Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper prese...Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.展开更多
In this paper,the formation control problem of secondorder nonholonomic mobile robot systems is investigated in a dynamic event-triggered scheme.Event-triggered control protocols combined with persistent excitation(PE...In this paper,the formation control problem of secondorder nonholonomic mobile robot systems is investigated in a dynamic event-triggered scheme.Event-triggered control protocols combined with persistent excitation(PE)conditions are presented.In event-detecting processes,an inactive time is introduced after each sampling instant,which can ensure a positive minimum sampling interval.To increase the flexibility of the event-triggered scheme,internal dynamic variables are included in event-triggering conditions.Moreover,the dynamic event-triggered scheme plays an important role in increasing the lengths of time intervals between any two consecutive events.In addition,event-triggered control protocols without forward and angular velocities are also presented based on approximate-differentiation(low-pass)filters.The asymptotic convergence results are given based on a nested Matrosov theorem and artificial sampling methods.展开更多
China has become the world’s largest producer and consumer of energy,and ranks first in its wind and solar power installation capacity.However,serious wind and solar curtailment in China has significantly hindered th...China has become the world’s largest producer and consumer of energy,and ranks first in its wind and solar power installation capacity.However,serious wind and solar curtailment in China has significantly hindered the development and utilization of renewable energy.To address problems in the consumption of renewable energy,this paper analyzes four key factors affecting the capacity of power generated from renewable energy sources:power balance,power regulation performance,transmission capacity,and load level.Focusing on these bottlenecks,we propose seven solutions:centralized and distributed development of renewable energy,improving the peak-load regulation flexibility of thermal power,increasing the proportion of gas turbines and pumped-hydropower storage,construction of transmission channels and a flexible smart grid developing demand response and virtual power plants,adopting new energy active support and energy storage,and establishing appropriate policies and market mechanisms.The Chinese Government and energy authorities have issued a series of policies and measures,and in the past three years,China has had remarkable achievements in the adoption of renewable energy.The rate of idle wind capacity decreased from 17%in 2016 to 7%in 2018,and that of solar decreased from 10%in 2016 to 3%in 2018.展开更多
To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs base...To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.展开更多
Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
In this study, the consensus problem for a class of second-order multi-agent systems with nonuniform time delays is investigated. A linear consensus protocol is used to make all agents reach consensus and move with a ...In this study, the consensus problem for a class of second-order multi-agent systems with nonuniform time delays is investigated. A linear consensus protocol is used to make all agents reach consensus and move with a constant velocity. By a frequency-domain analysis, a simplified sufficient condition is given to guarantee the consensus stability of the dynamic system. Finally, the effectiveness of the obtained theoretical results is illustrated through numerical simulations.展开更多
Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly importa...Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.展开更多
The initial shape of the secondary arc considerably influences its subsequent shape.To establish the model for the arcing time of the secondary arc and modify the single-phase reclosing sequence,theoretical and experi...The initial shape of the secondary arc considerably influences its subsequent shape.To establish the model for the arcing time of the secondary arc and modify the single-phase reclosing sequence,theoretical and experimental analysis of the evolution process of the short-circuit arc to the secondary arc is critical.In this study,an improved charge simulation method was used to develop the internal-space electric-field model of the short-circuit arc.The intensity of the electric field was used as an independent variable to describe the initial shape of the secondary arc.A secondary arc evolution model was developed based on this model.Moreover,the accuracy of the model was evaluated by comparison with physical experimental results.When the secondary arc current increased,the arcing time and dispersion increased.There is an overall trend of increasing arc length with increasing arcing time.Nevertheless,there is a reduction in arc length during arc ignition due to short circuits between the arc columns.Furthermore,the arcing time decreased in the range of 0°-90°as the angle between the wind direction and the x-axis increased.This work investigated the method by which short-circuit arcs evolve into secondary arcs.The results can be used to develop the secondary arc evolution model and to provide both a technical and theoretical basis for secondary arc suppression.展开更多
In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. A...In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. As the difference of hybrid energy source in stability and economy, thus, this paper focuses on the network with hybrid energy source, and design the utility of each user in the hybrid energy source system from the perspective of stability, economy and environment pollution. A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed. In addition, an iteration method is proposed which enables all players to reach the Stackelberg equilibrium(SE). Simulation results validate that players can reach the SE and the utilities of users and networks can be maximization, and the green energy can be efficiently used.展开更多
