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Experimental Study and Modeling of Automatic Home Energy Management System Using AI
(2021-01-01)
Pranee, Piyanut
;
Jirasuwankul, Nirudh
This paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30-38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results.
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Discrete wavelet transform and fuzzy logic algorithm for classification of fault type in underground cable
(2018-01-01)
Yoomak, Suntiti
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Pothisarn, Chaichan
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Jettanasen, Chaiyan
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Ngaopitakkul, Atthapol
This paper proposes the combination of discrete wavelet transform (DWT) and fuzzy logic to classify the fault type in underground distribution cable. The DWT is employed to decompose high frequency component from fault signal with the mother wavelet daubechies4 (db4). The maximum coefficients detail of DWT from phase A, B, C and zero sequence for post-fault current waveforms are considered as an input pattern of decision algorithm. Triangle-shaped S-shaped and Z-shaped membership function with maximum, medium, minimum, and zero are used to create a function for the input variable. Output variable of fuzzy are designated as values range 1 to 10 which corresponding with type of fault. The obtained average accuracy results shown that the proposed decision algorithm is able to classify the fault type with satisfactory accuracy.
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A lab-scale heliostat positioning control using fuzzy logic based stepper motor drive with micro step and multi-frequency mode
(2017-08-23)
Jirasuwankul, N.
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Manop, C.
This paper proposes positioning control technique for a lab-scale heliostat by application of hybrid stepper motors and fuzzy logic controllers. Steady state tracking error has been kept minimal by micro step drive together with speed control by multi stepping rate adjustment. By supportive video streaming device and image processing, a reflected image of illuminant area on the target is captured and analyzed, an obtaining position error in azimuth and altitude angles are real-time fed to the fuzzy controllers. As a result, the closed loop tracking is formulated and steady state error can then be minimized. Simulation and experimental results confirm the proposed technique.
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Fuzzy logic-based predictive model for biomass pyrolysis
(2017-01-01)
Lerkkasemsan, Nuttapol
As pyrolysis reaction is one of an important reaction applied to lignocellulosic biomass in order to transform it to be user-friendly energy form recognized as prospective alternative energy source, the reaction has been widely investigated in order to understand the mechanisms and kinetics of the pyrolysis. However, modeling pyrolysis of biomass is full of complication. As lignocellulosic biomass is not a homogeneous chemical source, chemical compositions in biomass are also uncertain and they vary even in the same biomass. The reactions of imprecise chemical compositions in biomass affects the capability of deterministic model in modeling chemical reaction since available deterministic models are designed to model homogeneous and precise chemical compositions. With this problem, it raises the idea of using model which has ability to calculate something ambiguous. Since the fuzzy logic-based model which is adaptive network-based fuzzy inference system (ANFIS) is built to calculate uncertainty, the model should be suitable to handle uncertainty which is imprecise chemical compositions in the reaction. The proposed model is built with four input variables: the reaction time, amount of cellulose component, amount of hemicellulose component, and amount of lignin component in biomass. The model is trained with tuning datasets which are the pyrolysis datasets of lignin, cellulose and Madhuca before applying to predict the pyrolysis reactions of Pongamia pinnata and Jatropha curcas. The comparative results show that the proposed model can correctly predict 91.82% and 97.29%, respectively, of the pyrolysis reactions of P. pinnata and J. curcas. As the ANFIS model gives good prediction in modeling pyrolysis of two different biomasses, the model can be applied to predict the pyrolysis reaction of other lignocellulosic biomass products.
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Identifying types of simultaneous fault in transmission line using discrete wavelet transform and fuzzy logic algorithm
(2013-07-17)
Ngaopitakkul, Atthapol
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Apisit, Chaowat
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Bunjongjit, Sulee
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Pothisarn, Chaichan
In the literature for fault classification, several decision algorithms have different solutions and techniques. These research works have been rarely mentioned about simultaneous faults in transmission systems. This paper presents the decision algorithm for identifying types of simultaneous fault along the transmission line. Decision algorithms based on discrete wavelet transform (DWT) and fuzzy logic are investigated. The analysis of fault signals is performed using DWT. The DWT is used in order to detect the high frequency components. The coefficient details (phase A, B, C and zero sequence of post-fault current signals) of DWT at the first peak time that positive sequence current can detect fault, are performed as an input for the fuzzy logic. The result shows that the accuracy of the proposed algorithm is highly satisfactory. © 2013 ICIC International.
