Pub Date : 2016-11-01DOI: 10.1109/POWERI.2016.8077376
Ankita Sharma, Om Prakash Mahela, S. Ola
Recently the open-access and competitive market power policy has been adopted by the utilities. Now, the electricity consumers are in a position to demand and expect a higher quality of service. The utilities and power providers have to provide a high quality of service to remain competitive as well as to retain or attract the customers. To achieve this goal an efficient power quality (PQ) monitoring and analysis system is required. This paper presents an S-transform based technique for the detection of power system operational events and power quality disturbances associated with these events. The power quality disturbances associated with the power system operational events such as switching on and off the loads, switching on and off the capacitor banks, tripping and reclosing the transmission lines, outage of the generator and utility network has been investigated effectively. The detailed simulation study of power quality disturbances has been carried out in MATLAB/Simulink environment.
{"title":"Detection of power quality disturbances in the utility grid using stockwell transform","authors":"Ankita Sharma, Om Prakash Mahela, S. Ola","doi":"10.1109/POWERI.2016.8077376","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077376","url":null,"abstract":"Recently the open-access and competitive market power policy has been adopted by the utilities. Now, the electricity consumers are in a position to demand and expect a higher quality of service. The utilities and power providers have to provide a high quality of service to remain competitive as well as to retain or attract the customers. To achieve this goal an efficient power quality (PQ) monitoring and analysis system is required. This paper presents an S-transform based technique for the detection of power system operational events and power quality disturbances associated with these events. The power quality disturbances associated with the power system operational events such as switching on and off the loads, switching on and off the capacitor banks, tripping and reclosing the transmission lines, outage of the generator and utility network has been investigated effectively. The detailed simulation study of power quality disturbances has been carried out in MATLAB/Simulink environment.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122472327","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077348
R. Garg, N. Gupta
Power factor correction is one of the major issue in electrical power system for maintaining its high efficiency. Low power factor leads to draw extra power from the source to fulfill the same power demand of load. This paper presents a technology named as Magnetic Energy Recovery Switch (MERS) for improving the power factor by compensating reactive power. MERS consists of four semiconductor devices (with antiparallel diodes) connected in full bridge configuration and a DC capacitor. Simulation study is conducted with resistive- Inductive load (to create the reactive power demand) and results are compared with and without MERS, whereas experimental analysis confirms the potential and effectiveness of the proposed technology for power factor improvement.
{"title":"Experimental analysis of power factor correction using magnetic energy recovery switch","authors":"R. Garg, N. Gupta","doi":"10.1109/POWERI.2016.8077348","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077348","url":null,"abstract":"Power factor correction is one of the major issue in electrical power system for maintaining its high efficiency. Low power factor leads to draw extra power from the source to fulfill the same power demand of load. This paper presents a technology named as Magnetic Energy Recovery Switch (MERS) for improving the power factor by compensating reactive power. MERS consists of four semiconductor devices (with antiparallel diodes) connected in full bridge configuration and a DC capacitor. Simulation study is conducted with resistive- Inductive load (to create the reactive power demand) and results are compared with and without MERS, whereas experimental analysis confirms the potential and effectiveness of the proposed technology for power factor improvement.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126655203","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077237
Arjun Swami, P. Gaur
The objective of this paper is to control the speed of a non-linear D.C. servo motor using various control techniques. Installing only a Proportional controller (P) to control the system, it is observed that there is high overshoot (OS), undershoot (US) and the system takes time to achieve its steady state. The performance of the system relatively improves by installing a conventional PID controller as it decreases the overshoot, undershoot of the system and the system attains steady state faster. The conventional PID controller cannot tackle the nonlinear systems effectively and gives a poor tracking and disturbance rejection performance. In order to further improve the response of the system, Improved Self Tuning Fuzzy (ISTF)-PID controller has been used. In this technique fuzzy logic is used to tune the gains of a PID controller. The various control techniques that are discussed in this paper are designed to achieve the desired D.C. servo motor speed.
{"title":"ISTF-pid based D.C. servo motor control","authors":"Arjun Swami, P. Gaur","doi":"10.1109/POWERI.2016.8077237","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077237","url":null,"abstract":"The objective of this paper is to control the speed of a non-linear D.C. servo motor using various control techniques. Installing only a Proportional controller (P) to control the system, it is observed that there is high overshoot (OS), undershoot (US) and the system takes time to achieve its steady state. The performance of the system relatively improves by installing a conventional PID controller as it decreases the overshoot, undershoot of the system and the system attains steady state faster. The conventional PID controller cannot tackle the nonlinear systems effectively and gives a poor tracking and disturbance rejection performance. In order to further improve the response of the system, Improved Self Tuning Fuzzy (ISTF)-PID controller has been used. In this technique fuzzy logic is used to tune the gains of a PID controller. The various control techniques that are discussed in this paper are designed to achieve the desired D.C. servo motor speed.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125232147","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077464
U. Kalla, Deven Gurjar, K. Rathore, Prateek Dixit
This Paper dealt with the design of an efficient controller for Photovoltaic operated permanent magnet brushless DC (PMBLDC) motor based electric vehicle system in MATLAB/Simulink platform. In the proposed scheme modeling and simulation of photovoltaic system, MPPT, and PMBLDC motor is carried out and simulation results are also presented in this paper.