This paper uses CT to gain the energy directly from the high-voltage transmission line, to address the problem of power supply for monitoring system in high voltage side of transmission line. The draw-out power coil c...This paper uses CT to gain the energy directly from the high-voltage transmission line, to address the problem of power supply for monitoring system in high voltage side of transmission line. The draw-out power coil can induce voltage from the transmission line, using single-chip microcomputer to analog and output PMW wave to control the charging module, provides a stable 3.4 V DC voltage to the load, and solve the problem of easy saturating of core. The power supply based on this kind of draw-out power coil has undergone the overall testing, and it is verified-showing that it can properly work in a non-saturated status within the current range of 50 - 1000 A, and provide a stable output. The equipment also design protection circuit to improve the reliability to avid the impacts of the impulse current or short-circuit current. It effectively solves the problem of power supply for On-line Monitoring System of Transmission.展开更多
In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing...In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing penetration of EVs and integration of distributed energy resources DER(such as photovoltaic and energy storages).Given this background,this paper proposes a comprehensive evaluation framework to investigate the potential role of DER-integrated PLs(DPL)with the capability of vehicle-to-grid(V2G)in improving the reliability of the distribution network.For this aim,first,an overview for the distribution system with DPLs is provided.Then,a generic model for the available generation capacity(AGC)of DPLs with consideration of EV scheduling strategy is developed.On the above basis,an iterative-based algorithm leveraging sequential Monte Carlo simulation is presented to quantify the contribution of DPLs to the reliability of the system.In order to verify the effectiveness of the proposed method,a series of numerical studies are carried out.The simulation results show that the integration of DPLs with the V2G capability could help to improve the reliability performance of distribution grid to a great extent and reduce the adverse impact incurred by EV accommodation,if utilized properly.展开更多
Power transformer serves as one of the most widely used electrical equipments in power grid. During the operation, terrible losses are produced. With the development of loss reduction technology of power transformers,...Power transformer serves as one of the most widely used electrical equipments in power grid. During the operation, terrible losses are produced. With the development of loss reduction technology of power transformers, in order to save energy saving and reduce emissions, the old power transformer should be replaced. The paper summarizes the main method to reduce the losses of power transformers and brings up the improved Total Owning Cost (TOC) algorithm, which applies to 220 kV power transformers’ comprehensive benefit analysis. Using the improved Total Owning Cost (TOC) algorithm, based on today 220 kV energy-saving power transformer manufacturing level, the economic benefits of new energy-saving power transformer and the return period of investment are analyzed. Finally, combined with energy-saving effect, the appropriate replacement proposal of 220 kV power transformers has been given.展开更多
This paper proposes a hybrid ocean energy sys-tem to form a virtual power plant(VPP)for participating in electricity markets in order to promote the renewable ocean energy utilization and accommodation.In the proposed...This paper proposes a hybrid ocean energy sys-tem to form a virtual power plant(VPP)for participating in electricity markets in order to promote the renewable ocean energy utilization and accommodation.In the proposed system,solar thermal energy is integrated with the closed-cycle ocean thermal energy conversion(OTEC)to boost the temperature differences between the surface and deep seawater for efficiency and flexibility improvements,and the thermodynamic effects of seawater mass flow rates on the output of solar-boosted OTEC(SOTEC)are exploited for deploying SOTEC as a renewable dispatchable unit.An optimal tidal-storage operation model is also developed to make use of subsea pumped storage(SPS)with hydrostatic pressures at ocean depths for mitigating the intermittent tidal range energy in order to make the arbitrage in the electricity market.Furthermore,a two-stage coordinated scheduling strategy is presented to optimally control seawater mass flow rates of SOTEC and hydraulic reversible pump-turbines of SPS for enhancing the daily VPP profit.Comparative studies have been investigated to confirm the superiority of the developed methodology in various renewable ocean energy and electricity market price scenarios.展开更多
With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to eva...With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.展开更多
Polyethylene oxide(PEO)-based electrolytes have obvious merits such as strong ability to dissolve salts(e.g.,LiTFSI)and high flexibility,but their applications in solid-state batteries is hindered by the low ion condu...Polyethylene oxide(PEO)-based electrolytes have obvious merits such as strong ability to dissolve salts(e.g.,LiTFSI)and high flexibility,but their applications in solid-state batteries is hindered by the low ion conductance and poor mechanical and thermal properties.Herein,poly(m-phenylene isophthalamide)(PMIA)is employed as a multifunctional additive to improve the overall properties of the PEO-based electrolytes.The hydrogen-bond interactions between PMIA and PEO/TFSI-can effectively prevent the PEO crystallization and meanwhile facilitate the LiTFSI dissociation,and thus greatly improve the ionic conductivity(two times that of the pristine electrolyte at room temperature).With the incorporation of the high-strength PMIA with tough amide-benzene backbones,the PMIA/PEO-LiTFSI composite polymer electrolyte(CPE)membranes also show much higher mechanical strength(2.96 MPa),thermostability(4190℃)and interfacial stability against Li dendrites(468 h at 0.10 mA cm-2)than the pristine electrolyte(0.32 MPa,364℃and short circuit after 246 h).Furthermore,the CPE-based LiFePO4/Li cells exhibit superior cycling stability(137 mAh g^-1 with 93%retention after 100 cycles at 0.5 C)and rate performance(123 mAh g^-1 at 1.0 C).This work provides a novel and effective CPE structure design strategy to achieve comprehensively-upgraded electrolytes for promising solid-state battery applications.展开更多
