Analysis of Active and Reactive Power Control of a Stand-Alone PEM Fuel Cell Power Plant

ABSTRACT:

This paper presents analytical details of how active and reactive power output of a stand-alone proton-exchange-membrane (PE M) fuel cell power plant (F C PP) is controlled. This analysis is based on an integrated dynamic model of the entire power plant including the reformer. The validity of the analysis is verified when the model is used to predict the response of the power plant to: 1) computer-simulated step changes in the load active and reactive power demand and 2) actual active and reactive load profile of a single family residence. The response curves indicate the load-following characteristics of the model and the predicted changes in the analytical parameters predicated by the analysis.

 

KEYWORDS:

  1. Active power control
  2. Fuel cell
  3. Fuel cell model,
  4. PEM fuel cell
  5. Proton exchange membrane (PEM)
  6. Reactive power.

 

BLOCK DIAGRAM:

Fig. 1. FCPP, inverter and load connection diagram.

 

EXPECTED SIMULATION RESULTS:

Fig. 2 Load step changes.

Fig. 3. FCPP output current.

Fig. 4. AC output voltage.

Fig. 5. Active output power.

Fig. 6. Reactive output power.

Fig.7 Output voltage phase angle.

Fig. 8. Hydrogen flow rate.

Fig. 9. AC output power.

Fig. 10. Active power of residential load.

Fig. 11. Reactive power of residential load.

Fig. 12 FCPP active power output.

Fig. 13. FCPP reactive power output.

                                                                                                                     CONCLUSION:

This paper introduces an integrated dynamic model for a fuel cell power plant. The proposed dynamic model includes a fuel cell model, a gas reformer model, and a power conditioning unit block. The model introduces a scenario to control active and reactive power output from the fuel cell power plant. The analysis is based on traditional methods used for the control of active and reactive power output of a synchronous generator. To test the proposed model, its active and reactive power outputs are compared with variations in load demand of a single family residence. The results obtained show a fast response of the fuel cell power plant to load changes and the effectiveness of the proposed control technique for active and reactive power output.

 

REFERENCES:

[1] M. A. Laughton, “Fuel cells,” Power Eng. J., vol. 16, no. 1, pp. 37–47, Feb. 2002.

[2] S. Um et al., “Computational fluid dynamics modeling of proton exchange membrane fuel cell,” J. Power Electrochem. Soc., vol. 147, no. 12, pp. 4485–4493, 2000.

[3] D. Singh et al., “A two-dimension analysis of mass transport in proton exchange membrane fuel cells,” Int. J. Eng. Sci., vol. 37, pp. 431–452, 1999.

[4] J. C. Amphlett et al., “A model predicting transient response of proton exchange membrane fuel cells,” J. Power Sources, vol. 61, pp. 183–188, 1996.

[5] J. Padulles et al., “An integrated SOFC plant dynamic model for power systems simulation,” J. Power Sources, vol. 86, pp. 495–500, 2000.

A Simple Active and Reactive Power Control for Applications of Single-Phase Electric Springs

ABSTRACT

Aiming at effective power management in microgrids with high penetration of renewable energy sources (RESs), the paper proposes a simple power control for the so-called second-generation, single-phase electric springs (ES-2), that overcomes the shortcomings of the existing ES control methods. By the proposed control, the unpredictable power generated from RESs is divided into two parts, i.e. the one absorbed by the ES-2 that still varies and the other injected into the grid that turns to be controllable, by a simple and accurate signal manipulation that works both at steady-state and during RES transients. It is believed that such a control is suitable for the distributed power generation, especially at domestic homes.  In the paper, the proposed control is supported by a theoretical background. Its effectiveness is at first validated by simulations and then by experiments. To this purpose, a typical RES application is considered, and an experimental setup is arranged, built up around an ES-2 implementing the proposed control. Testing of the setup is carried out in three steps and proves not only the smooth operation of the ES-2 itself, but also its capability in running the application properly.

 

KEYWORDS

  1. Electric spring
  2. Smart load
  3. Microgrids
  4. Power control
  5. Grid connected
  6. Distributed generation.

 

SOFTWARE: MATLAB/SIMULINK

 

CIRCUIT DIAGRAM

Fig. 1. Topology of ES-2 and associated circuitry.

