One-dimensional ring power system is discredited to a number of nodes each containing a generator with internal reactance and load branch of resistance and reactance with a certain power factor. When a disturbance occ...One-dimensional ring power system is discredited to a number of nodes each containing a generator with internal reactance and load branch of resistance and reactance with a certain power factor. When a disturbance occurs at any machine in the power system, simulative analysis is performed to verify how the variation of load power factor affecting the behavior of electromechanical wave propagation by using the MATLAB package, from which different situations are presented and discussed. These results show the type of load has no effect on the behavior of electromechanical wave propagation.展开更多
The validity of electric power system simulation or prediction models depends on static load model. Measurement- based approach is the unique method to identify them adequately. The measured power depends on both load...The validity of electric power system simulation or prediction models depends on static load model. Measurement- based approach is the unique method to identify them adequately. The measured power depends on both load reaction to supply voltage alteration and random process of load alteration Basically, there is no any universal method that can single out the inherent static load model from experimental data. The paper offers a proprietary technique which is the particular solution of the task. The technique considers the selection of neighboring measurement pairs with the supply voltage altering significantly be-tween them, the exclusion of selected pairs by load power factor and subsequent selection of the inherent static load model presented as the polynomial load model. The usage of the technique to identify static load model at “Fenster” industrial enterprise （in Borisov city） is presented. The ideas considered in the paper can be used for future development of static load model identification methods with the data obtained during both active experiment and in other operating models of electric power systems.展开更多
Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods, a back-propagation artificial neural network （BP-ANN） based method for short-term load forecasting is presented ...Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods, a back-propagation artificial neural network （BP-ANN） based method for short-term load forecasting is presented in this paper. The forecast points are related to prophase adjacent data as well as the periodical long-term historical load data. Then the short-term load forecasting model of Shanxi Power Grid （China） based on BP-ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP-ANN method is simple and with higher precision and practicality.展开更多
According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are comput...According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.展开更多
Since the existing prediction methods have encountered difficulties in processing themultiple influencing factors in short-term power load forecasting,we propose a bidirectional long short-term memory(BiLSTM)neural ne...Since the existing prediction methods have encountered difficulties in processing themultiple influencing factors in short-term power load forecasting,we propose a bidirectional long short-term memory(BiLSTM)neural network model based on the temporal pattern attention(TPA)mechanism.Firstly,based on the grey relational analysis,datasets similar to forecast day are obtained.Secondly,thebidirectional LSTM layermodels the data of thehistorical load,temperature,humidity,and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network,so that the influencing factors(with different characteristics)can select relevant information from different time steps to reduce the prediction error of the model.Simultaneously,the complex and nonlinear dependencies between time steps and sequences are extracted by the TPA mechanism,so the attention weight vector is constructed for the hidden layer output of BiLSTM and the relevant variables at different time steps are weighted to influence the input.Finally,the chaotic sparrow search algorithm(CSSA)is used to optimize the hyperparameter selection of the model.The short-term power load forecasting on different data sets shows that the average absolute errors of short-termpower load forecasting based on our method are 0.876 and 4.238,respectively,which is lower than other forecastingmethods,demonstrating the accuracy and stability of our model.展开更多
Accurate power load forecasting plays an important role in the power dispatching and security of grid.In this paper,a mathematical model for power load forecasting based on the random forest regression(RFR)was establi...Accurate power load forecasting plays an important role in the power dispatching and security of grid.In this paper,a mathematical model for power load forecasting based on the random forest regression(RFR)was established.The input parameters of RFR model were determined by means of the grid search algorithm.The prediction results for this model were compared with those for several other common machine learning methods.It was found that the coefficient of determination(R^(2))of test set based on the RFR model was the highest,reaching 0.514 while the corresponding mean absolute error(MAE)and the mean squared error(MSE)were the lowest.Besides,the impacts of the air conditioning system used in summer on the power load were discussed.The calculation results showed that the introduction of indexes in the field of Heating,Ventilation and Air Conditioning(HVAC)could improve the prediction accuracy of test set.展开更多