With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of ...With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of demand response(DR)resources has become a valuable solution to this problem.However,existing research indicates that problems on flexibility prediction of DR resources have not been investigated.This study applied the temporal convolution network(TCN)-combined transformer,a deep learning technique to predict the aggregated flexibility of two types of DR resources,that is,electric vehicles(EVs)and domestic hot water system(DHWS).The prediction uses historical power consumption data of these DR resources and DR signals(DSs)to facilitate prediction.The prediction can generate the size and maintenance time of the aggregated flexibility.The accuracy of the flexibility prediction results was verified through simulations of case studies.The simulation results show that under different maintenance times,the size of the flexibility changed.The proposed DR resource flexibility prediction method demonstrates its application in unlocking the demand-side flexibility to provide a reserve to grids.展开更多
According to the reciprocity principle, we propose an efficient model to compute the shielding effectiveness of a rectangular cavity with apertures covered by conductive sheet against an external incident electromagne...According to the reciprocity principle, we propose an efficient model to compute the shielding effectiveness of a rectangular cavity with apertures covered by conductive sheet against an external incident electromagnetic wave. This problem is converted into another problem of solving the electromagnetic field leakage from the cavity when the cavity is excited by an electric dipole placed within it. By the combination of the unperturbed cavity field and the transfer impedance of the sheet, the tangential electric field distribution on the outer surface of the sheet is obtained. Then, the field distribution is regarded as an equivalent surface magnetic current source responsible for the leakage field. The validation of this model is verified by a comparison with the circuital model and the full-wave simulations. This time-saving model can deal with arbitrary aperture shape, various wave propagation and polarization directions, and the near-field effect.展开更多
Compressed air pumped hydro energy storage equipment combines compressed air energy storage technology and pumped storage technology. The water is pumped to a vessel to compress air for energy storage, and the compres...Compressed air pumped hydro energy storage equipment combines compressed air energy storage technology and pumped storage technology. The water is pumped to a vessel to compress air for energy storage, and the compressed air expanses pushing water to drive the hydro turbine for power generation. The novel storage equipment saves natural gas resources, reduces carbon emission, and improves the controllability and reliability. The principle of compressed air pumped hydro energy storage is introduced and its mathematical model is built. The storage and generation process of the novel equipment is analyzed using the model. The calculation formula of the storage power is deduced in theory in different situations of isothermal and adiabatic compression. The optimal storage scheme is given when the capacity and withstand pressure of the vessel is definitive, and the max available capacity and the equipment utilization efficiency evaluation of the scheme is given.展开更多
The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing"instrumented,interconnected,and intelligent"power grids.The traditional optimal dispatch method ...The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing"instrumented,interconnected,and intelligent"power grids.The traditional optimal dispatch method can not coordinate the economic benefits of all the stakeholders from multiple regions of the transmission network,comprehensively.Hence,this study proposes a large-scale wind-power coordinated consumption strategy based on the Nash-Q method and establishes an economic dispatch model for interconnected systems considering the uncertainty of wind power,with optimal windpower consumption as the objective for redistributing the shared benefits between regions.Initially,based on the equivalent cost of the interests of stakeholders from different regions,the state decision models are respectively constructed,and the noncooperative game Nash equilibrium model is established.The Q-learning algorithm is then introduced for high-dimension decision variables in the game model,and the dispatch solution methods for interconnected systems are presented,integrating the noncooperative game Nash equilibrium and Q-learning algorithm.Finally,the proposed method is verified through the modified IEEE 39-bus interconnection system,and it is established that this method achieves reasonable distribution of interests between regions and promotes large-scale consumption of wind power.展开更多
基金supported by National Natural Science Foundation of China(61533013,61273144)Scientific Technology Research and Development Plan Project of Tangshan(13130298B)Scientific Technology Research and Development Plan Project of Hebei(z2014070)
文摘Reliable load frequency control(LFC) is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control(DMPC) based on coordination scheme.The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The generation rate constraints(GRCs), load disturbance changes, and the wind speed constraints are considered. Furthermore, the DMPC algorithm may reduce the impact of the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and without the participation of the wind turbines is carried out. Analysis and simulation results show possible improvements on closed–loop performance, and computational burden with the physical constraints.
