ABSTRACT:
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.
KEYWORDS:
1.
Wind energy
2.
Maximum power point tracking
3.
Energy management
4.
Power electronics
SOFTWARE: MATLAB/SIMULINK
CIRCUIT DIAGRAM:
Fig
1 System diagram with the proposed management control algorithm
EXPECTED SIMULATION RESULTS:
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).
CONCLUSION:
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.
REFERENCES:
[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: www.canwea.ca.
[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.
