1008 / 2019-05-12 14:05:46

Fuzzy Logic Based Algorithm for Wind Energy Prediction

Fuzzy Logic, Inference Engine, Mamdani, Chaotic, Prediction, Wind Speed, Power Generation

In recent years, wind power generation is rapidly
gaining popularity due to the major concerns about the
excessive emissions and the worldwide electrical energy crisis.
In addition, this kind of power systems have shown more
security options than others. Due to the highly variable and
intermittent nature of the wind energy, it is crucial to achieve
higher accuracy of long-term wind speed prediction for
improving the reliability and economic feasibility of power
systems. Hence, this paper proposes a novel methodology for
long-term wind speed prediction using fuzzy logic-based
prediction network. It uses fuzzy logic and employs Mamdani
product inference engine, singleton fuzzifier and center
average de-fuzzifier. The algorithm is capable of predicting
values in linear, non-linear and even chaotic sequences.
Literature search indicates that many researchers have
developed similar algorithms and used Mackey Glass time
series for prediction. Our attempt has used data series of wind
speed. The simulation results indicate that the algorithm works
reasonably well. However, prediction accuracy, in occasion of
data series, depends on extent of chaos. This algorithm works
reasonably well even when the mathematical model of the
system is not available.