基金supported by the Beijing Natural Science Foundation(4222053).
文摘In this paper,the formation control problem of secondorder nonholonomic mobile robot systems is investigated in a dynamic event-triggered scheme.Event-triggered control protocols combined with persistent excitation(PE)conditions are presented.In event-detecting processes,an inactive time is introduced after each sampling instant,which can ensure a positive minimum sampling interval.To increase the flexibility of the event-triggered scheme,internal dynamic variables are included in event-triggering conditions.Moreover,the dynamic event-triggered scheme plays an important role in increasing the lengths of time intervals between any two consecutive events.In addition,event-triggered control protocols without forward and angular velocities are also presented based on approximate-differentiation(low-pass)filters.The asymptotic convergence results are given based on a nested Matrosov theorem and artificial sampling methods.
基金The work was supported in part by the consulting research project of Chinese Academy of Engineering(2017-XY-16)in part by the National Natural Science Foundation of China(52061635102).
文摘China has become the world’s largest producer and consumer of energy,and ranks first in its wind and solar power installation capacity.However,serious wind and solar curtailment in China has significantly hindered the development and utilization of renewable energy.To address problems in the consumption of renewable energy,this paper analyzes four key factors affecting the capacity of power generated from renewable energy sources:power balance,power regulation performance,transmission capacity,and load level.Focusing on these bottlenecks,we propose seven solutions:centralized and distributed development of renewable energy,improving the peak-load regulation flexibility of thermal power,increasing the proportion of gas turbines and pumped-hydropower storage,construction of transmission channels and a flexible smart grid developing demand response and virtual power plants,adopting new energy active support and energy storage,and establishing appropriate policies and market mechanisms.The Chinese Government and energy authorities have issued a series of policies and measures,and in the past three years,China has had remarkable achievements in the adoption of renewable energy.The rate of idle wind capacity decreased from 17%in 2016 to 7%in 2018,and that of solar decreased from 10%in 2016 to 3%in 2018.
基金This study was supported by the National Key Research and Development Program of China(No.2018YFE0122200)National Natural Science Foundation of China(No.52077078)Fundamental Research Funds for the Central Universities(No.2020MS090).
文摘To address the significant lifecycle degradation and inadequate state of charge(SOC)balance of electric vehicles(EVs)when mitigating wind power fluctuations,a dynamic grouping control strategy is proposed for EVs based on an improved k-means algorithm.First,a swing door trending(SDT)algorithm based on compression result feedback was designed to extract the feature data points of wind power.The gating coefficient of the SDT was adjusted based on the compression ratio and deviation,enabling the acquisition of grid-connected wind power signals through linear interpolation.Second,a novel algorithm called IDOA-KM is proposed,which utilizes the Improved Dingo Optimization Algorithm(IDOA)to optimize the clustering centers of the k-means algorithm,aiming to address its dependence and sensitivity on the initial centers.The EVs were categorized into priority charging,standby,and priority discharging groups using the IDOA-KM.Finally,an two-layer power distribution scheme for EVs was devised.The upper layer determines the charging/discharging sequences of the three EV groups and their corresponding power signals.The lower layer allocates power signals to each EV based on the maximum charging/discharging power or SOC equalization principles.The simulation results demonstrate the effectiveness of the proposed control strategy in accurately tracking grid power signals,smoothing wind power fluctuations,mitigating EV degradation,and enhancing the SOC balance.
