As one of the most serious natural disasters,many typhoons affect southeastern China every year.Taking Shenzhen,a coastal city in southeast China as an example,we employed a Monte-Carlo simulation to generate a large ...As one of the most serious natural disasters,many typhoons affect southeastern China every year.Taking Shenzhen,a coastal city in southeast China as an example,we employed a Monte-Carlo simulation to generate a large number of virtual typhoons for wind hazard analysis.By analyzing 67-year historical typhoons data from 1949 to 2015 using the Best Track Dataset for Tropical Cyclones over the Western North Pacific recorded by the Shanghai Typhoon Institute,China Meteorological Administration(CMASTI),typhoon characteristic parameters were extracted and optimal statistical distributions established for the parameters in relation to Shenzhen.We employed the Monte-Carlo method to sample each distribution to generate the characteristic parameters of virtual typhoons.In addition,the Yah Meng(YM)wind field model was introduced,and the sensitivity of the YM model to several parameters discussed.Using the YM wind field model,extreme wind speeds were extracted from the virtual typhoons.The extreme wind speeds for different return periods were predicted and compared with the current structural code to provide improved wind load information for wind-resistant structural design.展开更多
An accurate probability distribution model of wind speed is critical to the assessment of reliability contribution of wind energy to power systems. Most of current models are built using the parametric density estimat...An accurate probability distribution model of wind speed is critical to the assessment of reliability contribution of wind energy to power systems. Most of current models are built using the parametric density estimation(PDE) methods, which usually assume that the wind speed are subordinate to a certain known distribution(e.g. Weibull distribution and Normal distribution) and estimate the parameters of models with the historical data. This paper presents a kernel density estimation(KDE) method which is a nonparametric way to estimate the probability density function(PDF) of wind speed. The method is a kind of data-driven approach without making any assumption on the form of the underlying wind speed distribution, and capable of uncovering the statistical information hidden in the historical data. The proposed method is compared with three parametric models using wind data from six sites.The results indicate that the KDE outperforms the PDE in terms of accuracy and flexibility in describing the longterm wind speed distributions for all sites. A sensitivity analysis with respect to kernel functions is presented and Gauss kernel function is proved to be the best one. Case studies on a standard IEEE reliability test system(IEEERTS) have verified the applicability and effectiveness of the proposed model in evaluating the reliability performance of wind farms.展开更多
Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations a...Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.展开更多
Highly wind power integrated power system requires continuous active power regulation to tackle the power imbalances resulting from the wind power forecast errors. The active power balance is maintained in real-time w...Highly wind power integrated power system requires continuous active power regulation to tackle the power imbalances resulting from the wind power forecast errors. The active power balance is maintained in real-time with the automatic generation control and also from the control room, where regulating power bids are activated manually. In this article, an algorithm is developed to simulate the activation of regulating power bids, as performed in the control room, during power imbalance between generation and load demand. In addition, the active power balance is also controlled through automatic generation control, where coordinated control strategy between combined heat and power plants and wind power plant enhances the secure power system operation. The developed algorithm emulating the control room response,to deal with real-time power imbalance, is applied and investigated on the future Danish power system model. The power system model takes the hour-ahead regulating power plan from power balancing model and the generation and power exchange capacities for the year 2020 into account.The real-time impact of power balancing in a highly wind power integrated power system is assessed and discussed by means of simulations for different possible scenarios.展开更多
This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variati...This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.展开更多
基金Supported by the National Key Research and Development Program of China(Nos.2016YFC1402004,2016YFC1402000,2018YFC1407003)the National Natural Science Foundation of China(Nos.U1706216,U1606402,41421005)
文摘As one of the most serious natural disasters,many typhoons affect southeastern China every year.Taking Shenzhen,a coastal city in southeast China as an example,we employed a Monte-Carlo simulation to generate a large number of virtual typhoons for wind hazard analysis.By analyzing 67-year historical typhoons data from 1949 to 2015 using the Best Track Dataset for Tropical Cyclones over the Western North Pacific recorded by the Shanghai Typhoon Institute,China Meteorological Administration(CMASTI),typhoon characteristic parameters were extracted and optimal statistical distributions established for the parameters in relation to Shenzhen.We employed the Monte-Carlo method to sample each distribution to generate the characteristic parameters of virtual typhoons.In addition,the Yah Meng(YM)wind field model was introduced,and the sensitivity of the YM model to several parameters discussed.Using the YM wind field model,extreme wind speeds were extracted from the virtual typhoons.The extreme wind speeds for different return periods were predicted and compared with the current structural code to provide improved wind load information for wind-resistant structural design.
