You need to take into consideration of the performance curve of the wind turbine, This performance curve as an S-shape and the y-axis shows the power in kW or MW and the x-axis shows the wind speed.

Wind turbines can control the maximum by changing the tilt angle of the blades of the turbines. In some wind turbines, each blade has a motor to change its tilt relative to the wind direction to maximize the speed and, hence, the power generated.

This means that wind turbines with fixed blades' angles cannot control the maximum power in the same way wind turbines with motorized blades can.

Hope this helps answer your question.

Professor Yehia Khalil

Yale University

USA

There are several steps here. First you need to match the behaviour of the turbine itself to the wind speed; variable pitch blades are about the only option here. Then you have to match the mechanical power transferred from the turbine to the generator; this is done with either a gearbox or by design in a direct drive generator; finally you have to match the output of the generator to the input of the grid (or whatever it is connected to). This won't be a single variable MPPT device. You will require at least 2 variables, so a double MPPT or two MPPTs to do the job properly.

Joydeep,

I would do some in-depth study on the aerodynamics and mechanical engineering in the context of wind turbines, if I were you.

If you do go ahead with my suggestion, you would immediately realise that there is no best method or universal method for control. Source wind conditions differ in many ways, and the control strategies are framed accordingly.

-Sanjay

In fact, there is no best technique. Every technique has advantages and disadvantages. You should select a MPPT technique which is suitable for your system.

Joydeep,

First of all, tt is not necessary to vary the pitch angle to reach the MPP on a variable speed WT. If the WT can operate a diferent rotational speeds, you only need to control the generator.

Second, there it is not a best method. I sugest the reading of the book:

"Power Conversion and Control of Wind Energy Systems" by Bin Wu. (Wiley)

Cordially,

Marcelo.

Facultad de Ingeniería,

Universidad Nacional de La Plata, Argentina.

Thank you all the researchers for their valuable suggestions. 

Wind technology, as far my understanding is dependent on multiple variables esp. the wind speed & load connected, for its operation.

But if i focus on a selected range of wind pattern where the wind speed at turbine is between cut-in speed to rated speed, I need to apply power electronic controls to stick with the power curve at MPPT.

Kindly provide some guidance regarding this or some study reference which can help.

It depends upon the what  system you are considered and their parameters. In fact, there is no best technique. Every technique has advantages and disadvantages. You should select a MPPT technique which is suitable for your system. For more, you can go through the following link:

http://www.ijser.org/researchpaper/Maximum-Power-Extraction-Schemes-Power-Control-in-Wind-Energy-Conversion-System.pdf

Thank you Dr. Shukla

The attached paper is a nice guide to various techniques available.

Electrical MPPT depends on input power over a small range of a fixed ratio of Voc for many systems incl: PV, WP, therefore an estimate of MPT output can be derived from sensing input then open loop estimate then hunt for MPT is much faster.

 e.g.

for PV  Vmpt =82%Voc then Vmpt reduces to 70%Voc with solar W input to 0

PV is an imperfect current source

for Seeback effect generator, Vmpt=50%Voc since SEG is a lossy voltage source

for wind power, each blade design has a RPM vs power load profile, matched impedance gives rise to MPT, profile can be enhanced by measuring wind speed and blade speed  and adjusting blade angle to increase availble power with known increased loss due to drag/eddy current loss, therefore wind tunnel transfer functions are desireable, otherwise hunting for MPT using PID iterative frequency control loop, then DC-DC and DC-AC invertors also have MPT points within storage voltage limits

-active PFC reduces non-linear losses with Bridgeless PFC by 1% can be significant vs bridge type PFC and reduce 30% losses with no PFC where impulse rectifier charge currents limit MPT due to saturation of peaks and load regulation

Thus each stage of power conversion should have a dynamic set of transfer functions and some like blade RPM are not linear so like a PV current source MPT may be a > 50% no load RPM then RPM decreases with wind speed some compressed ratio.. .. otherwise, if you assume nothing but can measure Pout and wind velocity, v I would suggest a multi-output Iteration Frequency Transform controller for each variable with preset delays for moment of inertia to change speed.  

However it seems from my observations all the wind farms with tri-prop blades tend to all run at the same RPM regardless of wind speed for some reason

For better understanding, the method used for selection for hydro turbine, could used, as the available wind velocity, high(high head), or low(low head), if wind velocity is low, total wind(mass), needed would be more, for same power produced(low head high discharged), the high torque low speed reaction type designed blades with fixed angle, and less number of blades. If the available speed of wind is high, the high speed low torque designed blades, with adjustable (variable) angle, would be better to optimized the available mechanical power, by adjustment of angle(mixed impact and reaction), like medium head medium discharge, with increased number of blades. 

