Wind turbine fires pose a significant global problem, leading to substantial financial losses. However, due to limited open discussions and lax regulations in the wind power industry, progress in addressing this issue has been hindered. This study aims to shed light on the fire risks associated with wind turbine nacelles and blades, while also exploring preventive measures and the latest fire detection and extinguishing technologies. The research conducted in this study involves a comprehensive investigation of various case studies, utilizing causal examination to identify common failure forms and their roles in fire incidents. Additionally, typical hazards, with a focus on fire incidents, in wind turbines are diagnosed. The primary causes of these fires were determined to be lightning strikes and hydraulic faults, often exacerbated by the presence of combustible materials. To conclude, the study includes a survey that encompasses education, knowledge analysis, and real-life accident experiences to assess fire risks and prevention measures in wind turbines. The participation of experts from wind farms, including those from the People's Republic of Bangladesh and other countries, adds valuable insights. The findings from this study serve as a crucial resource for enhancing safety standards and mitigating fire incidents within the wind power industry.
In this paper, an integrated thermoelectric (TE) and photovoltaic (PV) hybrid energy harvesting system (HEHS) is proposed for self-powered internet of thing (IoT)-enabled wireless sensor networks (WSNs). The proposed system can run at a minimum of 0.8 V input voltage under indoor light illumination of at least 50 lux and a minimum temperature difference, ∆T = 5 °C. At the lowest illumination and temperature difference, the device can deliver 0.14 W of power. At the highest illumination of 200 lux and ∆T = 13 °C, the device can deliver 2.13 W. The developed HEHS can charge a 0.47 F, 5.5 V supercapacitor (SC) up to 4.12 V at the combined input voltage of 3.2 V within 17 s. In the absence of any energy sources, the designed device can back up the complete system for 92 s. The sensors can successfully send 39 data string to the webserver within this time at a two-second data transmission interval. A message queuing telemetry transport (MQTT) based IoT framework with a customised smartphone application 'MQTT dashboard' is developed and integrated with an ESP32 Wi-Fi module to transmit, store, and monitor the sensors data over time. This research, therefore, opens up new prospects for self-powered autonomous IoT sensor systems under fluctuating environments and energy harvesting regimes, however, utilising available atmospheric light and thermal energy.