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Distributed Low-Complexity Controller for Wind Power Plant in Derated Operation

Presentation made at IEEE Multi Conference on Control, August 2013, Hyderabad, India. Authors from Aalborg, Lund, and Zagreb University.

Benjamin Biegel

on 25 March 2017

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Transcript of Distributed Low-Complexity Controller for Wind Power Plant in Derated Operation

Distributed Low-Complexity Controller for Wind Power Plant in Derated Operation

Wind overproduction
Moving from 30 % to 50 % wind in Denmark
Wind turbines can provide a fast power response
Model & Validation
Controller Synthesis
Key Idea
Unused freedom
Dynamics power dispatch
Gives us a freedom
No wind coupling
1. We will only make small pitch perturbations and not affect effective wind speed downstream

2. Wake models useful for finding the static power operating points – we examine dynamic coupling
Fatigue reduction
Reduce overall fatigue
Wind turbine model
Linear model
Variable speed wind turbine
Adjust the power set-point
Reduce tower and shaft moments
Linear second order model
Inputs and states
Operating point
Experiment at operational wind farm
Sequences of steps in the power set-points are applied
Measurements of states and outputs
Linearized model is verified
Validation of the linearized model
Demand to entire wind power
plant - freedom in power dispatch
Wind Power Plant Model
Distributed Controller
Control Algorithm
Coupling via power constraint
Elimination via transformation
Coupling eliminated
Transformation of parameters
Optimization problem
Distributed feedback controller
State feedback
Structural constraint
Gradient descent method
Locally measure pitch and
generator velocity
Obtain neighboring
Simulations on linear and nonlinear industrial model using effective wind speed measurements from operational wind farm.

Communication with 2 neighboring turbines, 8 turbines in all producing 17.6 MW with 6.4 MW in reserve.
Closeup on one turbine
Fatigue Reductions
Presented distributed controller for wind farm in derated operation
Objective is fatigue reduction on tower and shaft
Apply local power set-point updates
Low-complexity, little communicational effort, simple, and transparent
Simulations indicate fatigue reductions in the magnitude of 15 - 20 %
Benjamin Biegel, Daria Madjidian,
Vedrana Spudic, Anders Rantzer, and Jakob Stoustrup

Static power set points
Based on long term predictions
Shift fatigue
Low-complexity control law
Little communication and computational effort

Derated operation

Distributed approach
Full transcript