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
基金Project supported by the National Basic Research Program of China (Grant No. 2012CB215203)the Key Program of the National Natural Science Foundation of China (Grant No. 51036002)the Fundamental Research Funds for the Central Universities of China (Grant No. JB2012008)
文摘In this study, the consensus problem for a class of second-order multi-agent systems with nonuniform time delays is investigated. A linear consensus protocol is used to make all agents reach consensus and move with a constant velocity. By a frequency-domain analysis, a simplified sufficient condition is given to guarantee the consensus stability of the dynamic system. Finally, the effectiveness of the obtained theoretical results is illustrated through numerical simulations.
基金supported by the National Natural Science Foundation of China(Grant Nos.51627811,51725702)the Science and Technology Project of State Grid Corporation of Beijing(Grant No.SGBJDK00DWJS2100164).
文摘Owing to the expansion of the grid interconnection scale,the spatiotemporal distribution characteristics of the frequency response of power systems after the occurrence of disturbances have become increasingly important.These characteristics can provide effective support in coordinated security control.However,traditional model-based frequencyprediction methods cannot satisfactorily meet the requirements of online applications owing to the long calculation time and accurate power-system models.Therefore,this study presents a rolling frequency-prediction model based on a graph convolutional network(GCN)and a long short-term memory(LSTM)spatiotemporal network and named as STGCN-LSTM.In the proposed method,the measurement data from phasor measurement units after the occurrence of disturbances are used to construct the spatiotemporal input.An improved GCN embedded with topology information is used to extract the spatial features,while the LSTM network is used to extract the temporal features.The spatiotemporal-network-regression model is further trained,and asynchronous-frequency-sequence prediction is realized by utilizing the rolling update of measurement information.The proposed spatiotemporal-network-based prediction model can achieve accurate frequency prediction by considering the spatiotemporal distribution characteristics of the frequency response.The noise immunity and robustness of the proposed method are verified on the IEEE 39-bus and IEEE 118-bus systems.
基金supported by National Natural Science Foundation of China(Nos.92066108 and 51277061)。
文摘The initial shape of the secondary arc considerably influences its subsequent shape.To establish the model for the arcing time of the secondary arc and modify the single-phase reclosing sequence,theoretical and experimental analysis of the evolution process of the short-circuit arc to the secondary arc is critical.In this study,an improved charge simulation method was used to develop the internal-space electric-field model of the short-circuit arc.The intensity of the electric field was used as an independent variable to describe the initial shape of the secondary arc.A secondary arc evolution model was developed based on this model.Moreover,the accuracy of the model was evaluated by comparison with physical experimental results.When the secondary arc current increased,the arcing time and dispersion increased.There is an overall trend of increasing arc length with increasing arcing time.Nevertheless,there is a reduction in arc length during arc ignition due to short circuits between the arc columns.Furthermore,the arcing time decreased in the range of 0°-90°as the angle between the wind direction and the x-axis increased.This work investigated the method by which short-circuit arcs evolve into secondary arcs.The results can be used to develop the secondary arc evolution model and to provide both a technical and theoretical basis for secondary arc suppression.
基金supported by the Beijing Natural Science Foundation (4142049)863 project No. 2014AA01A701the Fundamental Research Funds for Central Universities of China No. 2015XS07
文摘In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. As the difference of hybrid energy source in stability and economy, thus, this paper focuses on the network with hybrid energy source, and design the utility of each user in the hybrid energy source system from the perspective of stability, economy and environment pollution. A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed. In addition, an iteration method is proposed which enables all players to reach the Stackelberg equilibrium(SE). Simulation results validate that players can reach the SE and the utilities of users and networks can be maximization, and the green energy can be efficiently used.
文摘This paper uses CT to gain the energy directly from the high-voltage transmission line, to address the problem of power supply for monitoring system in high voltage side of transmission line. The draw-out power coil can induce voltage from the transmission line, using single-chip microcomputer to analog and output PMW wave to control the charging module, provides a stable 3.4 V DC voltage to the load, and solve the problem of easy saturating of core. The power supply based on this kind of draw-out power coil has undergone the overall testing, and it is verified-showing that it can properly work in a non-saturated status within the current range of 50 - 1000 A, and provide a stable output. The equipment also design protection circuit to improve the reliability to avid the impacts of the impulse current or short-circuit current. It effectively solves the problem of power supply for On-line Monitoring System of Transmission.
基金financially supported by the National Social Science Fund of China(No.19ZDA081)Fundamental Research Funds for the Central Universities(No.2020MS067).