 

EXPECTED SIMULATION RESULTS

Fig. 2 Simulation waveforms under different variations of the input active power. (a) From 1.6kW to 1.1kW and then back to 1.6kW @ VG=230V. (b) From 8kW to 2kW and then back to 8kW @ VG=200V. (c) From 8kW to 4kW and then to 2kW @ VG=200V..

Fig. 3. Transient ES-2 responses to a change of the line voltage with Pinref=1.5kW. (a) From 240V to 210V. (b) From 210V to 240V

Fig. 4. Simulation waveforms before and after grid distortion. (a) Results of PLL. (b) Results of active and reactive power of ES system.

 

CONCLUSION

The input active and reactive power control is proposed for the purpose of practical application of ES-2 in this paper. An overall review and analysis have been done on the existing control strategies such as δ control and RCD control, revealing that the essences of the controls on ES-2 are to control the input active power and reactive power. If being equipped together with the distributed generation from RESs, the ES-2 can manage the fluctuated power and make sure the controllable power to grid, which means that the ES-2 is able to deal with the active power captured by MPPT algorithm. Simulations have been done on the steady and transient analysis and also under the grid anomalies, validating the effectiveness of the proposed control. Three steps have been set in the experiments to verify the three typical situations and namely the active power generated by the GCC from RESs are, 1) more than; 2) less than; 3) the same as the load demand. Tested results have validated the proposed control.

 

REFERENCES

  • Cheng and Y. Zhu, “The state of the art of wind energy conversion systems and technologies: Areview,” Energy Conversion and Management, vol. 88, pp. 332–347, Dec. 2014.
  • Sotoodeh and R. D. Miller, “Design and implementation of an 11-level inverter with FACTS capability for distributed energy systems,” IEEE J. Emerging Sel. Topics Power Electron., vol.2, no. 1, pp. 87–96, Mar. 2014.
  • Wang, and D. N. Truong, “Stability enhancement of a power system with a PMSG-based and a DFIG-based offshore wind farm using a SVC With an adaptive-network-based fuzzy inference system,” IEEE Trans. Ind. Electron., vol. 60, no. 7, pp. 2799–2807, Jul. 2013.
  • Zhang, X. Wu and X. Yuan, “A simplified branch and bound approach for model predictive control of multilevel cascaded H-bridge STATCOM,” IEEE Trans. Ind. Electron., vol. 64, no. 10, pp. 7634–7644, Oct. 2017.

 

Grid-Connected PV Array with Supercapacitor Energy Storage System for Fault Ride Through

ABSTRACT:

A fault ride through, power management and control strategy for grid integrated photovoltaic (PV) system with supercapacitor energy storage system (SCESS) is presented in this paper. During normal operation the SCESS will be used to minimize the short term fluctuation as it has high power density and during fault at the grid side it will be used to store the generated power from the PV array for later use and for fault ride through. To capture the maximum available solar power, Incremental Conductance (IC) method is used for maximum power point tracking (MPPT). An independent P-Q control is implemented to transfer the generated power to the grid using a Voltage source inverter (VSI). The SCESS is connected to the system using a bi-directional buck boost converter. The system model has been developed that consists of PV module, buck converter for MPPT, buck-boost converter to connect the SCESS to the DC link. Three independent controllers are implemented for each power electronics block. The effectiveness of the proposed controller is examined on Real Time Digital Simulator (RTDS) and the results verify the superiority of the proposed approach.

KEYWORDS:

  1. Active and reactive power control
  2. Fault ride through
  3. MPPT
  4. Photovoltaic system
  5. RTDS Supercapacitor
  6. Energy storage

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

image001

Fig.1. Grid connected PV system with energy storage

 EXPECTED SIMULATION RESULTS:

 image002

Fig.2. Grid voltage after three phase fault is applied

image003

Fig.3. PV array power PPV with SCESS and with no energy storage

image004

Fig.4. Grid active power Pg for a three phase fault with and without energy storage

image005

Fig.5.SCESS power PSC for the applied fault on the grid side

image006

Fig.6. Grid reactive power Qg during three phase fault

image007

Fig.7. DC link voltage for the applied fault

image008

Fig.8. PV array voltage VPV during three phase fault

image009

Fig.9. MPPT output voltage Vref for the applied fault

CONCLUSION:

This paper presents grid connected PV system with supercapacitor energy storage system (SCESS) for fault ride through and to minimize the power fluctuation. Incremental conductance based MPPT is implemented to track the maximum power from the PV array. The generated DC power is connected to the grid using a buck converter, VSI, buck-boost converter with SCESS. The SCESS which is connected to the DC link controls the DC link voltage by charging and discharging process. A P-Q controller is implemented to transfer the DC link power to the grid. During normal operation the SCESS minimizes the fluctuation caused by change in irradiation and temperature. During a grid fault the power generated from the PV array will be stored in the SCESS. The SCESS supplies both active and reactive power to ride through the fault. RTDS based results have shown the validity of the proposed controller.

REFERENCES:

[1] T. Esram, P.L. Chapman, “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,” IEEE Transaction on Energy Conversion, vol.22, no.2, pp.439-449, June 2007

[2] J. M. Enrique, E. Durán, M. Sidrach-de-Cardona, and J. M. Andújar,“Theoretical assessment of the maximum power point tracking efficiency of photovoltaic facilities with different converter topologies,” Sol. Energy, vol. 81, no. 1, pp. 31–38, Jan. 2007.

[3] W. Xiao, N. Ozog, and W. G. Dunford, “Topology study of photovoltaic interface for maximum power point tracking,” IEEE Trans. Ind. Electron., vol. 54, no. 3, pp. 1696–1704, Jun. 2007.

[4] J. L. Agorreta, L. Reinaldos, R. González, M. Borrega, J. Balda, and L. Marroyo, “Fuzzy switching technique applied to PWM boost converter operating in mixed conduction mode for PV systems,” IEEE Trans. Ind. Electron., vol. 56, no. 11, pp. 4363– 4373, Nov. 2009.

[5] A.Schneuwly, “Charge ahead [ultracapacitor technology and applications]”, IET Power Engineering Journal, vol.19, 34-37, 2005.

 

A New Control Strategy for Active and Reactive Power Control of Three-Level VSC Based HVDC System

ABSTRACT

This paper displays another control procedure no doubt and receptive power control of three-level multipulse voltage source converter based High Voltage DC (HVDC) transmission framework working at Fundamental Frequency Switching (FFS). A three-level voltage source converter replaces the regular two-level VSC and it is intended for the genuine and responsive power control is each of the four quadrants task. Another control strategy is produced for accomplishing the receptive power control by changing the beat width and by keeping the dc connect voltage consistent. The enduring state and dynamic exhibitions of HVDC framework interconnecting two unique frequencies arrange are shown for dynamic and responsive forces control. Complete quantities of transformers utilized in the framework are decreased in contrast with two dimension VSCs. The execution of the HVDC framework is likewise enhanced as far as decreased music level even at essential recurrence exchanging.

 

BLOCK DIAGRAM: 1

Fig. 1 A three-level 24-Pulse voltage source converter based HVDC system

 CONTROL SCHEME

2

Fig. 2 Control scheme of three-level VSC based HVDC system using dynamic dead angle (β) Control

EXPECTED SIMULATION RESULTS

3

Fig. 3 Performance of rectifier station during simultaneous real and reactive power control of three-level 24-pulse VSC based HVDC system

4

Fig. 4 Performance of inverter station during simultaneous real and reactive power control of three-level 24-pulse VSC based HVDC system

5

Fig. 5 Variation of angles (δ) and (β) values of three-level 24-pulse VSC based HVDC system during simultaneous real and reactive power control

CONCLUSION

Another control technique for three-level 24-beat voltage source converter setup has been intended for HVDC framework. The execution of this 24-beat VSC based HVDC framework utilizing the control technique has been exhibited in dynamic power control in bidirectional, free control of the receptive power and power quality enhancement. Another powerful dead point (β) control has been presented for three-level voltage source converter working at crucial recurrence exchanging. In this control the HVDC framework activity is effectively exhibited and furthermore an examination of (β) esteem for different responsive power necessity and symphonious execution has been completed in detail. In this way, the determination of converter task locale is progressively adaptable as indicated by the necessity of the responsive power and power quality.