For digital channelized frequency division multiple access based satellite communication(SATCOM) systems,it is a challenging but critical issue to improve the transponder power and spectrum efficiency simultaneously u...For digital channelized frequency division multiple access based satellite communication(SATCOM) systems,it is a challenging but critical issue to improve the transponder power and spectrum efficiency simultaneously under limited and non-linear high-power amplifier conditions.In this paper,different from the traditional link supportability designs aiming at minimizing the total transponder output power,a maximal sum Shannon capacity optimization objective is firstly raised subject to link supportability constraints.Furthermore,an efficient multilevel optimization(MO) algorithm is proposed to solve the considered optimization problem in the case of single link for each terminal.Moreover,in the case of multiple links for one terminal,an improved MO algorithm involving Golden section and discrete gradient searching procedures is proposed to optimize power allocation over all links.Finally,several numerical results are provided to demonstrate the effectiveness of our proposals.Comparison results show that,by the MO algorithm,not only all links' supportability can be guaranteed but also a larger sum capacity can be achieved with lower complexity.展开更多
In order to test the klystrons operated at a frequency of 3.7 GHz in a continuous wave （CW） mode, a type of water load to absorb its power up to 750 kW is presented. The distilled water sealed with an RF ceramic win...In order to test the klystrons operated at a frequency of 3.7 GHz in a continuous wave （CW） mode, a type of water load to absorb its power up to 750 kW is presented. The distilled water sealed with an RF ceramic window is used as the absorbent. At a frequency range of 70 MHz, the VSWR （Voltage Standing Wave Ratio） is below 1.2, and the rise in temperature of water is about 30 ℃ at the highest power level.展开更多
This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power ...This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power load into each department of the hospital.Firstly,the key influencing factors of the power loads were screened based on the grey relational degree analysis.Secondly,in view of the characteristics of the power loads affected by various factors and time series changes,the feature attention mechanism and sequential attention mechanism were introduced on the basis of LSTM network.The former was used to analyze the relationship between the historical information and input variables autonomously to extract important features,and the latter was used to select the historical information at critical moments of LSTM network to improve the stability of long-term prediction effects.In the end,the experimental results from the power loads of Shanxi Eye Hospital show that the LSTM model based on the double attention mechanism has the higher forecasting accuracy and stability than the conventional LSTM,CNN-LSTM and attention-LSTM models.展开更多
The DC microgrid has the advantages of high energy conversion efficiency,high energy transmission density,no reactive power flow,and grid-connected synchronization.It is an essential component of the future intelligen...The DC microgrid has the advantages of high energy conversion efficiency,high energy transmission density,no reactive power flow,and grid-connected synchronization.It is an essential component of the future intelligent power distribution system.Constant power load(CPL)will degrade the stability of the DC microgrid and cause system voltage oscillation due to its negative resistance characteristics.As a result,the stability of DC microgrids with CPL has become a problem.At present,the research on the stability of DC microgrid is mainly focused on unipolar DC microgrid,while the research on bipolar DC microgrid lacks systematic discussion.The stability of DC microgrid using CPL was studied first,and then the current stability criteria of DC microgrid were summarized,and its research trend was analyzed.On this basis,aiming at the stability problem caused by CPL,the existing control methods were summarized from the perspective of source converter output impedance and load converter input impedance,and the current control methods were outlined as active and passive control methods.Lastly,the research path of bipolar DC microgrid stability with CPL was prospected.展开更多
This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying tur...This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying turbulent wind fields have been under extensive investigation in recent years. We divide the related research activities into three categories： modeling and dynamics of wind turbines, active control of wind turbines, and passive control of wind turbines. Regarding turbine dynamics, we discuss the physical fundamentals and present the aeroelastic analysis tools. Regarding active control, we review pitch control, torque control, and yaw control strategies encompassing mathematical formulations as well as their applications toward different objectives. Our survey mostly focuses on blade pitch control, which is considered one of the key elements in facilitating load reduction while maintaining power capture performance. Regarding passive control, we review techniques such as tuned mass dampers, smart rotors, and microtabs. Possible future directions are suggested.展开更多
This paper presents a new approach for deriving a power system aggregate load area model (ALAM). In this approach, an equivalent area load model is derived to represent the load characters for a particular area load o...This paper presents a new approach for deriving a power system aggregate load area model (ALAM). In this approach, an equivalent area load model is derived to represent the load characters for a particular area load of a power system network. The Particle Swarm Optimization (PSO) method is employed to identify the unknown parameters of the generalised system, ALAM, based on the system measurement directly using a one-step scheme. Simulation studies are carried out for an IEEE 14-Bus power system and an IEEE 57-Bus power system. Simulation results show that the ALAM can represent the area load characters accurately under different operational conditions and at different power system states.展开更多
The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator cont...The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.展开更多
