Fast Processing Intelligent Wind Farm Controller for Production Maximisation

Ahmad, Tanvir; Basit, Abdul; Anwar, Juveria; Coupiac, Olivier; Kazemtabrizi, Behzad; Matthews, Peter

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 ( 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

Citation

Ahmad, T., Basit, A., Anwar, J., Coupiac, O., Kazemtabrizi, B., & Matthews, P. (2019). Fast Processing Intelligent Wind Farm Controller for Production Maximisation. Energies, 12(3), Article 544. https://doi.org/10.3390/en12030544

• Journal Article Type: Article
• Acceptance Date: Feb 6, 2019
• Online Publication Date: Feb 10, 2019
• Publication Date: Feb 10, 2019
• Deposit Date: Feb 13, 2019
• Publicly Available Date: Feb 13, 2019
• Journal: Energies
• Electronic ISSN: 1996-1073
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 3
• Article Number: 544
• DOI: https://doi.org/10.3390/en12030544
• Public URL: https://durham-repository.worktribe.com/output/1308211