Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer su...Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.展开更多
Approximate linear methods and nonlinear methods were adopted usually for solving models of nonlinear surveying and mapping parameters adjustment. But, these iterative algorithms need to compare harsh initial value. A...Approximate linear methods and nonlinear methods were adopted usually for solving models of nonlinear surveying and mapping parameters adjustment. But, these iterative algorithms need to compare harsh initial value. A kind of new algorithm-adaptive algorithm based on analyzing the general methods was put forward. The new algorithm has quick rate of convergence and low dependence for initial value, so it can avoid calculating complex second derivative of the target function. The results indicate that its performance is better than those of the others.展开更多
Study on solving nonlinear least squares adjustment by parameters is one of the most important and new subjects in modern surveying and mapping field . Many researchers have done a lot of work and gained some solving ...Study on solving nonlinear least squares adjustment by parameters is one of the most important and new subjects in modern surveying and mapping field . Many researchers have done a lot of work and gained some solving methods. These methods mainly include iterative algorithms and direct algorithms mainly. The former searches some methods of rapid convergence based on which surveying adjustment is a kind of problem of nonlinear programming. Among them the iterative algorithms of the most in common use are the Gauss-Newton method, damped least quares, quasi-Newton method and some mutations etc. Although these methods improved the quantity of the observation results to a certain degree, and increased the accuracy of the adjustment results, what we want is whether the initial values of unknown parameters are close to their real values. Of course, the model of the latter has better degree in linearity, that is to say, they nearly have the meaning of deeper theories researches. This paper puts forward a kind of method of solving the problems of nonlinear least squares adjustment by parameters based on neural network theory, and studies its stability and convergency. The results of calculating of living example indicate the method acts well for solving parameters problems by nonlinear least squares adjustment without giving exact approximation of parameters.展开更多
Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-sh...Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-shifting.The transient characteristics of energy spectrum were described by the Gaussian function space,and then the Gaussian function space was transferred by parameter adjustment method.Furthermore,the spectrum-shifting in measurement of energy spectrum was simulated.The applied example shows that the parameters can be adjusted flexibly by this method to meet the various requirements in simulation of energy spectrum-shifting.This method was one parameterized simulation method with good performance for the practical application.展开更多
For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration o...For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration of the map. The explicit expressions for the parameter adjustments are derived, and strict proof of convergence for method is given.展开更多
Closed-loop deep brain stimulation(DBS):DBS has been established as a surgical therapy for movement disorders and select neuropsychiatric disorders.Various efforts to improve the clinical outcomes of the procedure ...Closed-loop deep brain stimulation(DBS):DBS has been established as a surgical therapy for movement disorders and select neuropsychiatric disorders.Various efforts to improve the clinical outcomes of the procedure have been previously made.Several factors affect the DBS clinical outcomes such as lead position,programming technique,展开更多
This paper presents a method of tuning governor control parameters of an isolated hydropower generator considering the primary frequency performance and small-signal stability. First, generators that can be operated i...This paper presents a method of tuning governor control parameters of an isolated hydropower generator considering the primary frequency performance and small-signal stability. First, generators that can be operated in isolated state are identified. Second, different schemes are proposed for generator mode switching from on-grid to off-grid state through comparison and mechanism analysis. Third, the time domain model and frequency domain model of the isolated generator governor are constructed to respectively estimate the primary frequency performance and small signal stability. Parameter sets that satisfy the primary frequency performance and small signal stability are acquired as optimal values of governor control parameters. Finally, the measurement-based parameters of the governor are identified and validated using simulations to demonstrate the feasibility and effectiveness of the method.展开更多
Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration numbe...Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration number, computation time and convergence in a mine ventilation network analysis, were investigated based on 5 mine ventilation systems. The results show that a higher computation accuracy greatly influences the iteration number. When the accuracy reaches 10-6m3·s-1 for solving a complicated mine ventilation network, the running time is too long though a high-speed computer is used. The preliminary value of airflow rate in the range of 1100m3·s-1 has little effects the iteration number. The structure of network also has some effect on the iteration number.展开更多
The assessment of an energy retrofit necessarily requires an energy measurement campaign before (base year energy consumption) and after (post retrofit energy consumption) the retrofit. Only in this way is it possible...The assessment of an energy retrofit necessarily requires an energy measurement campaign before (base year energy consumption) and after (post retrofit energy consumption) the retrofit. Only in this way is it possible to reach a safe conclusion, on the true retrofit impact. In addition, a number of adjustments are necessary to secure that the retrofit impact on energy consumption is effectively isolated, i.e., which we report on the true retrofit impact and not, for example, on external variations, such as a more mild winter. This paper introduces a conceptual framework for taking account, in the retrofit impact assessment, of three external parameters: weather, indoor comfort and space occupancy. The broader strategy behind this work is to develop a comprehensive methodology that would allow a cost efficient, fast and accurate assessment of energy retrofits in buildings. This would allow insight, on the investor side, as to the prudence of his investment and, and in this way, could help the proliferation of the practice of energy retrofits. The adjustment methodology, introduced here, is a first step in this direction.展开更多
文摘Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.
基金Project (40174003) supported by the National Natural Science Foundation of China
文摘Approximate linear methods and nonlinear methods were adopted usually for solving models of nonlinear surveying and mapping parameters adjustment. But, these iterative algorithms need to compare harsh initial value. A kind of new algorithm-adaptive algorithm based on analyzing the general methods was put forward. The new algorithm has quick rate of convergence and low dependence for initial value, so it can avoid calculating complex second derivative of the target function. The results indicate that its performance is better than those of the others.