In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in...In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in redundant load mode. A new control system is designed by combining the redundant electronic load module, embedded controller, supportive capacitor and boost circuit. The system adjusts duty ratio of boost circuit dynamically based on the maximum power point parameter provided by redundant load unit in order to realize MPPT. An experiment shows that no matter whether system is under an even illumination or partly perturbed by shadow, this method can find the exact maximum power point.展开更多
The ability of power system to survive the transition from preloading state to the gradual increase in load and thereafter reach an acceptable operational condition is an indication of transient stability of the syste...The ability of power system to survive the transition from preloading state to the gradual increase in load and thereafter reach an acceptable operational condition is an indication of transient stability of the system. The study analyzed load shedding scheme through the use of empirical measurement tools and load-flow simulation techniques. It was geared towards determining effective load shedding strategies to reduce unnecessary overload in order to achieve dynamic stability of the electric power network in the Export Free Trade Zone, Calabar, Nigeria. From the tests and the measurements taken, it was observed that the real and reactive powers from the generator and the mechanical power from the turbine engine were stable when the load shedding controller was switched on, as compared to when it was off. The engine speed, the bus-bar frequency and the output voltage of the generator stabilized within a shorter time (about 8 seconds) when the controller was switched on than when it was on the off condition. Also, there were noticeable fluctuations in the speed of the remaining two generators. It became stable at about 12 seconds after the loss. The variations were 0.3 per cent of the nominal speed value. The excitation voltage fluctuated from 1.2 (pu) to 4.5 (pu) when the bus voltage dipped as a result of additional load. It then came down and stabilized at 1.8 (pu) after few swings. This confirmed that the stability of power system is much enhanced when load shedding controllers are effectively configured on the network.展开更多
In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power in...In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power injected by wind farms. The method proposed is based on the generation of correlated series of power values, which can be used in a MonteCarlo simulation, to obtain the probability density function of the power through branches of an electrical network.展开更多
Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could n...Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.展开更多
Despite the increasing popularity of mechanized coal mining, there are no convenient and accurate means available to measure the loads of powered supports. The measurement of such loads is important for monitoring min...Despite the increasing popularity of mechanized coal mining, there are no convenient and accurate means available to measure the loads of powered supports. The measurement of such loads is important for monitoring mine pressure and ensuring production safety. The load-carrying features of a powered support were used to develop a method for load measurement using the mag-netoelastic principle. A cross bridge-type magnetoelastic stress sensor was designed for the support structures to measure the different parts of the supports. Tests on single-body hydraulic cylinders and simulated linkages showed that an approximately linear relationship between the values of the sensor output signal and the loads borne by the hydraulic cylinders or linkages. The results were used to analyze the load-carrying measurements of powered supports with the cross bridge-type magnetoelastic stress sensor.展开更多
文摘One-dimensional ring power system is discredited to a number of nodes each containing a generator with internal reactance and load branch of resistance and reactance with a certain power factor. When a disturbance occurs at any machine in the power system, simulative analysis is performed to verify how the variation of load power factor affecting the behavior of electromechanical wave propagation by using the MATLAB package, from which different situations are presented and discussed. These results show the type of load has no effect on the behavior of electromechanical wave propagation.
基金Supported by National Natural Science Foundation of China （60674039, 60704004） and Innovation Fund for Outstanding Scholar of Henan Province （084200510009 ）
文摘The validity of electric power system simulation or prediction models depends on static load model. Measurement- based approach is the unique method to identify them adequately. The measured power depends on both load reaction to supply voltage alteration and random process of load alteration Basically, there is no any universal method that can single out the inherent static load model from experimental data. The paper offers a proprietary technique which is the particular solution of the task. The technique considers the selection of neighboring measurement pairs with the supply voltage altering significantly be-tween them, the exclusion of selected pairs by load power factor and subsequent selection of the inherent static load model presented as the polynomial load model. The usage of the technique to identify static load model at “Fenster” industrial enterprise （in Borisov city） is presented. The ideas considered in the paper can be used for future development of static load model identification methods with the data obtained during both active experiment and in other operating models of electric power systems.
文摘Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods, a back-propagation artificial neural network （BP-ANN） based method for short-term load forecasting is presented in this paper. The forecast points are related to prophase adjacent data as well as the periodical long-term historical load data. Then the short-term load forecasting model of Shanxi Power Grid （China） based on BP-ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP-ANN method is simple and with higher precision and practicality.
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.
