Power Curve Based-Fuzzy Wind Speed Estimation in Wind Energy Conversion Systems | Zendy

Agus Naba | Zendy; Ahmad Nadhir | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Power Curve Based-Fuzzy Wind Speed Estimation in Wind Energy Conversion Systems

Author(s) -

Agus Naba,

Ahmad Nadhir

Publication year - 2018

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2018.p0076

Subject(s) - anemometer , wind speed , wind power , turbine , computer science , estimator , fuzzy logic , control theory (sociology) , small wind turbine , power optimizer , power (physics) , meteorology , maximum power point tracking , engineering , mathematics , artificial intelligence , electrical engineering , aerospace engineering , statistics , physics , control (management) , quantum mechanics , inverter

Availability of wind speed information is of great importance for maximization of wind energy extraction in wind energy conversion systems. The wind speed is commonly obtained from a direct measurement employing a number of anemometers installed surrounding the wind turbine. In this paper a sensorless fuzzy wind speed estimator is proposed. The estimator is easy to build without any training or optimization. It works based on the fuzzy logic principles heuristically inferred from the typical wind turbine power curve. The wind speed estimation using the proposed estimator was simulated during the operation of a squirrel-cage induction generator-based wind energy conversion system. The performance of the proposed estimator was verified by the well estimated wind speed obtained under the wind speed variation.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research