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Friday, 20 January 2017

Control Scheme for a Stand-Alone Wind Energy Conversion System

ABSTRACT
Present energy need heavily relies on the conventional sources. But the limited availability and steady increase in the price of conventional sources has shifted the focus toward renewable sources of energy. Of the available alternative sources of energy, wind energy is considered to be one of the proven technologies. With a competitive cost for electricity generation, wind energy conversion system (WECS) is nowadays deployed formeeting both grid-connected and stand-alone load demands. However, wind flow by nature is intermittent. In order to ensure continuous supply of power suitable storage technology is used as backup. In this paper, the sustainability of a 4-kW hybrid of wind and battery system is investigated for meeting the requirements of a 3-kW stand-alone dc load representing a base telecom station. A charge controller for battery bank based on turbine maximum power point tracking and battery state of charge is developed to ensure controlled charging and discharging of battery. The mechanical safety of the WECS is assured by means of pitch control technique. Both the control schemes are integrated and the efficacy is validated by testing it with various load and wind profiles in MATLAB/SIMULNIK.

KEYWORDS
1.      Maximum power point tracking (MPPT)
2.       Pitch control
3.      State of charge (SoC)
4.      Wind energy conversion system (WECS).

SOFTWARE: Matlab/Simulink

BLOCK DIAGRAM:

Fig. 1. Layout of hybrid wind–battery system for a stand-alone dc load.

SIMULATION RESULTS:


Fig. 2. (a) WT and (b) battery parameters under the influence of gradual variation of wind speed.



Fig. 3. (a)WT and (b) battery parameters under the influence of step variation of wind speed.


Fig. 4. (a) WT and (b) battery parameters under the influence of arbitrary variation of wind speed.


CONCLUSION
The power available from a WECS is very unreliable in nature. So, a WECS cannot ensure uninterrupted power flow to the load. In order to meet the load requirement at all instances, suitable storage device is needed. Therefore, in this paper, a hybrid wind-battery system is chosen to supply the desired load power. To mitigate the random characteristics of wind flow the WECS is interfaced with the load by suitable controllers. The control logic implemented in the hybrid set up includes the charge control of battery bank using MPPT and pitch control of the WT for assuring electrical and mechanical safety. The charge controller tracks the maximum power available to charge the battery bank in a controlled manner. Further it also makes sure that the batteries discharge current is also within the C/10 limit. The current programmed control technique inherently protects the buck converter from over current situation. However, at times due to MPPT control the source power may be more as compared to the battery and load demand. During the power mismatch conditions, the pitch action can regulate the pitch angle to reduce the WT output power in accordance with the total demand. Besides controlling the WT characteristics, the pitch control logic guarantees that the rectifier voltage does not lead to an overvoltage situation. The hybrid wind-battery system along with its control logic is developed in MATLAB/SIMULINK and is tested with various wind profiles. The outcome of the simulation experiments validates the improved performance of the system.

REFERENCES
[1]   D. Sahin, “Progress and recent trends in wind energy,” Progress in Energy Combustion Sci., vol. 30, no. 5, pp. 501–543, 2004.
[2]   R. D. Richardson and G. M. Mcnerney, “Wind energy systems,” Proc. IEEE, vol. 81, no. 3, pp. 378–389, Mar. 1993.

[3]   R. Saidur, M. R. Islam, N. A. Rahim, and K. H. Solangi, “A review on global wind energy policy,” Renewable Sustainable Energy Rev., vol. 14, no. 7, pp. 1744–1762, Sep. 2010.

Friday, 6 January 2017

Tuesday, 20 December 2016

Active Power Factor Correction for Rectifier using Micro-controller



ABSTRACT:

 Industrialization increases the use of inductive load and hence power system loses its efficiency. Rigid occurrence of mains rectification circuits and the day by day increase in electronics consumers inside the electronic devices enhances the cause of mains harmonic distortion. Power is very precious in the present technological revolution and thus it requires to improve the power factor with a suitable method.This paper presents the simulation and the experimental results for active power factor correction system. Closed loop circuit is simulated in MATLAB using PI controller. The system has been implemented in MATLAB/SIMULINK environment.

KEYWORDS:

1.      Micro-controller
2.       Power factor correction system
3.       DC-DC boost converter
4.      Total harmonic distortion (THD)
5.      PI controller


SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:
Fig. 1. Circuit diagram of active power factor correction system


EXPECTED SIMULATION RESULTS:



             
Fig. 2. Input voltage of conventional converter in PSIM software





Fig. 3. Output voltage of conventional converter in PSIM software



Fig. 4. Output and input current waveform of conventional converter in PSIM software.







                                                        Fig. 5. Input current waveform at 15kHz in PSIM software

                                       


Fig. 6  Input voltage waveform at 15 kHz in PSIM software.


