensation technique helps to achieve voltage restoration goal just by the capacitors as energy storages. Due to internal losses of H-bridge cells and probable inaccuracies in measurements, voltage of DC link capacitors may become unequal, which prevents proper operation of the converter. A voltage control scheme, comprised of three separate controllers, was proposed in this paper for keeping voltage balance among the DC link capacitors within nominal range. A fast estimation method was also employed for calculation of phase and magnitude terms in an unbalanced three-phase system. This estimation method is able to recognise voltage sags in approximately half a cycle. Several simulations were performed in PSCAD/EMTDC environment to verify the performance of CHB-based DVR. Additionally, a laboratory-scale prototype of the proposed DVR was built and tested. Results of the experimental test also confirmed validity of the proposed control system.

 REFERENCES:

1 Chapman, D.: ‘The cost of poor power quality’ (European Copper Institute, Copper Development Association, 2001), March

2 Radmehr, M., Farhangi, S., Nasiri, A.: ‘Effects of power quality distortions on electrical drives and transformer life in paper industries’, IEEE Ind. Appl. Mag., 2007, 13, (5), pp. 38–48

3 Lamoree, J., Mueller, D., Vinett, P.: ‘Voltage sag analysis case studies’, IEEE Trans. Ind. Appl., 1994, 30, (4), pp. 1083–1089

4 Bollen, M.H.J.: ‘Understanding power quality problems: voltage sags and interruptions’ (New York, Saranarce University of Technology, 2000)

5 Ghosh, A., Ledwich, G.: ‘Power quality enhancement using custom power devices’ (Berlin, Kluwer Academic Publications, 2002)

BLDC Motor Driven Solar PV Array Fed Water Pumping System Employing Zeta Converter

BLDC Motor Driven Solar PV Array Fed Water Pumping System Employing Zeta Converter

 ABSTRACT:

This paper proposes a simple, cost effective and efficient brushless DC (BLDC) motor drive for solar photovoltaic (SPV) array fed water pumping system. A zeta converter is utilized in order to extract the maximum available power from the SPV array. The proposed control algorithm eliminates phase current sensors and adapts a fundamental frequency switching of the voltage source inverter (VSI), thus avoiding the power losses due to high frequency switching. No additional control or circuitry is used for speed control of the BLDC motor. The speed is controlled through a variable DC link voltage of VSI. An appropriate control of zeta converter through the incremental conductance maximum power point tracking (INC-MPPT) algorithm offers soft starting of the BLDC motor. The proposed water pumping system is designed and modeled such that the performance is not affected under dynamic conditions. The suitability of proposed system at practical operating conditions is demonstrated through simulation results using MATLAB/ Simulink followed by an experimental validation.

KEYWORDS:

  1. BLDC motor
  2. SPV array
  3. Water pump
  4. Zeta converter
  5. VSI
  6. INC-MPPT

 

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1 Configuration of proposed SPV array-Zeta converter fed BLDC motor drive for water pumping system

EXPECTED SIMULATION RESULTS:

Fig.2 Performances of the proposed SPV array based Zeta converter fed BLDC motor drive for water pumping

system (a) SPV array variables, (b) Zeta converter variables, and (c) BLDC motor-pump variables.

 

CONCLUSION:

The SPV array-zeta converter fed VSI-BLDC motor-pump for water pumping has been proposed and its suitability has been demonstrated by simulated results using MATLAB/Simulink and its sim-power-system toolbox. First, the proposed system has been designed logically to fulfil the various desired objectives and then modelled and simulated to examine the various performances under starting, dynamic and steady state conditions. The performance evaluation has justified the combination of zeta converter and BLDC motor drive for SPV array based water pumping. The system under study availed the various desired functions such as MPP extraction of the SPV array, soft starting of the BLDC motor, fundamental frequency switching of the VSI resulting in a reduced switching losses, reduced stress on IGBT switch and the components of zeta converter by operating it in continuous conduction mode and stable operation. Moreover, the proposed system has operated successfully even under the minimum solar irradiance.

