Powеr Quality Improvement In Powеr Systеm By Using SVPWM Based Static Synchronous Sеriеs Compеnsator

ABSTRACT:  

Power quality improvement is an important issue in power system. Flexible AC Transmission (FACTS) devices are commonly used for solving problems related to power quality and improving it. In this paper a synchronous static series compensator (SSSC) is used for control and modulation of power flow in a transmission line. The Pulse Width Modulation (PWM) and SVPWM control techniques are employed in SSSC. The active performance of SSSC is evaluated using Matlab/Simulink environment. The simulation results validate that the power quality is enhanced properly using SSSC.

KEYWORDS:

1.      Power Quality

2.      FACTS

3.      PWM

4.      SVPWM

5.      SSSC

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Figure 1. Functional model of SSSC.

 EXPECTED SIMULATION RESULTS:

Figure 2. (a) Source voltage (b) Source current without SSSC.

Figure 3. (a) Load voltage (b) Load current without SSSC.

Figure 4. (a) Source voltage (b) Source current with SSSC.

Figure 5. (a) Load voltage (b) Load current with SSSC.

Figure 6. (a) Source voltage (b) Source current with SVPWM SSSC.

Figure 7. (a) Load voltage (b) Load current with SVPWM SSSC.

Figure 8. FFT analysis of (a) Source voltage (b) Source current-without SSSC.

Figure 9. FFT analysis of (a) Load voltage (b) Load current –without SSSC.

Figure 10. FFT analysis of (a) Source voltage (b) Source current with SSSC.

Figure 11. FFT analysis of (a) Load voltage (b) Load current with SSSC.

Figure 12. FFT analysis of (a) source voltage and (b) source current using SVPWM SSSC.

Figure 13. FFT analysis of (a) Load voltage and (b) Load current using SVPWM SSSC.

CONCLUSION:

In this paper the problem of modulation and control of power flow in transmission line is carried out by using SSSC with PWM and SVPWM techniques. The performance of SSSC is validated using Matlab/Simulink software. Thus, simulation results and THD analysis shows that by using SVPWM based SSSC power quality gets improved more as compared to the SPWM based SSSC. Hence SVPWM technique proves better as compared to that of the SPWM technique for power quality improvement.

REFERENCES:

[1] N.G. Hingorani and L. Gyugyi, “Undеrstanding FATCS concеpts andtеchnology of flеxiblе ac transmission systеm”,Nеw York, NY: IЕЕЕ prеss, 2000.

[2] “Static Synchronous Compensator,” CIGRE, Working group 14.19, 1998.

[3] Laszlo Gyugyi, Colin D. Schaudеr, and Kalyan K. Sеn, “static synchronous sеriеs compеnsator: a solid-statе approach to thе sеriеs compеnsation of transmission linеs”, IЕЕЕ Transactions on powеr dеlivеry, Vol. 12, No. 1, January 1997.

[4] Vaishali M. Morе, V.K. Chandrakar, “Powеr systеm pеrformancеs improvеmеnt by using static synchronous sеriеs compеnsator”, intеrnational confеrеncе on Advancеs in Еlеctrical, Еlеctronics,Informantion, Communication and Bio-Informatics 978-1-4673-9745-2©2016 IЕЕЕ.

[5] M. Farhani, “Damping of subsynchronous oscillations in powеr systеm by using static synchronous sеriеs compеnsator”,IЕT Gеnr. Distrib.vol.6.Iss.6.pp.539-544,2012.