基金Project (40174003) supported by the National Natural Science Foundation of China
文摘Study on solving nonlinear least squares adjustment by parameters is one of the most important and new subjects in modern surveying and mapping field . Many researchers have done a lot of work and gained some solving methods. These methods mainly include iterative algorithms and direct algorithms mainly. The former searches some methods of rapid convergence based on which surveying adjustment is a kind of problem of nonlinear programming. Among them the iterative algorithms of the most in common use are the Gauss-Newton method, damped least quares, quasi-Newton method and some mutations etc. Although these methods improved the quantity of the observation results to a certain degree, and increased the accuracy of the adjustment results, what we want is whether the initial values of unknown parameters are close to their real values. Of course, the model of the latter has better degree in linearity, that is to say, they nearly have the meaning of deeper theories researches. This paper puts forward a kind of method of solving the problems of nonlinear least squares adjustment by parameters based on neural network theory, and studies its stability and convergency. The results of calculating of living example indicate the method acts well for solving parameters problems by nonlinear least squares adjustment without giving exact approximation of parameters.
基金Supported by National Natural Science Foundation of China(41204133)Scientific Reserch Fund of Sichuan Provincial Education Department(13ZA0066)Cultivating programme of excellent innovation team of Chengdu University of technology(KYTD201301)
文摘Based on the statistical characteristics of energy spectrum and the features of spectrum-shifting in spectrometry,the parameter adjustment method of Gaussian function space was applied in the simulation of spectrum-shifting.The transient characteristics of energy spectrum were described by the Gaussian function space,and then the Gaussian function space was transferred by parameter adjustment method.Furthermore,the spectrum-shifting in measurement of energy spectrum was simulated.The applied example shows that the parameters can be adjusted flexibly by this method to meet the various requirements in simulation of energy spectrum-shifting.This method was one parameterized simulation method with good performance for the practical application.
文摘For the two_parameter family of planar mapping, a method to stabilize an unstable fixed point without stable manifold embedding in hyperchaos is introduced. It works by adjusting the two parameters in each iteration of the map. The explicit expressions for the parameter adjustments are derived, and strict proof of convergence for method is given.
基金supported by Japan Society for the Promotion of Science(JSPS)Grant-in-Aid for young scientists(B)15K19984JSPS Fujita Memorial Fund for Medical Research,Takeda Science Foundation+1 种基金Uehara Memorial FoundationCentral Research Institute of Fukuoka University(No.161042)
文摘Closed-loop deep brain stimulation(DBS):DBS has been established as a surgical therapy for movement disorders and select neuropsychiatric disorders.Various efforts to improve the clinical outcomes of the procedure have been previously made.Several factors affect the DBS clinical outcomes such as lead position,programming technique,
基金supported by the Fujian Provincial Government Project (Title: Research on whole process evaluation of dynamic stability and control strategy in condition of grid connection of ultra-high voltage and large scale penetration of nuclear power.No.2015H0023)the State Grid Science & Technology Project (Title: Research on the improvement on stability of primary frequency of generator in account of the tolerance of equipment.No.52130417002P)the Key project of State Grid Fujian Electric Power Company,Ltd (research on key technologies of primary frequency power oscillation mechanism analysis and inhibition measures in large-scale unit in Fujian power grid.No.52130417000J)
文摘This paper presents a method of tuning governor control parameters of an isolated hydropower generator considering the primary frequency performance and small-signal stability. First, generators that can be operated in isolated state are identified. Second, different schemes are proposed for generator mode switching from on-grid to off-grid state through comparison and mechanism analysis. Third, the time domain model and frequency domain model of the isolated generator governor are constructed to respectively estimate the primary frequency performance and small signal stability. Parameter sets that satisfy the primary frequency performance and small signal stability are acquired as optimal values of governor control parameters. Finally, the measurement-based parameters of the governor are identified and validated using simulations to demonstrate the feasibility and effectiveness of the method.
基金Project (50474050) supported by the National Natural Science Foundation of China
文摘Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration number, computation time and convergence in a mine ventilation network analysis, were investigated based on 5 mine ventilation systems. The results show that a higher computation accuracy greatly influences the iteration number. When the accuracy reaches 10-6m3·s-1 for solving a complicated mine ventilation network, the running time is too long though a high-speed computer is used. The preliminary value of airflow rate in the range of 1100m3·s-1 has little effects the iteration number. The structure of network also has some effect on the iteration number.
文摘The assessment of an energy retrofit necessarily requires an energy measurement campaign before (base year energy consumption) and after (post retrofit energy consumption) the retrofit. Only in this way is it possible to reach a safe conclusion, on the true retrofit impact. In addition, a number of adjustments are necessary to secure that the retrofit impact on energy consumption is effectively isolated, i.e., which we report on the true retrofit impact and not, for example, on external variations, such as a more mild winter. This paper introduces a conceptual framework for taking account, in the retrofit impact assessment, of three external parameters: weather, indoor comfort and space occupancy. The broader strategy behind this work is to develop a comprehensive methodology that would allow a cost efficient, fast and accurate assessment of energy retrofits in buildings. This would allow insight, on the investor side, as to the prudence of his investment and, and in this way, could help the proliferation of the practice of energy retrofits. The adjustment methodology, introduced here, is a first step in this direction.