REFERENCES:

  • Uno and A. Kukita, “Single-Switch Voltage Equalizer Using Multi- Stacked Buck-Boost Converters for Partially-Shaded Photovoltaic Modules,” IEEE Transactions on Power Electronics, no. 99, 2014.
  • Arulmurugan and N. Suthanthiravanitha, “Model and Design of A Fuzzy-Based Hopfield NN Tracking Controller for Standalone PV Applications,” Electr. Power Syst. Res. (2014). Available: http://dx.doi.org/10.1016/j.epsr.2014.05.007
  • Satapathy, K.M. Dash and B.C. Babu, “Variable Step Size MPPT Algorithm for Photo Voltaic Array Using Zeta Converter – A Comparative Analysis,” Students Conference on Engineering and Systems (SCES), pp.1-6, 12-14 April 2013.
  • Trejos, C.A. Ramos-Paja and S. Serna, “Compensation of DC-Link Voltage Oscillations in Grid-Connected PV Systems Based on High Order DC/DC Converters,” IEEE International Symposium on Alternative Energies and Energy Quality (SIFAE), pp.1-6, 25-26 Oct. 2012.
  • K. Dubey, Fundamentals of Electrical Drives, 2nd ed. New Delhi, India: Narosa Publishing House Pvt. Ltd., 2009.

Using “STF-PQ” Algorithm and Hysteresis Current Control in Hybrid Active Power Filter to Eliminate Source Current Harmonic

ABSTRACT:

According to importance of power quality in power network, improvement of compensator equipment and ways of efficiency increasing can reduces destroyer effect on network. Active power filters as more importance and finance in network and industrial has depended detector algorithm and switching technique. This paper presents a novel algorithm (STF-PQ). This algorithm base on harmonic extract is divided into two parts as feedback loop and feed forward loop. Then, the hysteresis current control has been used to produce the switching pattern. A comparison between PWM and hysteresis current control has been performed that shows the efficiency and simplicity of hysteresis current control. Simulation of this filter has been done in Matlab/Simulink to prove the good performance of STF-PQ and hysteresis current control in hybrid filters.

KEYWORDS:

  1. Hybrid active power filters
  2. Self tuning filter
  3. Hystrsis current control
  4. Matlab/Simulink

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

 

 

Fig.1 Parallel hybrid active filter configuration

 EXPECTED SIMULATION RESULTS:

 

 

Fig.2 simulation Results

CONCLUSION:

According to development of power systems in industrial such as UPS, speed control of electrical machine, electrical furnace, computers and non-linear load that cause increasing of harmonic in network, Undesirable effect of harmonic is one of power transfer problem. This is why of standard codifying on THD limitation. Thus, it is necessary to detect and remove it until under permit limit. In this paper a novel algorithm of “STF-PQ” has been proposed to detect harmonics in power system. Then hysteresis current control has been used to make the reference current due to its simplicity and high accuracy. The comparison between PWM and hysteresis proves that use of PWM has more complexity and calculation to generate pulses. Simulation results show the efficiency of this power filter in harmonic elimination.

REFERENCES:

[1] J. C. Das,” Passive filters- Potentialities and limitations” IEEETransactions on industry applications, vol. 40, pp. 345-362, (2004).

[2] Park, J-h. Sung and K. Nam,” A New parallel hybrid filter configuration minimizing active filter size” IEEE/PESC Ann. Meeting Conf, vol. 1, pp.400-405 (1999)

[3] B. N. Singh, Bhim Singh, A. Chandra and K. Al-Haddad,” Digital implementation of new type of hybrid filter with simplified control strategy” Conference Proceeding IEEE-APEC 99., vol 1, pp. 642- 648 (1999)

[4] H. Fujita, and H. Akagi,” A practical approach to harmonic compensatreion in power systems-Series connection of passive and shunt active filters,” IEEE Trans. Ind. Appl, vol 27, pp. 1020-1025 (1991)

[5] Michael John Newman, Daniel Nahum Zmood , Donald Grahame Holmes,” Stationary Frame Harmonic Reference Generation for Active Filter Systems”, IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 38, NO. 6, NOVEMBER/DECEMBER 2002