Desain Sistem Akuisisi Kecepatan Angin pada Menara SST Berbasis IoT

Wind energy is one of the new renewable energy sources that can be used to generate electricity. The application of microgrids is expected to reduce the use of fossil fuels. PT PLN UP3B West Kalimantan has a greenfield type SST (Self Support Tower) communication tower with a height of 52 meters. This study aims to test the wind speed acquisition system in real-time on the SST tower. This research was conducted because there is no research on the design of the wind speed acquisition system on the SST Tower. Wind speed measurement data is obtained from the anemometer sensor mounted on the top of the SST Tower. The wind speed measurement data is sent to the MQTT broker and database using the MQTT protocol with the help of a microcontroller and communication media so that the measurement data can be monitored in real-time using the Grafana application either through local or public networks. The study was conducted from February 6 to 27, 2021. As a result, the wind speed data acquisition system managed to collect 5,501,689 wind speed measurement data stored in the database with an average wind speed of 3.03 m/s.

Emulators of a Physical Model for Estimating Leaf Wetness Duration

Leaf wetness duration (LWD) has rarely been measured due to lack of standard protocol. Thus, empirical and physical models have been proposed to resolve this gap. Although the physical model provides robust performance in diverse conditions, it requires many variables. The empirical model requires fewer variables; nevertheless, its performance is specific to a given condition. A universal LWD estimation model using fewer variables is thus needed to improve LWD estimation. The objective of this study was to develop emulators of the LWD estimation physical model for use as universal empirical models. It is assumed that the Penman–Monteith (PM) model determines LWD and can be employed as a physical model. In this study, a simulation was designed and conducted to investigate the characteristics of the PM model and to build the emulators. The performances of the built emulators were evaluated based on a case study of LWD data obtained in South Korea. It was determined that a machine learning algorithm can properly emulate the PM model in LWD estimations based on the simulation. Moreover, the poor performances of some emulators that use wind speed may have been due to the limitation of wind speed measurement. The accuracy of the anemometer is thus critical to estimating LWD using physical models. A deep neural network using relative humidity and air temperature was found to be the most appropriate emulator of those tested for LWD estimation.

Development and Experimental Testing of a Rotary Direct Wind Lidar System Based on Fabry.Perot Interferometer Technology-=SUP=-*-=/SUP=-

A 532-nm Rayleigh--Mie Doppler lidar system based on three-channel Fabry--Perot interferometer (FPI) technology was developed to measure wind speed from the bottom of the troposphere to the top of the stratosphere. An FPI transmittance calibration experiment and laser frequency stability experiments were carried out, resulting in the accuracy of the emitted laser frequency falling within .8 MHz. In addition, multiple sets of radial wind speed detection experiments were conducted during day and night, and the results of horizontal wind speed detection experiments were compared with those from balloon radiosonde. Results showed that, although the signal-to-noise ratio is not high, due to factors such as the size of the telescope aperture and the low optical coupling efficiency of the system, the overall performance of the verification system is good. When the spatiotemporal resolution of a single radial wind speed measurement is 2 min and 75 m, the system has the ability to detect the wind field in the height range of 16 km. In the height range of roughly 2 km to 12 km, the horizontal wind speed of the system and the balloon radiosonde were compared, revealing a direct correlation between the data that exceeded 0.8. Thus, the accuracy of the system.s wind speed measurement results was fully verified. Keywords: Doppler lidar; rotary direct wind measurement; Fabry-Perot interferometer; Rayleigh-Mie scattering.

Hierarchical Pitch Control for Small Wind Turbines Based on Fuzzy Logic and Anticipated Wind Speed Measurement

Bringing electricity to areas of difficult terrain is a complicated task, so it is convenient to generate power using local natural resources, such as wind, through a small horizontal-axis wind turbine (S-HAWT). However, at the rotor height of these wind turbines, the wind is often turbulent due to obstacles such as trees and buildings. For a turbine to function properly in these conditions, the action of the wind force on the rotor must be smoothed out by controlling the pitch angle. A commercial derivative-integral-proportional (PID)-type pitch controller works well when system dynamics are stable, but not when there are disturbances in the system. This paper proposes a hierarchical fuzzy logic controller (HFLC) to solve the nonlinear system effects produced by atypical winds. The methodology includes a statistical analysis of wind variability at the installation site, which determines the functions of belonging and its hierarchy. In addition, installing an anemometer in front of the turbine allows an advanced positioning of the blades in the presence of wind gusts. The algorithm was implemented in an S-HAWT, and a comparison was made to quantify the performance difference between the proposed control strategy and a conventional PID controller.