Single Phase NPC Inverter Controller with Integrated MPPT for PV Grid Connection

ABSTRACT:  

This paper presents a single-stage three-level Neutral Point Clamped (NPC) inverter for connection to the electrical power grid, with integrated Maximum Power Point Tracking (MPPT) algorithm to extract the maximum power available from solar photovoltaic (PV) panels. This single-stage topology is more compact than the traditional topology, it was chosen because with the proper control strategy. It is suitable to connect the PV panels to the power grid. The paper describes the design of a 5 kW NPC inverter for the interface of PV panels with the power grid, presenting the circuit parameters and the description of the control algorithms. A phase locked loop control is used to connect the inverter into the grid. Then, a proposed DC Link voltage control to regulate the input voltage of the inverter. Although an MPPT algorithm was used to optimize the energy extraction and the system efficiency. Inverter Output Current control to produce an output current (current injected in the power grid) with low Total Harmonic Distortion (THD) implemented in a DSP. Simulation and experimental results verify the correct operation of the proposed system, even with fluctuations in the solar radiation.

KEYWORDS:

1.      Photovoltaic System

2.       Maximum Power Point Tracking (MPPT)

3.      Neutral Point Clamped (NPC) Inverter

4.      Phase-Locked Loop (PLL)

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Figure 1. Block diagram of the NPC converter control system.

 EXPECTED SIMULATION RESULTS:

Figure 2. Block diagram of the E-PLL.

Figure 3. Startup of the proposed system with maximum solar radiation: (a)

PV current (ipanels); (b) PV panels voltage (vpanels);

(c) PV panels power (ppanels).

Figure 4. Operation with fluctuations in the solar radiation, from1000 W/m² to

800 W/m² and to 600 W/m: (a) Maximum theoretical power (pmax); (b)

Extracted power PV panels (ppanels); (c) Inverter output current (iout).

Figure 5. Reference current (iref *) and current injected into the power grid (iout).

Figure 6. Power grid voltage (vgrid) and inverter output current (iout).

Figure 7. Voltages in the two capacitors of the DC-link (vc1, vc2).

CONCLUSION:

This paper presents the design, simulation and experimental results of a 5 kW single-stage three-level Neutral Point Clamped (NPC) inverter for connection to the electrical power grid, with integrated Maximum Power Point Tracking (MPPT) algorithm to extract the maximum available power from solar photovoltaic (PV) panels. It also describes the design of the PLL controller, used to track the fundamental power grid voltage in order to synchronize the NPC inverter with the power grid, and to generate a reference for the inverter output current (which consists in the injected power grid current). All the controllers have been implemented using C code, validated by simulation in PSIM, and executed in a DSP. Experimental results indicate that the current injected in the power grid follows the reference, and that the voltages in the two DC-link capacitors are kept balanced. It is shown that the proposed system is able to always extract the maximum power available from the solar PV panels, even when there are solar radiation fluctuations.

REFERENCES:

[1] S. V. Araújo, S. Member, P. Zacharias, and R. Mallwitz, “Highly Efficient Single-Phase Transformerless Inverters for Grid-Connected Photovoltaic Systems,” Ind. Electron. IEEE Trans., vol. 57, no. 9, pp. 3118–3128, 2010.

[2] S. Saridakis, E. Koutroulis, and F. Blaabjerg, “Optimal  Design of Modern Transformerless PV Inverter Topologies,” Energy Conversion, IEEE Trans., vol. 28, no. 2, pp. 394–404, 2013.

[3] R.Teodorescu, M.Liserre, and P.Rodriguez, Grid Converters for Photovoltaic and Wind Power Systems. 2011.

[4] S. Busquets-monge, J. Rocabert, P. Rodríguez, P. Alepuz, and J. Bordonau, “Multilevel Diode-Clamped Converter for Photovoltaic Generators With Independent Voltage Control of Each Solar Array,” Ind. Electron. IEEE Trans., vol. 55, no. 7, pp. 2713–2723, 2008.