{"title":"An efficient controller for PV operated PMBLDC drive based electric vehicle system","authors":"U. Kalla, Deven Gurjar, K. Rathore, Prateek Dixit","doi":"10.1109/POWERI.2016.8077464","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077464","url":null,"abstract":"This Paper dealt with the design of an efficient controller for Photovoltaic operated permanent magnet brushless DC (PMBLDC) motor based electric vehicle system in MATLAB/Simulink platform. In the proposed scheme modeling and simulation of photovoltaic system, MPPT, and PMBLDC motor is carried out and simulation results are also presented in this paper.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125324869","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077180
R. Ghosh, B. Chatterjee, S. Dalai
In an acoustic partial discharge (PD) detection system, estimation of time difference of arrival (TDOA) between acoustic signals arriving at a sensor array is an important criterion for accurate localization of PD sources inside a transformer. The localization accuracy can be improved by improving the accuracy of estimation of TDOA between sensors. The estimation of TDOA is a challenging task because acoustic signals are corrupted by noise, reverberation, echo and reflection of acoustic signals inside the transformer tank. Keeping this in mind, this paper presents a technique for the accurate estimation of TDOA by extraction of an estimate of the PD pulse from the recorded acoustic signals. The TDOA between two sensors is then calculated by finding the cross-correlation function between the two sensors. The acoustic path through the transformer tank and oil constitutes the physical system, which when excited by the PD pulse, gives rise to the acoustic pressure waves. An estimate of the PD pulse, which generates the acoustic pressure waves, may therefore be obtained by separating the acoustic response of the tank-oil physical system from the acoustic signal. The extracted PD pulse information gives an estimate of the instant of appearance of the PD pulse at each sensor, which makes the accurate estimation of TDOA possible.
{"title":"A new method for the estimation of time difference of arrival for localization of partial discharge sources using acoustic detection technique","authors":"R. Ghosh, B. Chatterjee, S. Dalai","doi":"10.1109/POWERI.2016.8077180","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077180","url":null,"abstract":"In an acoustic partial discharge (PD) detection system, estimation of time difference of arrival (TDOA) between acoustic signals arriving at a sensor array is an important criterion for accurate localization of PD sources inside a transformer. The localization accuracy can be improved by improving the accuracy of estimation of TDOA between sensors. The estimation of TDOA is a challenging task because acoustic signals are corrupted by noise, reverberation, echo and reflection of acoustic signals inside the transformer tank. Keeping this in mind, this paper presents a technique for the accurate estimation of TDOA by extraction of an estimate of the PD pulse from the recorded acoustic signals. The TDOA between two sensors is then calculated by finding the cross-correlation function between the two sensors. The acoustic path through the transformer tank and oil constitutes the physical system, which when excited by the PD pulse, gives rise to the acoustic pressure waves. An estimate of the PD pulse, which generates the acoustic pressure waves, may therefore be obtained by separating the acoustic response of the tank-oil physical system from the acoustic signal. The extracted PD pulse information gives an estimate of the instant of appearance of the PD pulse at each sensor, which makes the accurate estimation of TDOA possible.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124400455","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077175
J. Bhutto, Richpal Bana
This paper presents the design & analysis of D-STATCOM using ICCT with conventional controllers to improve the power quality. The use of AC circuits in electrical power system has been a common practice nearly since the very inception of the interconnected power network. The most familiar loads on such a system were the constant power, constant impedance and constant current loads or a linear combination of thereof. In these cases, the voltage and current wave forms are nearly sinusoidal. But this is no longer the case with modern electric power system. Enormous use of the non-linear and time varying devices has led to distortion of source voltage and source current waveforms. As a consequence, recently the issue of power quality has become important. Both electric utility and end users of electric power are becoming increasingly concerned about the quality of electric power. The simulation model and results of proposed scheme are described and discussed in this paper.
