Optimal Power Extraction for PMSG based WTG through monotonous Power Increments

Author:

Renjith A.,Selvam P.

Abstract

Abstract Due to the uncertainty in the cost of fossil fuels due to various reasons, its depleting trend in reserves and the consequential pollution caused due to its usage forced to enhance the usage of renewable energy sources. As the characteristic behavior of the renewable energy extraction systems are exhibiting non-linear characteristic, it is quite cumbersome to extract power from the renewable systems in a straight forward manner. In the case of wind energy systems, the change in wind speed through the day makes the extraction of power still more difficult. Hence, different algorithms with the intention of extracting maximum possible available power are implemented. Different algorithms are already available whose behavior depends on the various parameters to be measured and controlled. In this paper one such algorithm, which is simple in nature is proposed. The algorithm takes the benefit of the monotonicity of power with respect to the wind turbine’s spinning speed. The algorithm senses the power increments in conjunction with the increments in turbine speed and implements further increment magnitude in such a manner to reach the maximum power point.

Publisher

IOP Publishing

Reference12 articles.

1. Neural-network-based sensor-less maximum wind energy capture with compensated power coefficient;Li;IEEE Trans. Ind. Appl.,2005

2. A UPF power conditioner with maximum power point tracker for grid connected variable speed wind energy conversion system;Raju,2004

3. Design of a maximum power tracking system for wind-energy-conversion applications;Koutroulis;IEEE Transactions on Industrial Electronics,2006

4. Limit Cycle Based Simple MPPT Control Scheme for a Small Sized Wind Turbine Generator System;Matsui;Proc. of 4th International Power Electronics and Motion Control Conference Xi’an,2004

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