Fast Processing Intelligent Wind Farm Controller for Production Maximisation

被引：16

作者：

Ahmad, Tanvir ^{[1
,2
]}

Basit, Abdul ^{[1
]}

Anwar, Juveria ^{[1
]}

Coupiac, Olivier ^{[3
]}

Kazemtabrizi, Behzad ^{[2
]}

Matthews, Peter C. ^{[2
]}

机构：

[1] UET, US Pakistan Ctr Adv Studies Energy, Peshawar 25000, Pakistan

[2] Univ Durham, Sch Engn, Durham DH1 3LE, England

[3] Engie Green, F-59777 Lille, France

来源：

ENERGIES | 2019年 / 12卷 / 03期

关键词：

wind farm production maximisation; coordinated control; C-P-based optimisation; yaw-based optimisation; wake effects; turbulence intensity; Jensen model; particle swarm optimisation; COORDINATED CONTROL; POWER; WAKE; DYNAMICS; POINT; LOAD;

D O I：

10.3390/en12030544

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

A practical wind farm controller for production maximisation based on coordinated control is presented. The farmcontroller 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 (CP) 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.

引用

页数：17

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