[5] P. Panagis, F. Stergiopoulos, P. Marabeas, and S. Manias, “Comparison of State of the Art Multilevel Inverters,” Power Electron. Spec. Conf. 2008. PESC 2008. IEEE, pp. 4296– 4301, 2008.

A Unified Control and Power Management Scheme for PV-Battery-Based Hybrid Microgrids for Both Grid-Connected and Islanded Modes

ABSTRACT:  

Battery storage is usually employed in Photovoltaic (PV) system to mitigate the power fluctuations due to the characteristics of PV panels and solar irradiance. Control schemes for PV-battery systems must be able to stabilize the bus voltages as well as to control the power flows flexibly. This paper proposes a comprehensive control and power management system (CAPMS) for PV-battery-based hybrid microgrids with both AC and DC buses, for both grid-connected and islanded modes. The proposed CAPMS is successful in regulating the DC and AC bus voltages and frequency stably, controlling the voltage and power of each unit flexibly, and balancing the power flows in the systems automatically under different operating circumstances, regardless of disturbances from switching operating modes, fluctuations of irradiance and temperature, and change of loads. Both simulation and experimental case studies are carried out to verify the performance of the proposed method.

KEYWORDS:

1.      Solar PV System

2.      Battery

3.      Control and Power Management System

4.      Distributed Energy Resource

5.      Microgrid

6.      Power Electronics

7.      dSPACE

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig. 1. The proposed control and power management system (CAPMS) for PV-battery-based hybrid microgrids.

EXPECTED SIMULATION RESULTS:

Fig.. 2.. (Gb)rid-connected mode Case A-1: (a) power flows and (b) voltage

values of the PV-battery system.

Fig. 3. Grid-connected mode Case A-2: power flows of the PV-battery system.

Fig. 4. Grid-connected mode Case A-3-1: PV array in power-reference mode.

Fig. 5. Grid-connected mode Case A-3-2: DC bus and PV array voltages

during transitions between MPPT and power-reference modes.

Fig. 6. Grid-connected mode Case A-4: the PV-battery system is receiving

power from the grid after 2.2 s.

Fig. 7. Grid-connected mode Case A-5: Reactive power control of the

inverter.

Fig. 8. Grid-connected mode Case A-6: transition from grid-connected to

islanded mode.

Fig. 9. Islanded mode Case B-1: power flows of the PV-battery system with

changing loads.

Fig. 10. Islanded mode Case B-2: battery power changes with PV generation.

Fig. 11. Islanded mode Case B-3: bus voltage control of the PV-battery

system.

 Fig. 12. Islanded mode Case B-4: (a) unsynchronized and (b) synchronized

AC bus voltages (displaying phase-a) when closing the breaker at the PCC.

 CONCLUSION:

This paper proposes a control and power management system (CAPMS) for hybrid PV-battery systems with both DC and AC buses and loads, in both grid-connected and islanded modes. The presented CAPMS is able to manage the power flows in the converters of all units flexibly and effectively, and ultimately to realize the power balance between the hybrid microgrid system and the grid. Furthermore, CAPMS ensures a reliable power supply to the system when PV power fluctuates due to unstable irradiance or when the PV array is shut down due to faults. DC and AC buses are under full control by the CAPMS in both grid-connected and islanded modes, providing a stable voltage environment for electrical loads even during transitions between these two modes. This also allows additional loads to access the system without extra converters, reducing operation and control costs. Numerous simulation and experimental case studies are carried out in Section IV that verifies the satisfactory performance of the proposed CAPMS.

REFERENCES:

[1] T. A. Nguyen, X. Qiu, J. D. G. II, M. L. Crow, and A. C. Elmore, “Performance characterization for photovoltaic-vanadium redox battery microgrid systems,” IEEE Trans. Sustain. Energy, vol. 5, no. 4, pp. 1379–1388, Oct 2014.

[2] S. Kolesnik and A. Kuperman, “On the equivalence of major variable step- size MPPT algorithms,” IEEE J. Photovolt., vol. 6, no. 2, pp. 590– 594, March 2016.