Fig. 7 . Output voltage waveform at 15kHz in PSIM software.


Fig. 8. Input current waveform in PSIM software.



Fig. 9. Input voltage waveform in PSIM software



Fig. 10. Output voltage waveform in PSIM software.



Fig. 11. Firing pulse for MOSFET IRF640 captured in DSO.



Fig. 12. Input current and voltage waveform captured in DSO.


 CONCLUSION:
Analog firing circuit designing makes circuit complex and also it requires the maintenance. Employing microcontroller instead reduces all its disadvantages thus being economical. It is easier to design with precision output. It was very interesting and absorbing to design AC-DC converter in the power electronics laboratory using power MOSFET IRF640.The design is adequate for many purposes. These improvements have been tested in principle, but some detailed work remains to be done in this area. This research work can be extended for the speed control of the motor using PI controller or fuzzy logic controller, Maximum Power Point Tracking (MPPT) using this circuit can be studied later on.

 REFERENCES:

[1] B.K.Bose, “Modern power electronics and AC Drives”, PHI,2001 .
[2] P.C.Sen, “Power Electronics”, Tata McGraw Hill Publishers, 4th edition, 1987.
[3] N.Mohan, T.M.Undeland, W.P.Robbins, “Power Electronics: Converters application and Design”, New York: Wiley, 3rd edition, 2006.
[4] Mohammed E. El-Hawary, “Principles of Electric Machines with Power Electronic Applications”, Wiley India, 2nd edition, 2011.
[5] Gayakwad, “Operational Amplifier”, Prentice Hall of India, 2009.




Monday, 19 December 2016

Power Management Strategy for a Multi-Hybrid Fuel Cell/Energy Storage Power Generation Systems


 ABSTRACT:
This paper depicts a new configuration for modular hybrid power conversion systems, namely, multi-hybrid generation system (MHGS), and parallel connection at the output, such that the converter of each unit shares the load current equally. This is a significant step towards realizing a modular power conversion system architecture, where smaller units can be connected in any series/parallel grouping to realize any required unit specifications. The supercapacitor (SC) as a complementary source is used to compensate for the slow transient response of the fuel cell (FC) as a main power source. It assists the Fe to meet the grid power demand in order to achieve a better performance and dynamic behavior. Reliable control of the proposed MHGS with multiple units is also a challenging issue. In this paper, a simple control method to achieve active sharing of load current among MHGS modules is proposed. The simulation results verify the performance of the proposed structure and control scheme.

KEYWORDS:

1.      Multi-hybrid generation system (MHGS)
2.      Fuel cell (FC)
3.       Dc/dc converter
4.       Supercapacitor (SC)
5.       Average load sharing (ALS)

SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:




Figure 1. Configuration of the FC/SC hybrid system.


CONTROL SYSTEM:




Figure 2. Proposed control strategy of hybrid FC/SC power conversion
.


 EXPECTED SIMULATION RESULTS:





Figure 3. Dynamic response of MHGS, (a) load active power, (b) output power of hybrid units, (c) FC stack and SC module power of first hybrid umt, and (d) FC stack and SC module power of second hybrid unit.




Figure 4. Output waveform of (a) dc bus voltage, and (b) dc bus current.




Figure 5. Waveforms of unit's (a) hydrogen input flow, (b) hydrogen partial
pressure, and (d) oxygen partial pressure.



CONCLUSION:

This paper proposes a comprehensive and effective multihybrid FC/SC power generation system structure and control strategy. The detailed model of the modular FC/SC hybrid system which includes an FC stack as a main power source and an SC as a complementary source is presented. In order to balance power sharing among the units, average load sharing technique is used. Elimination of outer voltage loop of ALS technique enhances reliability and reduces the complexity of the control structure. To show the superior dynamic behavior and power sharing of the proposed MHGS, results for two parallel hybrid systems are provided. The presented analysis and the simulation results offer a valuable structure with an effective control strategy to enhance power quality and management. These performances allow the integration MHGS into complex distributed generation systems such as microgrids.

REFERENCES:

[1] P. Chiradeja and R. Ramakumar, "An approach to quantify the technical benefits of distributed generation," IEEE Trans. Energy Convers., voL 19,no. 4,pp. 764-773,Dec,2004.
[2] B. Wojszczyk, R. Uluski, and F. Katiraei, 'The role of distributed generation and energy storage in utilities of the future," in Proc. IEEE PES Gen. Meet., 2008, pp. 1-2.
[3] K. Rajashekara, "Hybrid fuel-cell strategies for clean power generation," IEEE Trans. Ind Appl., voL 41, no. 3, pp. 682-689, May/Jun. 2005.
[4] 1. M. Carrasco, L. G. Franquelo, 1. T. Bialasiewicz, E. Galvan, R. C. PortilloGuisado, M. A M. Prats, 1. L Leon, and N.Moreno-Alfonso, "Power-electronic systems for the grid integration of renewable energy sources: A survey," IEEE Trans. Ind Electron., voL 53, no. 4, pp. 1002- 1016, Jun. 2006.

