Engineering projects for final year students

Engineering projects for final year students

Electrical engineering is a field of engineering that generally deals with the study and application of electricity, electronics, and electromagnetism. This field first became an identifiable occupation in the later half of the 19th century after commercialization of the electric telegraph, the telephone, and electric power distribution and use. Subsequently, broadcasting and recording media made electronics part of daily life. The invention of the transistor, and later the integrated circuit, brought down the cost of electronics to the point they can be used in almost any household object.

Electrical engineering has now subdivided into a wide range of subfields including electronics, digital computers, power engineering, telecommunications, control systems, radio-frequency engineering, signal processing, instrumentation, and microelectronics. Many of these subdisciplines overlap and also overlap with other engineering branches, spanning a huge number of specializations such as hardware engineering, power electronics, electromagnetics & waves, microwave engineering, nanotechnology, electrochemistry, renewable energies, mechatronics, electrical materials science, and many more.

Electrical engineers typically hold a degree in electrical engineering or electronic engineering. Practicing engineers may have professional certification and be members of a professional body. Such bodies include the Institute of Electrical and Electronics Engineers (IEEE) and the Institution of Engineering and Technology (professional society) (IET).

Electrical engineers work in a very wide range of industries and the skills required are likewise variable. These range from basic circuit theory to the management skills required of a project manager. The tools and equipment that an individual engineer may need are similarly variable, ranging from a simple voltmeter to a top end analyzer to sophisticated design and manufacturing software.

 

Hybrid Active Filter with Variable Conductance for Harmonic Resonance Suppression in Industrial Power Systems

 

ABSTRACT:

Unintentional series and/or parallel resonances, due to the tuned passive filter and the line inductance, may result in severe harmonic distortion in the industrial power system. This paper presents a hybrid active filter to suppress harmonic resonance and to reduce harmonic distortion. The proposed hybrid filter is operated as variable harmonic conductance according to the voltage total harmonic distortion; therefore, harmonic distortion can be reduced to an acceptable level in response to load change or parameter variation of the power system. Since the hybrid filter is composed of a seventh-tuned passive filter and an active filter in series connection, both dc voltage and kVA rating of the active filter are dramatically decreased compared with the pure shunt active filter. In real application, this feature is very attractive since the active power filter with fully power electronics is very expensive. A reasonable tradeoff between filtering performances and cost is to use the hybrid active filter. Design consideration are presented, and experimental results are provided to validate effectiveness of the proposed method. Furthermore, this paper discusses filtering performances on line impedance, line resistance, voltage unbalance, and capacitive filters.

 KEYWORDS:

  1. Harmonic resonance
  2. Hybrid active filter
  3. Industrial power system

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

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Fig. 1. Proposed HAFU in the industrial power system and its associated control. (a) Circuit diagram of the HAFU. (b) Control block diagram of the HAFU.

EXPECTED SIMULATION RESULTS:

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Fig. 2. Line voltage e, source current is, load current iL, and filter current i in the case of NL1 initiated. X-axis: 5 ms/div. (a) HAFU is off. (b) HAFU is on.

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Fig. 3. Line voltage e, source current is, load current iL, and filter current i in the case of NL2 initiated. X-axis: 5 ms/div. (a) HAFU is off. (b) HAFU is on.

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Fig. 4. Transient response when the nonlinear load is increased at T. (a)Waveforms of vdc, Voltage THD, G*. X-axis: 100 ms/div; Y -axis: vdc (V), G* (1.21 p.u./div), and THD (1.25%/div). (b) Current waveforms.

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Fig. 5. HAFU is off for single-phase nonlinear load. (a) Terminal voltage. (b) Source current. (c) Filter current. (d) Load current.

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Fig. 6. HAFU is on for single-phase nonlinear load. (a) Terminal voltage. (b) Source current. (c) Filter current. (d) Load current.

CONCLUSION:

 This paper presents a hybrid active filter to suppress harmonic resonances in industrial power systems. The proposed hybrid filter is composed of a seventh harmonic-tuned passive filter and an active filter in series connection at the secondary side of the distribution transformer. With the active filter part operating as variable harmonic conductance, the filtering performances of the passive filter can be significantly improved. Accordingly, the harmonic resonances can be avoided, and the harmonic distortion can be maintained inside an acceptable level in case of load changes and variations of line impedance of the power system. Experimental results verify the effectiveness of the proposed method. Extended discussions are summarized as follows.