文摘In the future smart cities,parking lots(PLs)can accommodate hundreds of electric vehicles(EVs)at the same time.This trend creates an opportunity for PLs to serve as a potential flexibility resource,considering growing penetration of EVs and integration of distributed energy resources DER(such as photovoltaic and energy storages).Given this background,this paper proposes a comprehensive evaluation framework to investigate the potential role of DER-integrated PLs(DPL)with the capability of vehicle-to-grid(V2G)in improving the reliability of the distribution network.For this aim,first,an overview for the distribution system with DPLs is provided.Then,a generic model for the available generation capacity(AGC)of DPLs with consideration of EV scheduling strategy is developed.On the above basis,an iterative-based algorithm leveraging sequential Monte Carlo simulation is presented to quantify the contribution of DPLs to the reliability of the system.In order to verify the effectiveness of the proposed method,a series of numerical studies are carried out.The simulation results show that the integration of DPLs with the V2G capability could help to improve the reliability performance of distribution grid to a great extent and reduce the adverse impact incurred by EV accommodation,if utilized properly.
文摘Power transformer serves as one of the most widely used electrical equipments in power grid. During the operation, terrible losses are produced. With the development of loss reduction technology of power transformers, in order to save energy saving and reduce emissions, the old power transformer should be replaced. The paper summarizes the main method to reduce the losses of power transformers and brings up the improved Total Owning Cost (TOC) algorithm, which applies to 220 kV power transformers’ comprehensive benefit analysis. Using the improved Total Owning Cost (TOC) algorithm, based on today 220 kV energy-saving power transformer manufacturing level, the economic benefits of new energy-saving power transformer and the return period of investment are analyzed. Finally, combined with energy-saving effect, the appropriate replacement proposal of 220 kV power transformers has been given.
基金the Sino-US International Science and Technology Cooperation Project(No.2019YFE0114700)the National Natural Science Foundation of China(No.51877072)the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(No.LAPS20005)。
文摘This paper proposes a hybrid ocean energy sys-tem to form a virtual power plant(VPP)for participating in electricity markets in order to promote the renewable ocean energy utilization and accommodation.In the proposed system,solar thermal energy is integrated with the closed-cycle ocean thermal energy conversion(OTEC)to boost the temperature differences between the surface and deep seawater for efficiency and flexibility improvements,and the thermodynamic effects of seawater mass flow rates on the output of solar-boosted OTEC(SOTEC)are exploited for deploying SOTEC as a renewable dispatchable unit.An optimal tidal-storage operation model is also developed to make use of subsea pumped storage(SPS)with hydrostatic pressures at ocean depths for mitigating the intermittent tidal range energy in order to make the arbitrage in the electricity market.Furthermore,a two-stage coordinated scheduling strategy is presented to optimally control seawater mass flow rates of SOTEC and hydraulic reversible pump-turbines of SPS for enhancing the daily VPP profit.Comparative studies have been investigated to confirm the superiority of the developed methodology in various renewable ocean energy and electricity market price scenarios.
基金supported in part by the National Key R&D Program of China (No.2017YFE0109000)the project of China Datang Corporation Ltd
文摘With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.
基金supported partially by Natural Science Foundation of Beijing Municipality(L172036)Joint Funds of the Equipment Pre-Research and Ministry of Education(6141A020225)+3 种基金Par-Eu Scholars Program,Science and Technology Beijing 100 Leading Talent Training ProjectChina Postdoctoral Science Foundation(2018M631419)Fundamental Research Funds for Central Universities(2017ZZD02,2019QN001)NCEPU“Double First-Class”Graduate Talent Cultivation Program。
文摘Polyethylene oxide(PEO)-based electrolytes have obvious merits such as strong ability to dissolve salts(e.g.,LiTFSI)and high flexibility,but their applications in solid-state batteries is hindered by the low ion conductance and poor mechanical and thermal properties.Herein,poly(m-phenylene isophthalamide)(PMIA)is employed as a multifunctional additive to improve the overall properties of the PEO-based electrolytes.The hydrogen-bond interactions between PMIA and PEO/TFSI-can effectively prevent the PEO crystallization and meanwhile facilitate the LiTFSI dissociation,and thus greatly improve the ionic conductivity(two times that of the pristine electrolyte at room temperature).With the incorporation of the high-strength PMIA with tough amide-benzene backbones,the PMIA/PEO-LiTFSI composite polymer electrolyte(CPE)membranes also show much higher mechanical strength(2.96 MPa),thermostability(4190℃)and interfacial stability against Li dendrites(468 h at 0.10 mA cm-2)than the pristine electrolyte(0.32 MPa,364℃and short circuit after 246 h).Furthermore,the CPE-based LiFePO4/Li cells exhibit superior cycling stability(137 mAh g^-1 with 93%retention after 100 cycles at 0.5 C)and rate performance(123 mAh g^-1 at 1.0 C).This work provides a novel and effective CPE structure design strategy to achieve comprehensively-upgraded electrolytes for promising solid-state battery applications.
