Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712314
D. Bellan
This paper investigates the statistical effects of additive noise on the magnitude of the space-vector spectral lines estimated through a discrete Fourier transform (DFT). In fact, the space vector is a well-known and effective tool for monitoring power quality issues in modern power systems. In many practical cases waveform distortion requires a DFT in order to extract the fundamental component and the harmonic/interharmonic content. In particular, the space vector shape (on the complex plane) of the fundamental component provides information such as voltage dips, whereas space-vector spectral lines provide information related to waveform distortion. Additive noise mainly impacts on low-magnitude spectral lines which require a statistical characterization. Conventional results available in the literature cannot be used in a straightforward way because a space vector is a complex-valued function, therefore special care is needed for proper interpretation and use of its properties in the frequency domain. In the paper, the probability density function, the mean value and the variance of the magnitude of space-vector DFT spectral lines are derived in closed form. Analytical results are validated by means of numerical simulations.
{"title":"On the Statistical Characterization of the Discrete Fourier Transform of Noisy Space Vectors","authors":"D. Bellan","doi":"10.1109/IEECON.2018.8712314","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712314","url":null,"abstract":"This paper investigates the statistical effects of additive noise on the magnitude of the space-vector spectral lines estimated through a discrete Fourier transform (DFT). In fact, the space vector is a well-known and effective tool for monitoring power quality issues in modern power systems. In many practical cases waveform distortion requires a DFT in order to extract the fundamental component and the harmonic/interharmonic content. In particular, the space vector shape (on the complex plane) of the fundamental component provides information such as voltage dips, whereas space-vector spectral lines provide information related to waveform distortion. Additive noise mainly impacts on low-magnitude spectral lines which require a statistical characterization. Conventional results available in the literature cannot be used in a straightforward way because a space vector is a complex-valued function, therefore special care is needed for proper interpretation and use of its properties in the frequency domain. In the paper, the probability density function, the mean value and the variance of the magnitude of space-vector DFT spectral lines are derived in closed form. Analytical results are validated by means of numerical simulations.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"53 4","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91494082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712254
Kishan Bhushan Sahay, Khushboo Singh
With deregulation much attention is given to electricity price forecasting. Some of the factors which affect forecast are day of the week, weather, season, hour of the day, year, and special days. In general, the main factor which drives the electricity price is power demand. Here, ANN algorithms i.e. Bayesian Regularization, Levenberg Marquardt back propagation & Scaled Conjugate Gradient algorithms has been applied in short-term price forecasting that is, the one hour-ahead forecast of the electricity price using MATLAB R14a. The simulation results have shown accurate one hour ahead forecasts.
{"title":"Short-Term Price Forecasting by Using ANN Algorithms","authors":"Kishan Bhushan Sahay, Khushboo Singh","doi":"10.1109/IEECON.2018.8712254","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712254","url":null,"abstract":"With deregulation much attention is given to electricity price forecasting. Some of the factors which affect forecast are day of the week, weather, season, hour of the day, year, and special days. In general, the main factor which drives the electricity price is power demand. Here, ANN algorithms i.e. Bayesian Regularization, Levenberg Marquardt back propagation & Scaled Conjugate Gradient algorithms has been applied in short-term price forecasting that is, the one hour-ahead forecast of the electricity price using MATLAB R14a. The simulation results have shown accurate one hour ahead forecasts.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"24 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84840436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712166
H. Swalehe, B. Marungsri
One of the essential factor for the better operation of an electrical power system is load demand. Normally, higher load demand leads to instability and insufficient power supply. To make an electrical power system stable and sufficient, a good correlation between demand and supply should exist. A survey conducted during 2011 indicated that residential sector is consuming 18% of total energy. Also, the demand was seen to increase rapidly close to and sometimes beyond the supply. Hence, this paper focuses on appliance scheduling for cost reduction and peak load reduction by increasing demand-side response in the smart home. A load management algorithm is developed in MATLAB which reduces both cost and peak load consumption by managing the operation according to utility controls and consumer preferences. The optimization problem was solved by using Genetic Algorithm (GA) technique. The simulation results depicted that GA can be adopted for appliance scheduling in the household, reduction of electrc bill as well as cutback of peak demand from the demand side.
