An Energy Management Scheme with Power Limit Capability and an Adaptive Maximum Power Point Tracking for Small Standalone PMSG Wind Energy Systems


Due to its high energy generation capability and minimal environmental impact, wind energy is an elegant solution to the growing global energy demand. However, frequent atmospheric changes make it difficult to effectively harness the energy in the wind because maximum power extraction occurs at a different operating point for each wind condition. This paper proposes a parameter independent intelligent power management controller that consists of a slope-assisted maximum power point tracking (MPPT) algorithm and a power limit search (PLS) algorithm for small standalone wind energy systems with permanent synchronous generators. Unlike the parameter independent perturb & observe (P&O) algorithms, the proposed slope-assisted MPPT algorithm preempts logical errors attributed to wind fluctuations by detecting and identifying atmospheric changes. The controller’s PLS is able to minimize the production of surplus energy to minimize the heat dissipation requirements of the energy release mechanism by cooperating with the state observer and using the slope parameter to seek the operating points that result in the desired power rather than the maximum power. The functionality of the proposed energy management control scheme for wind energy systems is verified through simulation results and experimental results.


  1. Wind energy
  2. Maximum power point tracking
  3. Energy management
  4. Power electronics



Fig 1 System diagram with the proposed management control algorithm



 Fig 2 Performance of the standard fixed-step size P&O algorithm (average power captured = 1066 W).

Fig 3 Performance of the standard variable-step size P&O algorithm (average power captured = 1106 W).

Fig 4 Performance of the slope-assisted MPPT algorithm (1238 W).

Fig 5 Power coefficient performance of the fixed-step size P&O, variable step size P&O, and the slope assist MPPT (comparison performed under atmospheric identical conditions as depicted in Fig.20).


In this paper, an intelligent parameter-independent power management controller has been presented for standalone offgrid small wind energy systems. With the state observer presiding over the slope-assisted MPPT and the PLS in the proposed controller, the convergence times to the desired operating points is reduced and the logical errors are minimized by identifying the changes in wind conditions. Being applicable for both grid-connected and standalone wind systems, the slope assist MPPT increases a wind system’s MPP search efficiency and enables the wind system to actively adapt to its changing behavior and wind conditions. The PLS algorithm was designed to complement the slope assist MPPT for standalone wind systems that have limited energy storage and use energy dissipation mechanisms to disperse surplus energy. Rather than focusing on capturing maximum power, the power limit search focuses on reducing the size and heat requirements of the energy dissipation mechanism by minimizing surplus power generation as desired. The operating principles of the proposed PLS and MPPT control techniques have been discussed in this paper. Simulation results on a 3kW system and experimental results on a proof-of-concept prototype with a wind turbine emulator have been provided to highlight the merits of this work.


[1] Global Wind Energy Council, “Global Wind Report – Anual Market Update 2012,” 2013.

[2] Global Wind Energy Council, “Global Wind 2011 Report,” 2012.

[3] Canadian Wind Energy Association, “Canadian Wind Energy Association,” [Online]. Available:

[4] Q. Wang and L. Chang, “An Intelligent Maximum Power Extraction Algorithm for Inverter-Based Variable Speed Wind Turbine Systems,” IEEE Transactions on Power Electronics, vol. 1, September 2004, pp. 1242-1249.

[5] E. Koutroulis and K. Kalaitzakis, “Design of a Maximum Power Tracking System for Wind Energy Conversion Applications,” IEEE Transaction on Industrial Electronics, vol. 53, no. 2, April 2006, pp. 486-494.

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