Distributed Cooperative Control and Stability Analysis of Multiple DC Electric Springs in a DC Microgrid

ABSTRACT:  

Recently, dc electric springs (dc-ESs) have been proposed to realize voltage regulation and power quality improvement in dc microgrids. This paper establishes a distributed cooperative control framework for multiple dc- ESs in a dc microgrid and presents the small-signal stability  analysis of the system. The primary level implements a droop control to coordinate the operations of multiple dc-ESs. The secondary control is based on a consensus algorithm to regulate the dc-bus voltage reference, incorporating  the state-of-charge (SOC) balance among dc-ESs. With the design, the cooperative control can achieve average dc-bus voltage consensus and maintain SOC balance among different dc-ESs using only neighbor-to-neighbor  information. Furthermore, a small-signal model of a four dc-ESs system with the primary and secondary controllers is developed. The eigenvalue analysis is presented to show   the effect of the communication weight on system stability. Finally, the effectiveness of the proposed control scheme and the small-signal model is verified in an islanded dc microgrid under different scenarios through simulation and  experimental studies.

KEYWORDS:

1.      Consensus

2.      Dc microgrid

3.      Distributed control

4.      Electric springs (ES)

5.      Small-signal stability

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

Fig.1.distributed network with multiple dc -ESs

 EXPECTED SIMULATION RESULTS:

Fig. 2.SEZ. Controller comparison. (a) Node bus voltage, (b) dc-ESs output

power, (c) SOC, and (d) state variables xi .

Fig. 3. Proposed controller with different aij . (a) and (d) Average  bus voltages with aij = 0.5 and aij = 10. (b) and (e) State variables with aij = 0.5 and aij = 10. (c) and (f) Bus voltages with aij = 0.5  and aij = 10.

Fig. 4. dc-ES4 failure at 5 s. (a) Node bus voltage, (b) output power,  and (c) SOC.

Fig. 5. Proposed controller with communication delay τ . (a) Node bus  average voltage, (b) SOC, and (c) state variables xi .

Fig. 6. Proposed controller with five dc-ESs. (a) Node bus voltage, (b) output power, and (c) SOC.

CONCLUSION:

A hierarchical two-level voltage control scheme was proposed for dc-ESs in a microgrid using the consensus algorithm to estimate the average dc-bus voltage and promote SOC balance among different dc-ESs. The small-signal model of four dc-ESs system incorporating the controllers was developed for eigenvalues analysis to investigate the stability of the system. The consensus of the observed average voltages and the defined state variables has been proven. Results show that the control can improve the voltage control accuracy of dc-ESs and realize power sharing in proportion to the SOC. The resilience of the system against the link failure has been improved and the system can still maintain operations as long as the remaining communication graph has a spanning tree. Simulation and experimental results also verify that the correctness and effectiveness of the proposed model and controller strategy.

REFERENCES:

[1] X. Lu, K. Sun, J. M. Guerrero, J. C. Vasquez, and L. Huang, “State-ofcharge balance using adaptive droop control for distributed energy storage systems inDCmicrogrid applications,” IEEE Trans. Ind. Electron., vol. 61, no. 6, pp. 2804–2815, Jun. 2014.

[2] Q. Shafiee, T. Dragicevic, J. C. Vasquez, and J. M. Guerrero, “Hierarchical control for multiple DC-microgrids clusters,” IEEE Trans. Energy Convers., vol. 29, no. 4, pp. 922–933, Dec. 2014.

[3] W. Yao, M. Chen, J. Matas, J. M. Guerrero, and Z. M. Qian, “Design and analysis of the droop control method for parallel inverters considering the impact of the complex impedance on the power sharing,” IEEE Trans. Ind. Electron., vol. 58, no. 2, pp. 576–588, Feb. 2011.

[4] V. Nasirian, S. Moayedi, A. Davoudi and F. Lewis, “Distributed cooperative control of DC microgrids,” IEEE Trans. Power Electron., vol. 30, no. 4, pp. 6725–6741, Dec. 2014.

[5] J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicu˜na, and M. Castilla, “Hierarchical control of droop-controlledAC andDCmicrogrids—A general  approach toward standardization,” IEEE Trans. Ind. Electron., vol. 58, no. 1, pp. 158–172, Jan. 2011.