基金This work was supported by the National Natural Science Foundation of China(51877078 and 52061635102)the Beijing Nova Program(Z201100006820106).
文摘With the growth of intermittent renewable energy generation in power grids,there is an increasing demand for controllable resources to be deployed to guarantee power quality and frequency stability.The flexibility of demand response(DR)resources has become a valuable solution to this problem.However,existing research indicates that problems on flexibility prediction of DR resources have not been investigated.This study applied the temporal convolution network(TCN)-combined transformer,a deep learning technique to predict the aggregated flexibility of two types of DR resources,that is,electric vehicles(EVs)and domestic hot water system(DHWS).The prediction uses historical power consumption data of these DR resources and DR signals(DSs)to facilitate prediction.The prediction can generate the size and maintenance time of the aggregated flexibility.The accuracy of the flexibility prediction results was verified through simulations of case studies.The simulation results show that under different maintenance times,the size of the flexibility changed.The proposed DR resource flexibility prediction method demonstrates its application in unlocking the demand-side flexibility to provide a reserve to grids.
基金Project supported by the National Natural Science Foundation of China(Grant No.51307055)in part by the State Grid Corporation of China(Grant No.No.SGRI-WD-71-12-009)
文摘According to the reciprocity principle, we propose an efficient model to compute the shielding effectiveness of a rectangular cavity with apertures covered by conductive sheet against an external incident electromagnetic wave. This problem is converted into another problem of solving the electromagnetic field leakage from the cavity when the cavity is excited by an electric dipole placed within it. By the combination of the unperturbed cavity field and the transfer impedance of the sheet, the tangential electric field distribution on the outer surface of the sheet is obtained. Then, the field distribution is regarded as an equivalent surface magnetic current source responsible for the leakage field. The validation of this model is verified by a comparison with the circuital model and the full-wave simulations. This time-saving model can deal with arbitrary aperture shape, various wave propagation and polarization directions, and the near-field effect.
文摘Compressed air pumped hydro energy storage equipment combines compressed air energy storage technology and pumped storage technology. The water is pumped to a vessel to compress air for energy storage, and the compressed air expanses pushing water to drive the hydro turbine for power generation. The novel storage equipment saves natural gas resources, reduces carbon emission, and improves the controllability and reliability. The principle of compressed air pumped hydro energy storage is introduced and its mathematical model is built. The storage and generation process of the novel equipment is analyzed using the model. The calculation formula of the storage power is deduced in theory in different situations of isothermal and adiabatic compression. The optimal storage scheme is given when the capacity and withstand pressure of the vessel is definitive, and the max available capacity and the equipment utilization efficiency evaluation of the scheme is given.
基金supported by the Fundamental Research Funds For the Central Universities(No.2017MS093)
文摘The large-scale utilization and sharing of renewable energy in interconnected systems is crucial for realizing"instrumented,interconnected,and intelligent"power grids.The traditional optimal dispatch method can not coordinate the economic benefits of all the stakeholders from multiple regions of the transmission network,comprehensively.Hence,this study proposes a large-scale wind-power coordinated consumption strategy based on the Nash-Q method and establishes an economic dispatch model for interconnected systems considering the uncertainty of wind power,with optimal windpower consumption as the objective for redistributing the shared benefits between regions.Initially,based on the equivalent cost of the interests of stakeholders from different regions,the state decision models are respectively constructed,and the noncooperative game Nash equilibrium model is established.The Q-learning algorithm is then introduced for high-dimension decision variables in the game model,and the dispatch solution methods for interconnected systems are presented,integrating the noncooperative game Nash equilibrium and Q-learning algorithm.Finally,the proposed method is verified through the modified IEEE 39-bus interconnection system,and it is established that this method achieves reasonable distribution of interests between regions and promotes large-scale consumption of wind power.
