Search

As other energy sources have become increasingly important, hydrokinetic turbines are one of the best energy production systems, and monitoring the state of hydrokinetic turbine power generation plays an important role. Ensuring proper condition-based monitoring, climate changes, stability aspects, turbine drive train status, and power outages should all be adequately monitored for remote turbines. Hydrokinetic turbines are capable of monitoring from any remote location. A condition monitoring system is a group of sensors that continuously collect performance data from hydrokinetic turbines, such as blade position, vibration, wind speed, humidity, temperature, structural alignment, drivetrain condition, vibration, rotor position, and generator state, and transmit it. If there is any error or omission, the controller responds promptly to avoid interruptions from any kind of defect that may damage and disrupt system performance. This is an innovative and novel idea, as the Internet of Underwater Things is a very niche area that is integrated with the hydrokinetics turbine, which is a comparatively new method of generating electricity. The erratic data or errors created as a result of disability are monitored for further processing of hydrokinetic turbines and related parameters. When the parameters are monitored, it will be easy to improve the performance of the turbine without causing any damage. The primary intent of the research is to establish an real-time monitoring system based on Internet of Things for a hydrokinetics turbine that will receive the data from the sensor network and send it to the seashore with the aid of an acoustic modem. From there, it will upload the data to the cloud for condition monitoring. The results shown in this paper are verified by node-red, an IoT-based platform that will show the data in real time. [ABSTRACT FROM AUTHOR]

The paper investigates the added-value brought by Net Effective Temperature (NET) index and its comparison with the already in-use Temperature-Humidity Index (THI) in characterizing the thermal comfort conditions in Romania during the warm season (May-September). In this context, two approaches are applied: (a) one based on the NET threshold values at daily scale obtained from the 30-years local climatology and (b) by using a comfort scale on monthly mean NET values. The second approach is further used to examine the changes in the comfort classes under climate change scenarios. [ABSTRACT FROM AUTHOR]

This paper aimed to establish a relationship between the selective meteorological variables such as temperature, humidity, wind speed, and rainfall in which contribute to the climate change in Peninsular Malaysia. Regression analysis, instantaneous causality, and impulse response function analysis were applied to the variables. The results revealed that humidity is positively related to rainfall and there is a strong relation between them. The instantaneous causality between wind speed and other variables concluded that the capability to predict the series of temperature, humidity, and rainfall based on the histories of all observable variables is unaffected by the omission of wind speed's history. [ABSTRACT FROM AUTHOR]