{"title":"Intelligent Algorithm for Optimal Load Management in Smart Home Appliance Scheduling in Distribution System","authors":"H. Swalehe, B. Marungsri","doi":"10.1109/IEECON.2018.8712166","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712166","url":null,"abstract":"One of the essential factor for the better operation of an electrical power system is load demand. Normally, higher load demand leads to instability and insufficient power supply. To make an electrical power system stable and sufficient, a good correlation between demand and supply should exist. A survey conducted during 2011 indicated that residential sector is consuming 18% of total energy. Also, the demand was seen to increase rapidly close to and sometimes beyond the supply. Hence, this paper focuses on appliance scheduling for cost reduction and peak load reduction by increasing demand-side response in the smart home. A load management algorithm is developed in MATLAB which reduces both cost and peak load consumption by managing the operation according to utility controls and consumer preferences. The optimization problem was solved by using Genetic Algorithm (GA) technique. The simulation results depicted that GA can be adopted for appliance scheduling in the household, reduction of electrc bill as well as cutback of peak demand from the demand side.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"58 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83129422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712287
Veerasak Chanarungruengkij, S. Kaitwanidvilai
This article proposes an application of lean and automated system to improve the efficiency, productivity and reduce the waste in Thailand's control cable manufacturing process for the automotive industry. By improving the 7 wastes in process and reducing the process flow by automating the process integration process to achieve continuous flow. As results indicated, the proposed system can reduce the inventory parts of the process to 0, the cycle time of the process by 61.25%, and the operation distance by 75%.
{"title":"An Application of Lean Automation: A Case Study of Thailand's Control Cable Manufacturing","authors":"Veerasak Chanarungruengkij, S. Kaitwanidvilai","doi":"10.1109/IEECON.2018.8712287","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712287","url":null,"abstract":"This article proposes an application of lean and automated system to improve the efficiency, productivity and reduce the waste in Thailand's control cable manufacturing process for the automotive industry. By improving the 7 wastes in process and reducing the process flow by automating the process integration process to achieve continuous flow. As results indicated, the proposed system can reduce the inventory parts of the process to 0, the cycle time of the process by 61.25%, and the operation distance by 75%.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"24 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84390648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712225
Pattrakorn Chokchalermwat, B. Supmonchai
This paper presents the circuit level design of a CMOS low power limiting amplifier with received signal strength indicator (RSSI) for low frequency application. The design utilizes a five-stage cascade amplifier with PMOS double diode-connected load for the limiting amplifier and a successive detection log amp for the RSSI structure. DC feedback technique is employed to suppress the DC offset at the output. The proposed circuit is laid out in $pmb{0.13 mu}mathbf{m}$ CMOS technology, then extracted and simulated. It occupies a minimal active area of 0.0084 mm2and is able to operate within a frequency range of 17 kHz to 166 kHz with an RSSI error less than 2dB, while consumes only $pmb{1.96mu}mathbf{A}$ current. It also achieves the −3dB input sensitivity of less than $pmb{12mu}mathbf{V}_{mathbf{rms}}$ for a typical dynamic range of 81.7 dB, and a maximum settling time of $pmb{236} pmb{mu}mathbf{s}$. Compared with best performer circuits, our design has the lowest power consumption while other performance aspects are comparable or better.