[3] H. A. Sher, A. F. Murtaza, A. Noman, K. E. Addoweesh, K. Al-Haddad, and M. Chiaberge, “A new sensorless hybrid MPPT algorithm based on fractional short-circuit current measurement and P&O MPPT,” IEEE Trans. Sustain. Energy, vol. 6, no. 4, pp. 1426–1434, Oct 2015.

[4] Y. Riffonneau, S. Bacha, F. Barruel, and S. Ploix, “Optimal power flow management for grid connected PV systems wi0th batteries,” IEEE Trans. Sustain. Energy, vol. 2, no. 3, pp. 309–320, July 2011.

[5] H. Kim, B. Parkhideh, T. D. Bongers, and H. Gao, “Reconfigurable solar converter: A single-stage power conversion PV-battery system,” IEEE Trans. Power Electron., vol. 28, no. 8, pp. 3788–3797, Aug 2013.

Energy Management and Control System for Laboratory Scale Microgrid based Wind-PV-Battery

 ABSTRACT:  

 This paper proposes an energy management and control system for laboratory scale microgrid based on hybrid energy resources such as wind, solar and battery. Power converters and control algorithms have been used along with dedicated energy resources for the efficient operation of the microgrid. The control algorithms are developed to provide power compatibility and energy management between different resources in the microgrid. It provides stable operation of the control in all microgrid subsystems under various power generation and load conditions. The proposed microgrid, based on hybrid energy resources, operates in autonomous mode and has an open architecture platform for testing multiple different control configurations. Real-time control system has been used to operate and validate the hybrid resources in the microgrid experimentally. The proposed laboratory scale microgrid can be used as a benchmark for future research in smart grid applications.

KEYWORDS:

1.      Wind energy

2.      Solar energy

3.      Conversion

4.      Storage

5.      Hybrid system

6.      Control

7.      Energy management

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

  

Fig. 1. Components of the laboratory scale experimental microgrid

EXPECTED SIMULATION RESULTS:

Fig. 2. Wind turbine-generator speed

Fig. 3. PV module current

Fig. 4. DC-link voltage

Fig. 5. Battery current

Fig. 6. Power at different locations in the microgrid (variable wind power)

Fig. 7. Battery state of charge

Fig. 8. Load Voltage

Fig. 9. Power at different locations in the microgrid (variable wind power)

Fig. 10. Battery current

Fig. 11. Battery state of charge

Fig. 12. DC-bus voltage

Fig. 13. Load Voltage

CONCLUSION:

A laboratory scale experimental microgrid of distributed renewable energy sources with battery storage and energy management and control system is developed in this paper. The experimental setup is flexible and allows testing difference power electronics interfaces and combinations. The control software is open source in order to implement different control strategies. This tool contributes to the enhancement of education and research the field of renewable energy and distributed energy systems.

REFERENCES:

[1] A. Bari, J. Jiang, W. Saad and A. Jaekel, “Challenges in the Smart Grid Applications: An Overview,” Int. J. of Distributed Sensor Networks, pp.1–12, 2014.

[2] M. B. Shadmand and R. S. Balog, “Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid,” IEEE Trans. Smart Grid, vol. 5, no. 5, pp. 2635–2643, Sep. 2014.

[3] M. J. Hossain, H. R. Pota, M. A. Mahmud and M. Aldeen, “Robust control for power Sharing in microgrids with low-inertia wind and PV generators,” IEEE Trans. Sustain. Energy, vol. 6, no. 3, pp. 1067–1077, Jul. 2015.

[4] Zaheeruddin and M. Manas, “Renewable energy management through microgrid central controller design: an approach to integrate solar, wind and biomass with battery,” Energy Reports, vol. 1, pp.156–163, 2015.

[5] A. Tani, M. B. Camara and B. Dakyo, “Energy management in the decentralized generation systems based on renewable energy—ultracapacitors and battery to compensate the wind/load power fluctuations,” IEEE Trans. Ind. Appl., vol. 51, no. 2, pp. 1817–1827, 2015.