Wind Turbine Fire Prevention System Using Fuzzy Rules and WEKA Data Mining Cluster Analysis

With the rapid expansion of supply renewable energy in accordance with global transition policy, wind power generation industry is attracting attention. Subsequently, various turbine control technologies have been widely developed and applied. However, there a lack research on optimal pitch control, which detects direction changes rotation angle blade real time. In areas where speed not strong, such as South Korea, it necessary to maintain time so that rotating surface can face direction. this study, was performed through real-time analysis speed, direction, temperature, core maintenance, using fuzzy rules FIS (Fuzzy Interface System) WEKA data mining cluster techniques. order prevent fires caused by over-current turbines, methods VCB (Vacuum Circuit Breaker) utilization, prototype utilization modular MCB (Main incorporating VI Interrupter), vacuum degree change PD (Partial Discharge) signal were proposed. The technique for parts facilities put forth after judging predicting annual average distribution suitable HRWPRM (Korea’s High-Resolution Wind Power Resource Maps). Finally, carried out study confirmed computer simulation, remote diagnosis early warning issuance, prediction increase decrease situation, automatic efficiency.