[5] Z. Jiang, and R. A Dougal, "A compact digitally controlled fuel cell/battery hybrid power source," IEEE Trans. Ind Electron., voL 53, no. 4,pp. 1094-1104,Jun. 2006. 

Performance Analysis of P&O and Incremental Conductance MPPT Algorithms Under Rapidly Changing Weather Conditions



ABSTRACT:

In this paper, the comparative analysis of two maximum power point tracking (MPPT) algorithms namely Perturb and Observe (P&O) and Incremental conductance (InC) is presented for the Photo-Voltaic (PV) power generation system. The mathematical model of the PV array is developed and transformed into MATLAB/Simulink environment. This model is used throughout the paper to simulate the PV source characteristics identical to that of a 20 Wp PV panel. The MPPT algorithms generate proper duty ratio for interfacing dc-dc boost converter driving resistive load. The performances of these algorithms are evaluated at gradual and rapidly changing weather conditions where it is observed that InC method tracks the rapidly changing insolation level at a faster rate as compared to P&O. Depending upon the prevailing environmental conditions the MPPT algorithms finds a unique operating point to track the maximum available power. The algorithms find a fixed duty ratio by comparing the previous power, voltage and current thereby optimizing the power output of the panel. The main objective is to compare the tracking capability and stability of the algorithms under different environmental situations on par with other real world tests.

KEYWORDS:

1.      Maximum Power Point Tracking (MPPT)
2.       Photovoltaic (PV)
3.      DC-DC Boost Converter
4.      Perturb & Observe (P&O)
5.       Incremental Conduction (InC)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:


 Fig. 1. PV Panel Interfaced with Boost Converter for MPP Tracking


 EXPECTED SIMULATION RESULTS:



Fig. 2. Experimental Measured PV Characteristics





Fig. 3. Experimental Results showing Source Voltage, Load Voltage and Duty Ratio




 Fig. 4. Performances of P&O and InC under slowly changing climatic conditions (a)
Irradiations Levels (b), (c) & (d) Duty ratio (e) Panel Voltage (f) Panel Power (g)
Oscillations in Duty by the algorithms



Fig. 5. Performances of P&O and InC under rapidly changing climatic conditions (a)
Insolations (b)& (c) Duty ratio (d)&(e) Panel Voltage (f) Panel Power




CONCLUSION:

The presented studies in this paper were the comparative analysis of two MPPT algorithms, Perturb & Observe and Incremental Conductance and conducted through boost converter. The simulation results prove positively that the P&O and the Incremental Conductance MPPTs reach the intended maximum power point. In the slowly changing whether both algorithms perform without significantly changes. It has observed that the Incremental Conductance reaches at the MPP three times faster than P&O in all cases and shows better performance for rapid changes and a better stability when the MPP is achieved. It has observed that P&O shows oscillations around the MPP when it reaches in steady state position which results in some power loss. But in case of InC there are no additional oscillations at steady state condition. However the P&O MPPT are mostly used in practice due to their simplicity. The originality and the specificity of the presented results obtain during this research reside in the fact that external parameters as irradiation and fixed temperature were introduced, at first as linear functions (ramp input) and, at second as random (step input) ones describing more closely the actual applicative conditions. The effect of the changing weather on the voltage and power of the PV panel according to change in MPP has shown in the results section.

REFERENCES:

[1] Tariq, J. Asghar, “Development of an Analog Maximum Power Point Tracker for Photovoltaic Panel”, PEDS. International Conference on, 2005, vol. 1, no., pp. 251, 255.
[2] H. Al-Bahadili, H. Al-Saadi, R. Al-Sayed, M.A.-S. Hasan, “Simulation of maximum power point tracking for photovoltaic systems”, Applications of Information Technology to Renewable Energy Processes and Systems (IT-DREPS), 1st International Conference & Exhibition on the , 2013, vol., no., pp. 79,84.
[3] Lu Yuan, Cui Xingxing, “Study on maximum power point tracking for photovoltaic power generation system”, Computer Science and Information Technology (ICCSIT), 3rd IEEE International Conference on, 2010, vol. 9, pp. 180,183.
[4] G. Walker, “Evaluating MPPT converter topologies using a MATLAB PV model”, Journal of Electrical & Electronics Engineering, 2001, Australia, IEAust, vol. 21, No. 1, pp. 49-56.

[5] Beriber, D.; Talha, A, "MPPT techniques for PV systems," Power Engineering, Energy and Electrical Drives (POWERENG), 2013 Fourth International Conference on, vol., no., pp.1437, 1442, 13-17 May 2013.