Mitigating Distribution Power Loss of DC Microgrids with DC Electric Springs

 ABSTRACT:  

 DC microgrids fed with substantial intermittent renewable energy sources (RES) face the immediate problem of power imbalance and the subsequent DC bus voltage fluctuation problem (that can easily breach power system standards). It has recently been demonstrated that DC electric springs (DCES), when connected with series non-critical loads, are capable of stabilizing the voltage of local nodes and improving the power quality of DC microgrids without large energy storage. In this paper, two centralized model predictive control (CMPC) schemes with (i) non-adaptive weighting factors and (ii) adaptive weighting factors are proposed to extend the existing functions of the DCES in the microgrid. The control schemes coordinate the DCES to mitigate the distribution power loss in the DC microgrids, while simultaneously providing their original function of DC bus voltage regulation. Using the DCES model that was previously validated with experiments, simulations based on MATLAB/SIMULINK platform are conducted to validate the control schemes. The results show that with the proposed CMPC schemes, the DCES are capable of eliminating the bus voltage offsets as well as reducing the distribution power loss of the DC microgrid.

KEYWORDS:

1.      DC microgrids

2.      DC electric springs (DCES)

3.      Centralized model predictive control (CMPC)

4.      Non-adaptive weighting factors

5.      Adaptive weighting factors

6.      Distribution power loss

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

Fig. 1. An m-bus DC microgrid with n RES units.

EXPECTED SIMULATION RESULTS:

Fig. 2. Waveforms of the power supply by RES and the bus voltages of the DC microgrid without DCES.

Fig. 3. Waveforms of the bus voltages of the DC microgrid when the DCES is installed at the five buses.

    

Fig. 4. Waveforms of the bus voltages of the DC microgrid with three DCES installed at bus 1, bus 4 and bus 5.

Fig. 5. The comparisons of the power loss on the distribution lines between α=1 and α=0.9 when three DCES are installed.

Fig. 6. Waveforms of the bus voltages of the DC microgrid with four DCES installed at bus 1, bus 2, bus 4 and bus 5.

Fig. 7. Comparisons of the power loss on the distribution lines for different values of α when four DCES are installed.

CONCLUSION:

DC electric springs (DCES) is an emerging technology that can be used to stabilize and improve the power quality of DC microgrids. In this paper, a centralized model predictive control (CMPC) with both non-adaptive weighting factors and adaptive weighting factors is proposed for multiple DCES to further mitigate the power loss on the distribution lines of a DC microgrid. Using a DCES model previously verified with experiments, simulation studies have been conducted for a DC microgrid setup. Simulation results on a 48 V five-bus DC microgrid show that the energy is saved about 49.4% in the 5 seconds when three DCES are controlled by the CMPC with non-adaptive weighting factors and is saved about 58.5% in the 5 seconds when four DCES are controlled by the CMPC with non-adaptive weighting factors. It is also demonstrated that the power loss on the distribution lines of the DC microgrid can be further reduced by the CMPC with adaptive weighting factors, as compared to the CMPC with non-adaptive weighting factors.

REFERENCES:

[1] B. C. Beaudreau, World Trade: A Network Approach, iUniverse, 2004.

[2] G. Neidhofer, “Early three-phase power,” IEEE Power and Energy Magazine, vol. 5, no. 5, pp.88−100, Sep. 2007.

[3] R. H. Lasseter and P. Paigi, “Microgrid: a conceptual solution,” in Proc. IEEE Power Electron. Spec. Conf., 2004, pp. 4285−4290.

[4] S. Anand, B. Fernandes, and J. Guerrero, “Distributed control to ensure proportional load sharing and improve voltage regulation in low-voltage dc microgrids,” IEEE Tran. Pow. Elect., vol. 28, no. 4, Aug. 2012.

[5] T. Gragicevic, X. Lu, J. C. Vasquez, and J. M. Guerrero, “DC microgrids−part I: a review of control strategies and stabilization techniques,” IEEE Trans. Pow. Elect., vol. 31, no. 7, Jul. 2016.