{"title":"Design of a CMOS Low-Power Limiting Amplifier with RSSI Integrated Circuit for Low-Frequency Wake-Up Receivers","authors":"Pattrakorn Chokchalermwat, B. Supmonchai","doi":"10.1109/IEECON.2018.8712225","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712225","url":null,"abstract":"This paper presents the circuit level design of a CMOS low power limiting amplifier with received signal strength indicator (RSSI) for low frequency application. The design utilizes a five-stage cascade amplifier with PMOS double diode-connected load for the limiting amplifier and a successive detection log amp for the RSSI structure. DC feedback technique is employed to suppress the DC offset at the output. The proposed circuit is laid out in $pmb{0.13 mu}mathbf{m}$ CMOS technology, then extracted and simulated. It occupies a minimal active area of 0.0084 mm2and is able to operate within a frequency range of 17 kHz to 166 kHz with an RSSI error less than 2dB, while consumes only $pmb{1.96mu}mathbf{A}$ current. It also achieves the −3dB input sensitivity of less than $pmb{12mu}mathbf{V}_{mathbf{rms}}$ for a typical dynamic range of 81.7 dB, and a maximum settling time of $pmb{236} pmb{mu}mathbf{s}$. Compared with best performer circuits, our design has the lowest power consumption while other performance aspects are comparable or better.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"144 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83582868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712170
W. Nakawiro
Evolutionary algorithm (EA) has been well accepted as a suitable tool for solving non-convex economic dispatch problems. However the major challenge is how to handle both equality and inequality constraints properly. The penalized fitness is commonly used to evaluate quality of candidate solutions. Moreover searching for feasible space is very difficult for a problem with large number of variables and number of constraints. This paper proposes a general framework which can be applied to any EA for handling constraints in ED problems. Four EAs namely differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO) and harmony search (HS) were selected to demonstrate effectiveness in solving a non-convex ED problem of a 15 unit power system. Simulation results reveal that with the proposed constraint handling all optimization algorithms converge to the identical result based on 20 independent trials.
{"title":"A Comparative Study on Constraint Handling for Solving Economic Dispatch by Evolutionary Algorithms","authors":"W. Nakawiro","doi":"10.1109/IEECON.2018.8712170","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712170","url":null,"abstract":"Evolutionary algorithm (EA) has been well accepted as a suitable tool for solving non-convex economic dispatch problems. However the major challenge is how to handle both equality and inequality constraints properly. The penalized fitness is commonly used to evaluate quality of candidate solutions. Moreover searching for feasible space is very difficult for a problem with large number of variables and number of constraints. This paper proposes a general framework which can be applied to any EA for handling constraints in ED problems. Four EAs namely differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO) and harmony search (HS) were selected to demonstrate effectiveness in solving a non-convex ED problem of a 15 unit power system. Simulation results reveal that with the proposed constraint handling all optimization algorithms converge to the identical result based on 20 independent trials.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"16 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89265234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712169
Kazuki Aihara, Kazuyuki Ito
Robots that operate in real complex situations, such as rescue missions, maintenance and inspections of large infrastructure, and agricultural activities, have attracted considerable attention. In this research, we propose a new leg mechanism that can vary the stiffness of the leg and improve our previous multi-legged robot for rubble environment.
{"title":"Adaptive Switching Mechanism of Leg Stiffness for Multi-Legged Robot","authors":"Kazuki Aihara, Kazuyuki Ito","doi":"10.1109/IEECON.2018.8712169","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712169","url":null,"abstract":"Robots that operate in real complex situations, such as rescue missions, maintenance and inspections of large infrastructure, and agricultural activities, have attracted considerable attention. In this research, we propose a new leg mechanism that can vary the stiffness of the leg and improve our previous multi-legged robot for rubble environment.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"54 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89292084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712298
D. Puangdownreong, Somchai Sumpunsri, Montri Sukchum, C. Thammarat, S. Hlangnamthip, A. Nawikavatan
Firefly algorithm (FA) was firstly proposed by Yang in 2008 as one of the most powerful population-based metaheuristic optimization techniques for solving the hardest optimization problems including real-world engineering practices. In this paper, the FA is applied to design an optimal proportional-integral-derivative-accelerated (PIDA) controller for the automatic voltage regulator (AVR) system. Based on the optimization context, the sum-squared errors between referent input voltage and actual terminal output voltage of the controlled system are performed as the objective function to be minimized. As results, the optimum PIDA controller for the AVR system is successfully obtained by the FA. Moreover, the FA-based design approach performs high robustness once parameter variations are occurred.