{"title":"Design & analysis of D-STATCOM for power quality improvement using ICCT with conventional controllers","authors":"J. Bhutto, Richpal Bana","doi":"10.1109/POWERI.2016.8077175","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077175","url":null,"abstract":"This paper presents the design & analysis of D-STATCOM using ICCT with conventional controllers to improve the power quality. The use of AC circuits in electrical power system has been a common practice nearly since the very inception of the interconnected power network. The most familiar loads on such a system were the constant power, constant impedance and constant current loads or a linear combination of thereof. In these cases, the voltage and current wave forms are nearly sinusoidal. But this is no longer the case with modern electric power system. Enormous use of the non-linear and time varying devices has led to distortion of source voltage and source current waveforms. As a consequence, recently the issue of power quality has become important. Both electric utility and end users of electric power are becoming increasingly concerned about the quality of electric power. The simulation model and results of proposed scheme are described and discussed in this paper.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127842141","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077285
Tanmay Tandel, U. Mate, Snehal Unde, Atul Gupta, Siddhartho Chaudhary
In the modern world, almost 90 percent of the motors used in the industry are induction motors. Induction motors are used in wide range of applications ranging from fans, pumps, compressors to their use in complex drives for critical application. As the world advances, newer applications come up which require robustness and complete operational control over an induction motor, when subjected to most adverse dynamic real time conditions. These applications need to be controlled using control techniques such as Field Oriented Control, which require the knowledge of induction motor. Use of sensors adds to the cost. If the machine parameters are known, it is possible to eliminate the use such costly hardware speed sensors and replace them with software speed estimators. Scope of this paper is design, simulation and implementation of speed estimation algorithm by estimating the rotor flux angle and slip in a Digital Signal Processor(DSP). The rotor flux angle and estimated speed can be used in sensor-less rotor field oriented control scheme. First, a code is developed for speed estimation of induction motor and is tested in MATLAB. Later, this code is ported to TMS320F28335 floating point DSP and is tested on a 415V, 3.3 HP 1430 RPM squirrel cage induction motor to estimate its speed in real-time.
在现代世界，工业中使用的电机几乎90%是感应电机。感应电机的应用范围很广，从风扇、泵、压缩机到关键应用的复杂驱动器。随着世界的进步，新的应用出现了，当受到最不利的动态实时条件时，需要对感应电机进行鲁棒性和完全的操作控制。这些应用需要使用控制技术进行控制，如磁场定向控制，这需要感应电机的知识。传感器的使用增加了成本。如果机器参数是已知的，就有可能消除使用这种昂贵的硬件速度传感器，并用软件速度估计器代替它们。本文的研究范围是在数字信号处理器(DSP)中通过估计转子磁链角和转差率来实现转速估计算法的设计、仿真和实现。转子磁链角和估计转速可用于无传感器转子定向控制方案。首先，编写了异步电动机转速估计代码，并在MATLAB中进行了测试。随后，将此代码移植到TMS320F28335浮点DSP上，并在一台415V, 3.3 HP 1430 RPM的鼠笼式异步电动机上进行测试，实时估算其转速。
{"title":"Speed estimation of induction motor using TMS320F28335 digital signal processor","authors":"Tanmay Tandel, U. Mate, Snehal Unde, Atul Gupta, Siddhartho Chaudhary","doi":"10.1109/POWERI.2016.8077285","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077285","url":null,"abstract":"In the modern world, almost 90 percent of the motors used in the industry are induction motors. Induction motors are used in wide range of applications ranging from fans, pumps, compressors to their use in complex drives for critical application. As the world advances, newer applications come up which require robustness and complete operational control over an induction motor, when subjected to most adverse dynamic real time conditions. These applications need to be controlled using control techniques such as Field Oriented Control, which require the knowledge of induction motor. Use of sensors adds to the cost. If the machine parameters are known, it is possible to eliminate the use such costly hardware speed sensors and replace them with software speed estimators. Scope of this paper is design, simulation and implementation of speed estimation algorithm by estimating the rotor flux angle and slip in a Digital Signal Processor(DSP). The rotor flux angle and estimated speed can be used in sensor-less rotor field oriented control scheme. First, a code is developed for speed estimation of induction motor and is tested in MATLAB. Later, this code is ported to TMS320F28335 floating point DSP and is tested on a 415V, 3.3 HP 1430 RPM squirrel cage induction motor to estimate its speed in real-time.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127757980","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077305
A. Azeem, G. Kumar, H. Malik
Wind resource assessment is essential to evaluate the future wind power generation from a wind farm. As wind power generation depends directly on wind speed, therefore accurate wind speed prediction facilitates wind power generation. In this paper generalized regression neural network is employed for accurate wind speed prediction. The performance of proposed approach is evaluated using publically available dataset of different cities in India. Air temperature, earth temperature, relative humidity, daily solar radiation, elevation, latitude, heating degree days, cooling degree days, longitude and atmospheric pressure are used as input variables. Correlation coefficient of 0.99909 is obtained during training and 0.95143 during testing of GRNN model. The proposed GRNN model is then utilized to find wind speed and power potential of major wind power generating sites of Andhra Pradesh, India. A comparison between the measured and forecasted wind speed and power values validate that generalized regression neural network is an appropriate technique for long term wind speed and power prediction.
