Fuzzy Sliding Mode Control for Photovoltaic System


In this study, a fuzzy sliding mode control (FSMC) based maximum power point tracking strategy has been applied for photovoltaic (PV) system. The key idea of the proposed technique is to combine the performances of the fuzzy logic and the sliding mode control in order to improve the generated power for a given set of climatic conditions.

Different from traditional sliding mode control, the developed FSMC integrates two parts. The first part uses a fuzzy logic controller with two inputs and 25 rules as an equivalent controller while the second part is designed for an online adjusting of the switching controller’s gain using a fuzzy tuner with one input and one output.

Simulation results showed the effectiveness of the proposed approach achieving maximum power point. The fuzzy sliding mode (FSM) controller takes less time to track the maximum power point, reduced the oscillation around the operating point and also removed the chattering phenomena that could lead to decrease the efficiency of the photovoltaic system.


  1. DC-DC converter
  2. Fuzzy sliding mode control
  3. photovoltaic system
  4. MPPT
  5. Solar energy



In this paper, a fuzzy sliding mode controller based MPPT technique was developed and tested. The proposed controller is designed by combining the fuzzy logic and sliding mode control to guarantee the stability and the tracking performance and also to avoid the drawbacks of the traditional SM and FL controllers.

A Matlab/Simulink based simulation of a stand-alone PV system under varying climatic conditions and two levels of load was carried out to validate the proposed controller.

Simulation results demonstrate that the designed FSMC-MPPT exhibits good responses as it successfully and accurately achieved the maximum power point with a significantly higher performance than the P&O, SM and FLC strategies. The proposed approach provides a feasible approach to control PV power systems.


[1] Dounis, A.I., Kofinas, P., Alafodimos, C., &Tseles, D. (2013). Adaptive fuzzy gain scheduling PID controller for maximum power point tracking of photovoltaic system. Renewable energy, 60, 202-214.

[2] Bhatnagar, P., & Nema, R.K. (2013). Maximum power point tracking control techniques: State-of-the-art in photovoltaic applications. Renewable and Sustainable Energy Reviews, 23, 224-241.

[3] Farhat, M., Barambones, O., & Sbita, L. (2015). Efficiency optimization of a DSP-based standalone PV system using a stable single input fuzzy logic controller. Renewable and Sustainable Energy Reviews, 49, 907-920.

[4] Kalashani, Mostafa Barzegar et Farsadi, Murtaza. New Structure for Photovoltaic Systems with Maximum Power Point Tracking Ability. International Journal of Power Electronics and Drive Systems, 2014, vol. 4, no 4, p. 489.

[5] Liu, F., Kang, Y., Zhang, Y., & Duan, S. (2008, June). Comparison of P&O and hill climbing MPPT methods for grid-connected PV converter. In Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on (pp. 804-807). IEEE.

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


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 standard for future research in smart grid applications.

  1. Wind energy
  2. Solar energy
  3. Conversion
  4. Storage
  5. Hybrid system
  6. Control
  7. Energy management



 Fig. 1. Components of the laboratory scale experimental microgrid


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


 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.


[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.

Modelling, Design, Control, and Implementation of a Modified Z-source Integrated PV/Grid/EVDC Charger/Inverter


Solar Energy has been the most popular sources of renewable energy for residential and semi commercial applications. Fluctuations of solar energy harvested due to atmospheric conditions can be mitigated through energy storage systems. Solar energy can also be used to charge electric vehicle batteries to reduce the dependency on the grid. One of the requirements for a converter for such applications is to have a reduced number of conversion stages and provide isolation. Z-source inverter (ZSI) topology is able to remove multiple stages and achieve voltage boost and DC-AC power conversion in a single stage. The use of passive components also presents an opportunity to integrate energy storage systems (ESS) into them. This paper presents modeling, design and operation of a modified Z-source inverter (MZSI) integrated with a split primary isolated battery charger for DC charging of electric vehicles (EV) batteries. Simulation and experimental results have been presented for the proof of concept of the operation of the proposed converter.


  1. Z-source-inverters
  2. Active filter
  3. Energy storage
  4. Photovoltaic (PV) power generation
  5. Quasi-Zsource inverter (qZSI)
  6. Single-phase systems
  7. Transportation electrification
  8. Solar energy
  9. Distributed power generation
  10. Inverter




Fig. 1. Simplified Block Diagram of the System



Fig. 2. Simulation Waveform of the grid current,Ig, DC link voltage,VPN, Capacitor Voltage,VC1, and Battery current,ib for the power balance between the Photovoltaic input power, the AC Grid side and the battery power.

Fig. 3. Simulation Waveform for the power balance between the Photovoltaic input power, the AC Grid side and the battery power.


A modified ZSI topology has been proposed in this paper is an attractive solution for photovoltaic grid connected charging systems. It consist of a single stage photovoltaic grid (PV-Grid) connection and an integrated charger for PV-Grid connected charging or energy storage. This topology can be applied to centralized configuration for charging in semi-commercial locations such as a parking lot of a shopping mall. For residential applications, this idea can be extended to string inverters with the charger side of the string inverter configurations connected in series or parallel for current sharing. The paper proposes a an energy storage topology using Z source converter through symmetrical operation of its impedance network.


[1] D. Aggeler, F. Canales, H. Zelaya, D. L. Parra, A. Coccia N. Butcher, and O. Apeldoorn, “Ultra-fast dc-charge infrastructures for ev-mobility and future smart grids,” in Proc. of IEEE PES Innovative Smart Grid Technologies Conference Europe, pp. 1–8, Oct. 2010.

[2] G. Carli and S. S. Williamson, “Technical considerations on power conversion for electric and plug-in hybrid electric vehicle battery charging in photovoltaic installations,” IEEE Trans. on Ind. Electron., vol. 28, no. 12, pp. 5784–5792, 2013.

[3] J. G. Ingersoll and C. A. Perkins, “The 2.1 kw photovoltaic electric vehicle charging station in the city of santa monica, california,” in Proc. of the Twenty Fifth IEEE Photovoltaic Specialists Conference, pp. 1509– 1512, May. 1996.

[4] S. B. Kjaer, J. K. Pedersen, and F. Blaabjerg, “A review of single-phase grid-connected inverters for photovoltaic modules,” IEEE Trans. on Ind. Appl., vol. 41, no. 5, pp. 1292–1306, Sep. 2005.

[5] N. A. Ninad, L. A. C. Lopes, and I. S. Member, “Operation of Single-phase Grid-Connected Inverters with Large DC Bus Voltage Ripple,” Proc. of the IEEE Canada Electrical Power Conference, 2007.