{"title":"FA-Based Optimal PIDA Controller Design for AVR System","authors":"D. Puangdownreong, Somchai Sumpunsri, Montri Sukchum, C. Thammarat, S. Hlangnamthip, A. Nawikavatan","doi":"10.1109/IEECON.2018.8712298","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712298","url":null,"abstract":"Firefly algorithm (FA) was firstly proposed by Yang in 2008 as one of the most powerful population-based metaheuristic optimization techniques for solving the hardest optimization problems including real-world engineering practices. In this paper, the FA is applied to design an optimal proportional-integral-derivative-accelerated (PIDA) controller for the automatic voltage regulator (AVR) system. Based on the optimization context, the sum-squared errors between referent input voltage and actual terminal output voltage of the controlled system are performed as the objective function to be minimized. As results, the optimum PIDA controller for the AVR system is successfully obtained by the FA. Moreover, the FA-based design approach performs high robustness once parameter variations are occurred.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"340 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79520713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712336
Kulsomsup Yenchamchalit, Y. Kongjeen, K. Bhumkittipich, N. Mithulananthan
This paper had presented the optimal battery charging station for Plug-in Electric Vehicles (PEVs) in the electrical power system, by using the Particle Swarm Optimization technique (PSO). The PEVs are represented using the Voltage Source Converter (VSC) as the group of PEVs that were installed in the charging station. The electrical power system was analyzed in a steady state, by using the IEEE 30 bus test system. The installed PEVs site in the power system aimed to minimize system power loss. The results were shown that the optimal site is bus N0.30. The total power loss and percentage of power loss reduction were 0.0994 p.u. and 6.4%, respectively.
{"title":"Optimal Sizing and Location of the Charging Station for Plug-in Electric Vehicles Using the Particle Swarm Optimization Technique","authors":"Kulsomsup Yenchamchalit, Y. Kongjeen, K. Bhumkittipich, N. Mithulananthan","doi":"10.1109/IEECON.2018.8712336","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712336","url":null,"abstract":"This paper had presented the optimal battery charging station for Plug-in Electric Vehicles (PEVs) in the electrical power system, by using the Particle Swarm Optimization technique (PSO). The PEVs are represented using the Voltage Source Converter (VSC) as the group of PEVs that were installed in the charging station. The electrical power system was analyzed in a steady state, by using the IEEE 30 bus test system. The installed PEVs site in the power system aimed to minimize system power loss. The results were shown that the optimal site is bus N0.30. The total power loss and percentage of power loss reduction were 0.0994 p.u. and 6.4%, respectively.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"7 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78993792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-01DOI: 10.1109/IEECON.2018.8712313
Kishan Bhushan Sahay, Ayushi Yadav
This paper proposes the modeling and simulation of PV array employing the Maximum Power Point Tracking (MPPT) model describing how maximum power point can be achieved with the varying load. Due to environmental conditions and load variations, PV array is influenced and the efficiency of conversion becomes low. Hence it becomes necessary to detect the peak power to maximize the energy produced during load fluctuations by MPPT technique. The requirement of MPPT controller is to ensure that at maximum power output possible, the PV power generation system gives an output. This system consists of a PV array, MPPT controller, and a converter. The working of the PV array is described with an MPPT technique and without the MPPT technique. This paper shows variation of power with MPPT and without MPPT with the help of the graph.
{"title":"Implementation of MPPT Technique in PV Array for a Varying Load by Modeling and Simulation","authors":"Kishan Bhushan Sahay, Ayushi Yadav","doi":"10.1109/IEECON.2018.8712313","DOIUrl":"https://doi.org/10.1109/IEECON.2018.8712313","url":null,"abstract":"This paper proposes the modeling and simulation of PV array employing the Maximum Power Point Tracking (MPPT) model describing how maximum power point can be achieved with the varying load. Due to environmental conditions and load variations, PV array is influenced and the efficiency of conversion becomes low. Hence it becomes necessary to detect the peak power to maximize the energy produced during load fluctuations by MPPT technique. The requirement of MPPT controller is to ensure that at maximum power output possible, the PV power generation system gives an output. This system consists of a PV array, MPPT controller, and a converter. The working of the PV array is described with an MPPT technique and without the MPPT technique. This paper shows variation of power with MPPT and without MPPT with the help of the graph.","PeriodicalId":6628,"journal":{"name":"2018 International Electrical Engineering Congress (iEECON)","volume":"61 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77390060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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