基金supported in part by the National Natural Science Foundation of China(No.51307185)Natural Science Foundation Project of CQ CSTC(No.cstc2012jjA90004)the Fundamental Research Funds for the Central Universities(No.CDJPY12150002)
文摘An accurate probability distribution model of wind speed is critical to the assessment of reliability contribution of wind energy to power systems. Most of current models are built using the parametric density estimation(PDE) methods, which usually assume that the wind speed are subordinate to a certain known distribution(e.g. Weibull distribution and Normal distribution) and estimate the parameters of models with the historical data. This paper presents a kernel density estimation(KDE) method which is a nonparametric way to estimate the probability density function(PDF) of wind speed. The method is a kind of data-driven approach without making any assumption on the form of the underlying wind speed distribution, and capable of uncovering the statistical information hidden in the historical data. The proposed method is compared with three parametric models using wind data from six sites.The results indicate that the KDE outperforms the PDE in terms of accuracy and flexibility in describing the longterm wind speed distributions for all sites. A sensitivity analysis with respect to kernel functions is presented and Gauss kernel function is proved to be the best one. Case studies on a standard IEEE reliability test system(IEEERTS) have verified the applicability and effectiveness of the proposed model in evaluating the reliability performance of wind farms.
基金supported by the State Key Laboratory of the Smart Grid Protection and Control of China and“111”project:Large Scale Power Grid Protection and Safety Defense 2.0(BP0820024)。
文摘Electrical power generation from wind technology is the most rapidly growing technology due to its ample characteristics.Nevertheless,because of its stochastic feature,it has the unnecessary impact on the operations and stability of the power grid system.The fluctuation of the grid frequency problem,for example,is more pronounced.The fluctuation of the frequency in turn impacts even the collapse of the power system.To minimize such problems,a droop-vector control strategy applied on a doubly-fed induction machine based(DFIM)variable speed pumped storage(VSPS)system is proposed in this paper.This method is should be used as a wind power fluctuation compensation solution in the wind farm-grid integration system.The system model is made on the basis of the technique called a phasor model.The frequency spectrum analysis approach is used in the VSPS plant for determining the dynamic performances of the grid in case of contingencies including wind power fluctuation compensation.The software platform MATLAB/Simulink is used for verifying the performance of the proposed system.The results show that the method of the frequency spectrum analysis technique is effective for determining the wind power fluctuation and stability requirements in large power networks.The control strategy proposed in this paper implementing the VSC-DFIM based VSPS plant integrated with the power gird and wind farm network achieves a well-controlled power flow and stable grid frequency with the deviations being in acceptable ranges.
基金a part of Ph.D.project funded by Sino-Danish centre for education and research(SDC)
文摘Highly wind power integrated power system requires continuous active power regulation to tackle the power imbalances resulting from the wind power forecast errors. The active power balance is maintained in real-time with the automatic generation control and also from the control room, where regulating power bids are activated manually. In this article, an algorithm is developed to simulate the activation of regulating power bids, as performed in the control room, during power imbalance between generation and load demand. In addition, the active power balance is also controlled through automatic generation control, where coordinated control strategy between combined heat and power plants and wind power plant enhances the secure power system operation. The developed algorithm emulating the control room response,to deal with real-time power imbalance, is applied and investigated on the future Danish power system model. The power system model takes the hour-ahead regulating power plan from power balancing model and the generation and power exchange capacities for the year 2020 into account.The real-time impact of power balancing in a highly wind power integrated power system is assessed and discussed by means of simulations for different possible scenarios.
基金supported by the Natural Sciences and Engineering Research Council of Canada(NSERC)(No.11R82911)the Institute of Computing,Information and Cognitive Systems(ICICS)at the University of British Columbia
文摘This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction.