I enjoyed reading Dr. Shukla's research.  I recognized the lookup table approach, which I defined earlier for other energy sources based on input.  I like the hybrid approach with a lookup table and fuzzy logic to store and track based on learned experience.

Speaking of wind experience, I wonder what algorithms are used in in the great sailing races for reducing arrival time with best path and maximum power attack angles baes on apparent wind speed.   The other factor is loss of advantage to predicting wind power and losses from change in direction, akin to loss of imertia. Fuzzy logic might also assist in predicting wind speed using weather services which offer speed direction information on an hourly basis.

Maybe wind power providers ought to have a competition like the Great Americas Cup for sailing, with total accumulated energy.  enerated in a time period.

This discussion is gaining some momentum ... thank you for the valuable inputs.

Based on one of my study, the power control scheme of wind turbine is classified in three categories based on wind speed:

Below Cut-in Speed (before start): Blades are pitched out to allow all the wind to pass away

Between Cut-in speed & Turbine Rated Wind speed: Power electronic controls based on turbine power curve like Hill climb search, Power signal feedback control, Tip speed ratio control & implementation of all these methods using fuzzy or neural network.

More than rated wind speed of turbine: Pitch angle controller is used to maintain the power output at rated value.

Drag (the one used in sails) & Lift (like airplanes) are two ways to rotate the blades of turbine for extracting power

I wonder how much energy could be gained due to sub-optimal control methods and lack of inertia anticipation energy computations to prevent stalling when coasting with no load or reverse boost might prevent a temporary stall, so that the hysteresis condition of start-threshold can be avoided and thus lost energy during a rise between stall/cut-in.

 In this case PID loop with anticipators on wind speed and an open loop lookup table for high impedance loading should be much better than a hunting method like hill climb or fuzzy logic to a stoichastic condition, which could have inherent instability higher potential stalling.

It is quite difficult to answer the best MPPT algorithm for wind generation as the power generation and control are different for different types of wind power generation configurations used such as PMSG, DFIG, IG etc...depending on the configuration MPPT algorithm can be selected. 

Getting back to Sarkar's focus near stall speed, there MUST be  an optimal solution, or a contest winner, with a consistent advantage with that algorithm.

Imagine you have access to any data you need to capture the most NET power in calm low wind conditions that can last for hours.

Imagine everyone has the same machine with ALL inputs are known about cut-in conditions for  true wind speed, , optimal direction error, energy cost of shifting direction or even kick starting generator vs weather conditions both monitored locally and from some mobile weather radar app  , {such as: } temperature, time of day, prevailing wind speed/ direction, past/future projected speed/ direction, % RH, temperature , plus internal diagnostics, generator efficiency load profile , RPM,  cost of energy to shift direction and start blade to lower cut-in threshold then perform calclated anticipated net loss/gain and use most efficient lookup table for generator controlled load voltage and power drain, battery State of charge history and weighting factors for anticipated demand lower to available power to determine next state of control.

Some algorithm has to be a consistently better and be the winner.  It may assume the storage capacity is greater than available power capacity for a defined time interval to be greater than the longest period with insufficient wind power or some other cost factor if high availability is not a priority.

recall Sarkar said...

(But if i focus on a selected range of wind pattern where the wind speed at turbine is between cut-in speed to rated speed, I need to apply power electronic controls to stick with the power curve at MPPT)

So the requirement here is to exploit the max net power gain over a time interval such as 1 hour to accumulate low energy between cut-in and stall and prevent a stall if gains exceed losses.  Hunting for the MPPT may be a poor man's approach unless all other variables are fixed. The effects of inertia must be known and rate of change of angular moment with available wind to electrical power conversion.

There MUST be an optimal solution, but only after assumptions on valid data from above are available and constantly updated by learning performance changes of the machine due to weather and aging.

There must be an inexpensive solution for data aquisition and performance sensing.  Data sharing with neighbour systems or swarming may also be included for redundancy and fault detection/correction.

-*_*~*-*_*~*-

My casual observation of farms containing >300 turbines has indicated they all tend to run at the same RPM regardless of wind conditions and at least 10% had no signs if movement (0RPM) even in good winds. My guess is this data on MTBF and cum power generated is private.