基金supported by the Major Project of Basic and Applied Research in Guangdong Universities (2017WZDXM012)。
文摘Since the existing prediction methods have encountered difficulties in processing themultiple influencing factors in short-term power load forecasting,we propose a bidirectional long short-term memory(BiLSTM)neural network model based on the temporal pattern attention(TPA)mechanism.Firstly,based on the grey relational analysis,datasets similar to forecast day are obtained.Secondly,thebidirectional LSTM layermodels the data of thehistorical load,temperature,humidity,and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network,so that the influencing factors(with different characteristics)can select relevant information from different time steps to reduce the prediction error of the model.Simultaneously,the complex and nonlinear dependencies between time steps and sequences are extracted by the TPA mechanism,so the attention weight vector is constructed for the hidden layer output of BiLSTM and the relevant variables at different time steps are weighted to influence the input.Finally,the chaotic sparrow search algorithm(CSSA)is used to optimize the hyperparameter selection of the model.The short-term power load forecasting on different data sets shows that the average absolute errors of short-termpower load forecasting based on our method are 0.876 and 4.238,respectively,which is lower than other forecastingmethods,demonstrating the accuracy and stability of our model.
基金supported by National Natural Science Foundation of China(Grant 61273151).
文摘Accurate power load forecasting plays an important role in the power dispatching and security of grid.In this paper,a mathematical model for power load forecasting based on the random forest regression(RFR)was established.The input parameters of RFR model were determined by means of the grid search algorithm.The prediction results for this model were compared with those for several other common machine learning methods.It was found that the coefficient of determination(R^(2))of test set based on the RFR model was the highest,reaching 0.514 while the corresponding mean absolute error(MAE)and the mean squared error(MSE)were the lowest.Besides,the impacts of the air conditioning system used in summer on the power load were discussed.The calculation results showed that the introduction of indexes in the field of Heating,Ventilation and Air Conditioning(HVAC)could improve the prediction accuracy of test set.
基金supportedin part by Natural Science Foundation under grant No.91338108,91438206Co-innovation Laboratory of Aerospace Broadband Network Technology
文摘For digital channelized frequency division multiple access based satellite communication(SATCOM) systems,it is a challenging but critical issue to improve the transponder power and spectrum efficiency simultaneously under limited and non-linear high-power amplifier conditions.In this paper,different from the traditional link supportability designs aiming at minimizing the total transponder output power,a maximal sum Shannon capacity optimization objective is firstly raised subject to link supportability constraints.Furthermore,an efficient multilevel optimization(MO) algorithm is proposed to solve the considered optimization problem in the case of single link for each terminal.Moreover,in the case of multiple links for one terminal,an improved MO algorithm involving Golden section and discrete gradient searching procedures is proposed to optimize power allocation over all links.Finally,several numerical results are provided to demonstrate the effectiveness of our proposals.Comparison results show that,by the MO algorithm,not only all links' supportability can be guaranteed but also a larger sum capacity can be achieved with lower complexity.
文摘In order to test the klystrons operated at a frequency of 3.7 GHz in a continuous wave （CW） mode, a type of water load to absorb its power up to 750 kW is presented. The distilled water sealed with an RF ceramic window is used as the absorbent. At a frequency range of 70 MHz, the VSWR （Voltage Standing Wave Ratio） is below 1.2, and the rise in temperature of water is about 30 ℃ at the highest power level.
基金Supported by the Shaanxi Provincial Education Department 2022 Key Research Program Project(22JS022)the National Natural Science Foundation of China(51808428)
文摘This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power load into each department of the hospital.Firstly,the key influencing factors of the power loads were screened based on the grey relational degree analysis.Secondly,in view of the characteristics of the power loads affected by various factors and time series changes,the feature attention mechanism and sequential attention mechanism were introduced on the basis of LSTM network.The former was used to analyze the relationship between the historical information and input variables autonomously to extract important features,and the latter was used to select the historical information at critical moments of LSTM network to improve the stability of long-term prediction effects.In the end,the experimental results from the power loads of Shanxi Eye Hospital show that the LSTM model based on the double attention mechanism has the higher forecasting accuracy and stability than the conventional LSTM,CNN-LSTM and attention-LSTM models.
基金supported by National Natural Science Foundation of China(No.51767015)Key Project of Natural Science Foundation of Gansu Province(No.22JR5RA317)Tianyou Innovation Team Support Program of Lanzhou Jiaotong University(No.TY202009)。
文摘The DC microgrid has the advantages of high energy conversion efficiency,high energy transmission density,no reactive power flow,and grid-connected synchronization.It is an essential component of the future intelligent power distribution system.Constant power load(CPL)will degrade the stability of the DC microgrid and cause system voltage oscillation due to its negative resistance characteristics.As a result,the stability of DC microgrids with CPL has become a problem.At present,the research on the stability of DC microgrid is mainly focused on unipolar DC microgrid,while the research on bipolar DC microgrid lacks systematic discussion.The stability of DC microgrid using CPL was studied first,and then the current stability criteria of DC microgrid were summarized,and its research trend was analyzed.On this basis,aiming at the stability problem caused by CPL,the existing control methods were summarized from the perspective of source converter output impedance and load converter input impedance,and the current control methods were outlined as active and passive control methods.Lastly,the research path of bipolar DC microgrid stability with CPL was prospected.