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Wireless intelligent fall detection and movement classification using fuzzy logic
(2012-12-01)
Putchana, Wuttichai
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Chivapreecha, Sorawat
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Limpiti, Tulaya
Global population aging leads to increased interests in preventive healthcare technology. As falls are the most common cause of injury or death in old persons, fall detection and movement classification is one of the key topics in this research area. In this paper we propose a simple wireless intelligent system prototype for fall detection and movement classification for real-time monitoring of the elderly. The portable sensor unit acquires data from a triaxial accelerometer and sends the data wirelessly to a computer using Zigbee technology. Alternative to classic methods, the movement data is analyzed using a fuzzy inference system. The system is designed to distinguish between four movement types: standing, sitting, forward fall, and backward fall. Its classification accuracy is investigated using experimental data. It is observed that the system performs well with high sensitivity and excellent specificity. Additionally, the system is applicable for monitoring rehabilitative patients and is extendable to a larger class of movements and postures. ©2012 IEEE.
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The combination of discrete wavelet transform and fuzzy logic algorithm for fault classification on transmission system
(2012-10-01)
Ngaopitakkul, Atthapol
In the literature for fault classification, several decision algorithms have different solutions and techniques. The most research works have only considered the fault diagnosis for single bus systems and two-bus systems. In fact, transmission lines are connected to each other and become a large grid connected system. During faults, it is necessary for the protection system to deal with a complicated transmission network. This paper proposes a new technique using discrete wavelet transform (DWT) and Fuzzy Logic in order to identify the fault types on transmission systems. The DWT is used to detect the high frequency components from these signals. Positive sequence current signals are used in fault detection decision algorithm. The variations of first scale high frequency component that detects fault are used as an input for the fuzzy logic. Various cases studies based on Thailand electricity transmission systems have been investigated so that the algorithm can be implemented. Fuzzy logic is also compared with the comparison of the coefficients DWT technique. The proposed method gives satisfactory accuracy, and will be very useful in the development of a modern protection scheme for electrical power transmission systems. ICIC International © 2012.
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Mobile path loss prediction with image segmentation and classification
(2007-10-01)
Phaiboon, Supachai
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Phokharatkul, Pisit
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Kittithamavongs, Piti
This paper presents an intelligent radio wave propagation prediction model by using the 2-dimension aerial image which is taken from the actual area. An suburban area is used as examples. The prediction procedure is done in three steps. First, the image segmentation is employed to divide the area image into subgroups by using Maximum Likelihood algorithm. The second step uses the subgroup images from step 1 to determine the parameters for the fuzzy model that we use to classify the propagation areas. The final step is to plot the path loss contour on the image so the cellular cell site can be chosen. The research results show that the proposed segmentation provides an accuracy of 80-90% compared with the actual area. Therefore, cell site selection can be designed on the 2-dimension aerial map with the error less than 8 dB.
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DC motor speed control using fuzzy logic based on LabVIEW
(2006-12-01)
Thepsatorn, P.
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Numsomran, A.
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Tipsuwanporn, V.
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Teanthong, T.
This paper presents implement in speed control of a separately excited DC motor using fuzzy logic control (FLC) based on Lab VIEW (Laboratory Virtual Instrument Engineering Workbench) program. Lab VIEW, is a graphical programming environment suited for high-level or system-level design. Therefore, the principle that are data flow model, different from text-base programming and a sequential model. The user-friendly interface and toolbox design are shown the high level of suitableness and stability of Lab VIEW and fuzzy logic on speed control of DC motor. The fuzzy logic controller designed to applies the required control voltage that sent to dc motor based on fuzzy rule base of motor speed error ( e ) and change of speed error (ce). The results show the control as a FLC that do the comparison with PI and PIP Controller. © 2006 ICASE.
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Energy saving of three-phase induction motor using fuzzy controller
(2006-12-01)
Tipsuwanporn, V.
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Intajag, S.
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Harnnarong, S.
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Krongratana, V.
This paper presents energy saving of three-phase induction motor, which is operated in regenerative mode. In this mode, the energy flows back into DC link voltage and causes to occur high voltage in capacitor that may be destroy the capacitor and switching component such an IGBT. The proposed method presents connection buck converter circuit between the rectifier diodes and the inverter, to control the voltage feeding into the inverter by using two fuzzy controllers. The first fuzzy controller will be managing the switching duty cycle of buck converter. The second fuzzy controller, which provide to control the switching component of braking circuit. The second controller will be synchronized with the first controller to balance the energy of the capacitor. © 2006 ICASE.

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