{"title":"Artificial neural network based intelligent model for wind power assessment in India","authors":"A. Azeem, G. Kumar, H. Malik","doi":"10.1109/POWERI.2016.8077305","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077305","url":null,"abstract":"Wind resource assessment is essential to evaluate the future wind power generation from a wind farm. As wind power generation depends directly on wind speed, therefore accurate wind speed prediction facilitates wind power generation. In this paper generalized regression neural network is employed for accurate wind speed prediction. The performance of proposed approach is evaluated using publically available dataset of different cities in India. Air temperature, earth temperature, relative humidity, daily solar radiation, elevation, latitude, heating degree days, cooling degree days, longitude and atmospheric pressure are used as input variables. Correlation coefficient of 0.99909 is obtained during training and 0.95143 during testing of GRNN model. The proposed GRNN model is then utilized to find wind speed and power potential of major wind power generating sites of Andhra Pradesh, India. A comparison between the measured and forecasted wind speed and power values validate that generalized regression neural network is an appropriate technique for long term wind speed and power prediction.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127426771","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077332
S. Bhasker, M. Tripathy, Vishal Kumar
This paper describes a technique for the detection of type of internal fault in an indirect symmetrical phase shift transformer (ISPST). An application of Pattern Recognition Network (PRN) is proposed as a core classifier to identify the type of internal fault. Four type of internal faults (turn-to-turn (TT), line-to-ground (LG), two line-to-ground (LLG), and three line-to-ground (LLLG)) have been classified. Numerous test cases of internal fault in an ISPST have been using PSCAD/EMTDC software. These cases are formed on the basic variation of different parameters of ISPST like fault inception angle, fault resistance loading condition and percentage of winding. The accuracy of the proposed technique is evaluated over a large number of cases and it is observed that the technique gives the results with high accuracy even in presence of noise in the signal.
{"title":"Identification of type of internal fault in indirect symmetrical phase shift transformer based on PRN","authors":"S. Bhasker, M. Tripathy, Vishal Kumar","doi":"10.1109/POWERI.2016.8077332","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077332","url":null,"abstract":"This paper describes a technique for the detection of type of internal fault in an indirect symmetrical phase shift transformer (ISPST). An application of Pattern Recognition Network (PRN) is proposed as a core classifier to identify the type of internal fault. Four type of internal faults (turn-to-turn (TT), line-to-ground (LG), two line-to-ground (LLG), and three line-to-ground (LLLG)) have been classified. Numerous test cases of internal fault in an ISPST have been using PSCAD/EMTDC software. These cases are formed on the basic variation of different parameters of ISPST like fault inception angle, fault resistance loading condition and percentage of winding. The accuracy of the proposed technique is evaluated over a large number of cases and it is observed that the technique gives the results with high accuracy even in presence of noise in the signal.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133673264","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 : 2016-11-01DOI: 10.1109/POWERI.2016.8077378
Jyothi Varanasi, M. M. Tripathi
Power generation from renewable energy sources needs great attention for future power sector to meet steadily increasing power demand and to reduce global warming. But, wind power generation is very unsure and intermittent in its nature. Wind power forecasting assists grid integration of enormous capacity wind farms to great extent. Grid stability is greatly accrued with the help of correct wind power forecasting This paper describes the suitability of NARX Artificial neural network in wind power forecasting with the historical power data accessible from European nation Belgium wind farms and meteorological information for wind speed.
{"title":"Artificial neural network based wind power forecasting in belgium","authors":"Jyothi Varanasi, M. M. Tripathi","doi":"10.1109/POWERI.2016.8077378","DOIUrl":"https://doi.org/10.1109/POWERI.2016.8077378","url":null,"abstract":"Power generation from renewable energy sources needs great attention for future power sector to meet steadily increasing power demand and to reduce global warming. But, wind power generation is very unsure and intermittent in its nature. Wind power forecasting assists grid integration of enormous capacity wind farms to great extent. Grid stability is greatly accrued with the help of correct wind power forecasting This paper describes the suitability of NARX Artificial neural network in wind power forecasting with the historical power data accessible from European nation Belgium wind farms and meteorological information for wind speed.","PeriodicalId":332286,"journal":{"name":"2016 IEEE 7th Power India International Conference (PIICON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130646404","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：