基金This work is supported in part by the US National Science Foundation （CMM11300236）.
文摘This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying turbulent wind fields have been under extensive investigation in recent years. We divide the related research activities into three categories： modeling and dynamics of wind turbines, active control of wind turbines, and passive control of wind turbines. Regarding turbine dynamics, we discuss the physical fundamentals and present the aeroelastic analysis tools. Regarding active control, we review pitch control, torque control, and yaw control strategies encompassing mathematical formulations as well as their applications toward different objectives. Our survey mostly focuses on blade pitch control, which is considered one of the key elements in facilitating load reduction while maintaining power capture performance. Regarding passive control, we review techniques such as tuned mass dampers, smart rotors, and microtabs. Possible future directions are suggested.
基金supported by the National Natural Science Foundation of China(61203129,61174038,61473151,51507080)the Fundamental Research Funds for the Central Universities(30915011104,30920130121010,30920140112005)
文摘This paper presents a new approach for deriving a power system aggregate load area model (ALAM). In this approach, an equivalent area load model is derived to represent the load characters for a particular area load of a power system network. The Particle Swarm Optimization (PSO) method is employed to identify the unknown parameters of the generalised system, ALAM, based on the system measurement directly using a one-step scheme. Simulation studies are carried out for an IEEE 14-Bus power system and an IEEE 57-Bus power system. Simulation results show that the ALAM can represent the area load characters accurately under different operational conditions and at different power system states.
文摘The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.
基金the National Natural Science Foundation of China(No.61107064)the Leading Academic Discipline Project of Communication and Information System(No.XXKZD1605)
文摘In order to ensure that the photovoltaic(PV) array always works at the global maximum point of power to increase the system's overall efficiency, this paper leads the study on maximum power point tracking(MPPT) in redundant load mode. A new control system is designed by combining the redundant electronic load module, embedded controller, supportive capacitor and boost circuit. The system adjusts duty ratio of boost circuit dynamically based on the maximum power point parameter provided by redundant load unit in order to realize MPPT. An experiment shows that no matter whether system is under an even illumination or partly perturbed by shadow, this method can find the exact maximum power point.
文摘The ability of power system to survive the transition from preloading state to the gradual increase in load and thereafter reach an acceptable operational condition is an indication of transient stability of the system. The study analyzed load shedding scheme through the use of empirical measurement tools and load-flow simulation techniques. It was geared towards determining effective load shedding strategies to reduce unnecessary overload in order to achieve dynamic stability of the electric power network in the Export Free Trade Zone, Calabar, Nigeria. From the tests and the measurements taken, it was observed that the real and reactive powers from the generator and the mechanical power from the turbine engine were stable when the load shedding controller was switched on, as compared to when it was off. The engine speed, the bus-bar frequency and the output voltage of the generator stabilized within a shorter time (about 8 seconds) when the controller was switched on than when it was on the off condition. Also, there were noticeable fluctuations in the speed of the remaining two generators. It became stable at about 12 seconds after the loss. The variations were 0.3 per cent of the nominal speed value. The excitation voltage fluctuated from 1.2 (pu) to 4.5 (pu) when the bus voltage dipped as a result of additional load. It then came down and stabilized at 1.8 (pu) after few swings. This confirmed that the stability of power system is much enhanced when load shedding controllers are effectively configured on the network.
文摘In this paper a procedure is established for solving the Probabilistic Load Flow in an electrical power network, considering correlation between power generated by power plants, loads demanded on each bus and power injected by wind farms. The method proposed is based on the generation of correlated series of power values, which can be used in a MonteCarlo simulation, to obtain the probability density function of the power through branches of an electrical network.
基金Supported by the Science and Technology Research Project Fund of Provincial Department of Education(12531004)Project of Heilongjiang Leading Talent Echelon Talented(2012)
文摘Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.
文摘Despite the increasing popularity of mechanized coal mining, there are no convenient and accurate means available to measure the loads of powered supports. The measurement of such loads is important for monitoring mine pressure and ensuring production safety. The load-carrying features of a powered support were used to develop a method for load measurement using the mag-netoelastic principle. A cross bridge-type magnetoelastic stress sensor was designed for the support structures to measure the different parts of the supports. Tests on single-body hydraulic cylinders and simulated linkages showed that an approximately linear relationship between the values of the sensor output signal and the loads borne by the hydraulic cylinders or linkages. The results were used to analyze the load-carrying measurements of powered supports with the cross bridge-type magnetoelastic stress sensor.
