scholarly journals Design of Energy Monitoring System for Small Scale Wind Turbine Applications

Author(s):  
Natalina Damanik ◽  
Muhammad R. Robiansyah ◽  
Almas Apriliana ◽  
Sahrijal Purba
2021 ◽  
Vol 2107 (1) ◽  
pp. 012039
Author(s):  
E.H. MatSaat ◽  
Majid M.A. ◽  
N.H. Abdul Rahman ◽  
Nur Amalina Muhamad ◽  
N. Othman

Abstract This paper presents the digitization of small-scale energy monitoring systems based on IoT. The proposed energy monitoring system known as EMOSY eliminates the high-cost energy meter. EMOSY is designed to be portable and practical to use without modification of internal or external connection of appliances. EMOSY is developed by using a voltage detector circuit concept by amplifying the existence of electrostatic. This electrostatic reading sends to the database through Wi-Fi module ESP8266 integrated with Arduino NodeMCU. The web page is designed using Adobe Dreamweaver with HTML and PHP coding. In the proposed system, the user able to monitor the energy usage of each appliance and estimated billing time to time. Based on the result, the energy monitoring system successfully can detect the existence of electrostatic, and the webpage database can display the energy usage extended to the estimated electricity bill. The monitoring system is found to be useful to the residential, commercial, and industrial to monitor energy patterns, which is essential to facilitate energy conservation measures for minimizing energy usage.


2013 ◽  
Vol 300-301 ◽  
pp. 576-579
Author(s):  
Wen Tsai Sung ◽  
Jui Ho Chen

The thesis proposes to construct a small vertical axis wind turbine monitoring system by the wireless sensor measuring network. This paper uses a small vertical axis wind turbine to generate electricity, and then provide to the parking lot and street lights, but also practical to monitor the entire system. Our monitoring system is constructed by the module. This paper proposes the small vertical axis wind turbine with the blade structure can be adjusted the angle with mechanical means, which is the most important improvement. Monitoring system to monitor real-time status of the communication part of the ZigBee and Ethernet established in the remote monitoring platform and the establishment of an Access database. Our research will be expected to improve the efficiency of wind turbine power generation, increase the stability of the monitoring system and the overall cost of power generation to reduce the effect.


2020 ◽  
Vol 37 ◽  
pp. 63-71
Author(s):  
Yui-Chuin Shiah ◽  
Chia Hsiang Chang ◽  
Yu-Jen Chen ◽  
Ankam Vinod Kumar Reddy

ABSTRACT Generally, the environmental wind speeds in urban areas are relatively low due to clustered buildings. At low wind speeds, an aerodynamic stall occurs near the blade roots of a horizontal axis wind turbine (HAWT), leading to decay of the power coefficient. The research targets to design canards with optimal parameters for a small-scale HAWT system operated at variable rotational speeds. The design was to enhance the performance by delaying the aerodynamic stall near blade roots of the HAWT to be operated at low wind speeds. For the optimal design of canards, flow fields of the sample blades with and without canards were both simulated and compared with the experimental data. With the verification of our simulations, Taguchi analyses were performed to seek the optimum parameters of canards. This study revealed that the peak performance of the optimized canard system operated at 540 rpm might be improved by ∼35%.


Author(s):  
Mopuri Deepika ◽  
Merugu Kavitha ◽  
N. S. Kalyan Chakravarthy ◽  
J. Srinivas Rao ◽  
D. Mohan Reddy ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.


Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 622
Author(s):  
Yasser Elhenawy ◽  
Yasser Fouad ◽  
Haykel Marouani ◽  
Mohamed Bassyouni

This study aims to evaluate the effect of functionalized multi-walled carbon nanotubes (MWCNTs) on the performance of glass fiber (GF)-reinforced polypropylene (PP) for wind turbine blades. Support for theoretical blade movement of horizontal axis wind turbines (HAWTs), simulation, and analysis were performed with the Ansys computer package to gain insight into the durability of polypropylene-chopped E-glass for application in turbine blades under aerodynamic, gravitational, and centrifugal loads. Typically, polymer nanocomposites are used for small-scale wind turbine systems, such as for residential applications. Mechanical and physical properties of material composites including tensile and melt flow indices were determined. Surface morphology of polypropylene-chopped E-glass fiber and functionalized MWCNTs nanocomposites showed good distribution of dispersed phase. The effect of fiber loading on the mechanical properties of the PP nanocomposites was investigated in order to obtain the optimum composite composition and processing conditions for manufacturing wind turbine blades. The results show that adding MWCNTs to glass fiber-reinforced PP composites has a substantial influence on deflection reduction and adding them to chopped-polypropylene E-glass has a significant effect on reducing the bias estimated by finite element analysis.


2021 ◽  
Vol 17 (3) ◽  
pp. 1-20
Author(s):  
Vanh Khuyen Nguyen ◽  
Wei Emma Zhang ◽  
Adnan Mahmood

Intrusive Load Monitoring (ILM) is a method to measure and collect the energy consumption data of individual appliances via smart plugs or smart sockets. A major challenge of ILM is automatic appliance identification, in which the system is able to determine automatically a label of the active appliance connected to the smart device. Existing ILM techniques depend on labels input by end-users and are usually under the supervised learning scheme. However, in reality, end-users labeling is laboriously rendering insufficient training data to fit the supervised learning models. In this work, we propose a semi-supervised learning (SSL) method that leverages rich signals from the unlabeled dataset and jointly learns the classification loss for the labeled dataset and the consistency training loss for unlabeled dataset. The samples fit into consistency learning are generated by a transformation that is built upon weighted versions of DTW Barycenter Averaging algorithm. The work is inspired by two recent advanced works in SSL in computer vision and combines the advantages of the two. We evaluate our method on the dataset collected from our developed Internet-of-Things based energy monitoring system in a smart home environment. We also examine the method’s performances on 10 benchmark datasets. As a result, the proposed method outperforms other methods on our smart appliance datasets and most of the benchmarks datasets, while it shows competitive results on the rest datasets.


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