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Energies 2019, 12(3), 544; https://doi.org/10.3390/en12030544

Fast Processing Intelligent Wind Farm Controller for Production Maximisation

1
US Pakistan Center for Advanced Studies in Energy, University of Engineering and Technology (UET), Peshawar 25000, Pakistan
2
School of Engineering, Durham University, Durham DH1 3LE, UK
3
Engie Green, 59777 Lille, France
*
Author to whom correspondence should be addressed.
Received: 26 December 2018 / Revised: 2 February 2019 / Accepted: 6 February 2019 / Published: 10 February 2019
(This article belongs to the Special Issue State of the Art of Wind Farm Optimization)
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Abstract

A practical wind farm controller for production maximisation based on coordinated control is presented. The farm controller emphasises computational efficiency without compromising accuracy. The controller combines particle swarm optimisation (PSO) with a turbulence intensity–based Jensen wake model (TI–JM) for exploiting the benefits of either curtailing upstream turbines using coefficient of power ( C P ) or deflecting wakes by applying yaw-offsets for maximising net farm production. Firstly, TI–JM is evaluated using convention control benchmarking WindPRO and real time SCADA data from three operating wind farms. Then the optimised strategies are evaluated using simulations based on TI–JM and PSO. The innovative control strategies can optimise a medium size wind farm, Lillgrund consisting of 48 wind turbines, requiring less than 50 s for a single simulation, increasing farm efficiency up to a maximum of 6% in full wake conditions. View Full-Text
Keywords: wind farm production maximisation; coordinated control; CP-based optimisation; yaw-based optimisation; wake effects; turbulence intensity; Jensen model; particle swarm optimisation wind farm production maximisation; coordinated control; CP-based optimisation; yaw-based optimisation; wake effects; turbulence intensity; Jensen model; particle swarm optimisation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ahmad, T.; Basit, A.; Anwar, J.; Coupiac, O.; Kazemtabrizi, B.; Matthews, P.C. Fast Processing Intelligent Wind Farm Controller for Production Maximisation. Energies 2019, 12, 544.

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