  • Large line inductance and large nonlinear load may result in severe voltage distortion. The conductance is increased to maintain distortion to an acceptable level.
  • Line resistance may help reduce voltage distortion. The conductance is decreased accordingly.
  • For low line impedance, THD* should be reduced to enhance filtering performances. In this situation, measuring voltage distortion becomes a challenging issue.
  • High-frequency resonances resulting from capacitive filters is possible to be suppressed by the proposed method.
  • In case of unbalanced voltage, a band-rejected filter is needed to filter out second-order harmonics if the SRF is realized to extract voltage harmonics.

 REFERENCES:

  [1] R. H. Simpson, “Misapplication of power capacitors in distribution systems with nonlinear loads-three case histories,” IEEE Trans. Ind. Appl., vol. 41, no. 1, pp. 134–143, Jan./Feb. 2005.

[2] T. Dionise and V. Lorch, “Voltage distortion on an electrical distribution system,” IEEE Ind. Appl. Mag., vol. 16, no. 2, pp. 48–55, Mar./Apr. 2010.

[3] E. J. Currence, J. E. Plizga, and H. N. Nelson, “Harmonic resonance at a medium-sized industrial plant,” IEEE Trans. Ind. Appl., vol. 31, no. 4, pp. 682–690, Jul/Aug. 1995.

[4] C.-J. Wu et al., “Investigation and mitigation of harmonic amplification problems caused by single-tuned filters,” IEEE Trans. Power Del., vol. 13, no. 3, pp. 800–806, Jul. 1998.

[5] B. Singh, K. Al-Haddad, and A. Chandra, “A review of active filters for power quality improvement,” IEEE Trans. Ind. Electron., vol. 46, no. 5, pp. 960–971, Oct. 1999.

 

 

Stability Enhancement of Wind Power System by using Energy Capacitor System

 

ABSTRACT:

This paper presents Permanent Magnet Synchronous generator (PMSG) based a variable speed wind turbine systems including energy capacitor system (ECS). The ECS is the combination of electric double layer capacitor (EDLC) known as super capacitor and power electronic devices for wind power application with its detailed modeling and control strategy which can supply smooth electrical power to the power grid and makes the system better stable and reliable. As generated power from wind fluctuates randomly, the objective of this control system is to select a line power reference level and to follow the reference level by absorbing or providing active power to or from ECS to smooth output power fluctuation penetrated to the grid and to keep the wind farm terminal voltage at a desired level by supplying necessary reactive power. The performance of the proposed system is investigated by simulation analysis using PSCAD/EMTDC software.

 KEYWORDS:

  1. Variable speed wind generator
  2. Permanent Magnet Synchronous generator (PMSG)
  3. Energy Capacitor System (ECS)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

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Fig. 1. Model System

EXPECTED SIMULATION RESULTS:

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Fig. 2. Response of real wind speed data [case-I]

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Fig. 3. Response of PMSG generated Active Power [case-I]

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Fig. 4. Grid terminal voltage without & with ECS [case-I]

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Fig. 5. Grid Power with/without EDLC and EDLC power [case-I]

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Fig. 6. Grid Active Power without and with EDLC [case-I]

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Fig. 7. EDLC active Power [case-I]

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Fig. 8. EDLC energy [case-I]

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Fig. 9. Comparison with SMA and ECS

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Fig. 10. Response of Wind speed [case-II]

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Fig. 11. PMSG generated Active Power [MW] [case-II]

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Fig. 12. Grid Active Power without and with EDLC [case-II]

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Fig. 13. EDLC active power [case-II]

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Fig. 14. EDLC energy [case-II]

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Fig. 15. Grid terminal voltage without & with ECS [case-II].

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Fig. 16. Frequency deviation of SMA, ECS & without ECS [case-I].

 CONCLUSION:

The simulation results show that the quality of the terminal voltage and output power penetrated to the grid is not good but continuously varying without ECS system. Besides, when we used ECS system, the terminal voltage and grid power is almost constant and quality of voltage and power is excellent. So, using ECS system smoothed power can be supplied to the grid by charging and discharging of EDLC. By using low pass filter to calculate line power reference instead of SMA, EMA makes the system very simple, compact and cost effective. Therefore, it can be concluded that this proposed system can be applied effectively in power systems to generate high quality electrical power from the natural fluctuating wind.

 REFERENCES:

[1] G. annual report, 2014; world wind energy association.

[2] Niu Jiangang, Baotou, “Investigation on the properties of fly ash concrete attacked by a Pseudo-capacitance Faradaic electrochemical storage with electron charge-transfer, achieved by redox reactions, intercalation or electrosorption. Rain,” IEEE, Conference, ICETCE, Lushan, DOI. 10, pp. 2335 – 2339, 22-24 April 2011.

[3] Harden F, Bleijis JAM, Jones R, Bromely P, Ruddell AJ, “Application of power-controlled flywheel drive for wind power conditioning in a wind /diesel power system,” Ninth international conference on Electrical Machines and Drives, Canterbury, paper no. 468, pp. 65-70.

[4] Senjyu T., Sakamoto R., Urasaki N., Funabashi T. Fujita H., SekineH.,“Output power leveling of wind turbine Generator for all operating regions by pitch angle control,” Energy Conversion, IEEE Transactions, Vol. 21, pp. 467 – 475, 2006.

[5] Ali MH, Murata T, Tamura J, “Minimization of fluctuations of line power and terminal voltage of wind generator by fuzzy logiccontrolled SMES,” international review of Electrical engineering, vol. 1, pp. 559-566, 2006.

 

 

 

 

Modeling and Simulation of a Stand-alone Photovoltaic System

 

 ABSTRACT:

In the future solar energy will be very important energy source. More than 45% of necessary energy in the world will be generated by photovoltaic module. Therefore it is necessary to concentrate our forces in order to reduce the application costs and to increment their performances. In order to reach this last aspect, it is important to note that the output characteristic of a photovoltaic module is nonlinear and changes with solar radiation and temperature. Therefore a maximum power point tracking (MPPT) technique is needed to track the peak power in order to make full utilization of PV array output power under varying conditions. This paper presents two widely-adopted MPPT algorithms, perturbation & observation (P&O) and incremental conductance (IC). These algorithms are widely used in PV systems as a result of their easy implementation as well as their low cost. These techniques were analyzed and their performance was evaluated by using the Matlab tool Simulink.

 

KEYWORDS:

  1. Photovoltaic system
  2. MPPT
  3. Perturbation and Observation
  4. Incremental conductance

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

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Fig. 1. Block diagram of the stand-alone PV system.

CIRCUIT DIAGRAM

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Fig. 2. Model of the photovoltaic module

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Fig. 3. Schematic diagram of a DC Buck-Boost converter.

 EXPECTED SIMULATION RESULTS:

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Fig. 4. Output current of PV module

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Fig. 5. Output voltage of PV module

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Fig. 6 Output power of PV module

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Fig. 7. Output current of MPPT+DC-DC converter

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Fig. 8. Output voltage of MPPT+DC-DC converter

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Fig. 9. Output power of MPPT+DC-DC converter

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Fig 10 : PV-Output power with and without MPPT+DC-DC converter

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Fig. 11. Output current of MPPT+DC-DC converter

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Fig. 12. Output voltage of MPPT+DC-DC converter

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Fig. 13. Output power of MPPT+DC-DC converter

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Fig. 14. PV-Output power with and without MPPT+DC-DC converter

CONCLUSION:

In this work, we presented a modeling and simulation of a stand-alone PV system. One-diode model for simulation of PV module was selected; Buck-Boost converter is studied and applied to test the system efficiency. Two Maximum Power Point Tracking techniques, P&O and IC, are presented and analyzed. The proposed system was simulated using the mathematical equations of each component in Matlab/Simulink. The simulation analysis shows that P&O method is simple, but has considerable power loss because PV module can only run in oscillation way around the maximum power point. IC method has more precise control and faster response, but has correspondingly higher hardware requirement. In practice, in order to achieve maximum efficiency of photovoltaic power generation, a reasonable and economical control method should be chosen. The following of this work is based on optimizing the performance of PV modules and stand-alone systems using more efficient algorithms to minimize the influence of the meteorological parameters on the PV energy production.

 REFERENCES:

[1] A.KH. Mozaffari Niapour, S. Danyali, M.B.B. Sharifian, M.R. Feyzi, “Brushless DC motor drives supplied by PV power system based on Zsource inverter and FL-IC MPPT controller”, Energy Conversion and Management 52, pp. 3043–3059, 2011.

[2] Reza Noroozian, Gevorg B. Gharehpetian, “An investigation on combined operation of active power filter with photovoltaic arrays”, International Journal of Electrical Power & Energy Systems, Vol. 46, Pages 392-399, March 2013.

[3] N. Femia, D. Granozio, G. Petrone, G. Spaguuolo, and M. Vitelli, “Optimized one-cycle control in photovoltaic grid connected applications”, IEEE Trans. Aerosp. Electron. Syst., Vol. 42, pp. 954- 972, 2006.

[4] T. L. Kottas, Y. S. Boutalis, and A. D. Karlis, “New maximum power point tracker for PV arrays using fuzzy controller in close cooperation with fuzzy cognitive net-work”, IEEE Trans. Energy Conv., Vol. 21, pp. 793–803, 2006.

[5] Mohamed A. Eltawil, Zhengming Zhao, “MPPT techniques for photovoltaic applications”, Renewable and Sustainable Energy Reviews, Vol. 25, P. 793-813, 2013.