Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified ...Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.展开更多
This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines...This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.展开更多
At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under...At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.展开更多
The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of th...The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.展开更多
Carrying out green energy transformation,implementing clean energy power replacement and supply,and developing a new power system are some primary driving forces needed to fulfill China’s carbon-peak and carbon-neutr...Carrying out green energy transformation,implementing clean energy power replacement and supply,and developing a new power system are some primary driving forces needed to fulfill China’s carbon-peak and carbon-neutral strategic goals.The construction of new power systems in China’s provinces and cities is developing rapidly,and the lack of a typical model promotes the application.The new power system path design should be based on the actual development of the power grid in different regions,energy use characteristics,and other actual needs to carry out the differentiated path design.In this context,this study analyzes the characteristics of the new domestic power system based on the policy background of the new domestic power system,constructs a new model for power system development stage identification,and proposes the overall design of the new power system development path from the power supply,transmission and distribution,and load sides.It also uses the Hebei South Network as an example to explore the development stage of the Hebei South Grid based on actual development needs.Finally,this study designs a novel power system development path for the entire supply and demand chain for the Hebei South Grid to propose ideas for constructing a new power system in China and to help green energy transformation.展开更多
Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effe...Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence(AI)algorithms,in which the different AI algorithms for OCR analysis are classified and reviewed.Firstly,the mechanisms and characteristics of artificial neural network-based OCR are summarized.Secondly,this paper explores machine learning-based OCR,and draws the conclusion that the algorithms available for this form of OCR are still in their infancy,with low generalization and fixed recognition errors,albeit with better recognition effect and higher recognition accuracy.Finally,this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms.This paper concludes that OCR requires algorithms with higher recognition accuracy.展开更多
The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,th...The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.展开更多
Historical materialism provides the ontology basis to understand the contemporary ecological justice problem,which is the perspective for analyzing ecological interests from the nature,structure,and transition of the ...Historical materialism provides the ontology basis to understand the contemporary ecological justice problem,which is the perspective for analyzing ecological interests from the nature,structure,and transition of the social power system.The transcendence of Marx’s thoughts on western mainstream environmental justice theory lies that it does not based on the“speculative ontology”of metaphysics,but on the basis of“realistic ontology”of social power system.展开更多
The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of secur...The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.展开更多
Dear Editor,Machine learning(ML) approaches have been widely employed to enable real-time ML-based stability assessment(MLSA) of largescale automated electricity grids. However, the vulnerability of MLSA to malicious ...Dear Editor,Machine learning(ML) approaches have been widely employed to enable real-time ML-based stability assessment(MLSA) of largescale automated electricity grids. However, the vulnerability of MLSA to malicious cyber-attacks may lead to wrong decisions in operating the physical grid if its resilience properties are not well understood before deployment. Unlike adversarial ML in prior domains such as image processing, specific constraints of power systems that the attacker must obey in constructing adversarial samples require new research on MLSA vulnerability analysis for power systems.展开更多
Dear Editor,To tackle the global challenges of climate change and energy secu-r ity, building low carbon energy systems has become a research hotspot. Cyber-physical power systems(CPPSs) is an important infrastructure...Dear Editor,To tackle the global challenges of climate change and energy secu-r ity, building low carbon energy systems has become a research hotspot. Cyber-physical power systems(CPPSs) is an important infrastructure to link both energy and transport systems, two major sectors that are difficult to decarbonize, and it is necessary to establish CPPSs model to consider the integration of both renewable energy and electric vehicle(EV).展开更多
This paper proposes the concept and framework of smart operating system based on the artificial intelligence(AI)techniques. The demands and the potential applications of AI technologies in power system control centers...This paper proposes the concept and framework of smart operating system based on the artificial intelligence(AI)techniques. The demands and the potential applications of AI technologies in power system control centers is discussed in the beginning of the paper. The discussion is based on the results of a field study in the Tianjin Power System Control Center in China. According to the study, one problem in power systems is that the power system analysis system in the control center is not fast and powerful enough to help the operators in time to deal with the incidents in the power system. Another issue in current power system control center is that the operation tickets are compiled manually by the operators, so that it is less efficient and human errors cannot be avoided. Based on these problems, a framework of the smart operating robot is proposed in this paper, which includes an intelligent power system analysis system and a smart operation ticket compiling system to solve the two problems in power system control centers. The proposed framework is mainly based on the AI techniques, especially the neural network with deep learning, since it is faster and more capable of dealing with the highly nonlinear and complex power system.展开更多
One method for eliminating oscillations in power systems is using stabilizers.By applying an appropriate control signal in the excitation system of a generator,a power system stabilizer improves the dynamic stability ...One method for eliminating oscillations in power systems is using stabilizers.By applying an appropriate control signal in the excitation system of a generator,a power system stabilizer improves the dynamic stability of power systems.However,the issue that is of high importance is the correct design of these stabilizers.These stabilizers must be designed to have proper performance when operating conditions change.When designed incorrectly,not only they do not improve the stability margin,but also increase the oscillations.In this paper,the robust design of power system stabilizers on a four-machine power system has been performed.For this purpose,the differential evolution algorithm has been used.The studies have been repeated as three scenarios by producing different loading conditions for the generators.The performances of the conventional stabilizer and the optimized one have been compared.Simulation results indicate that the designed robust stabilizer outperforms other stabilizers in different conditions and has damped the interarea and intra-area oscillation modes in the shortest time with minimum amplitude.展开更多
In themarine electric power system,the marine generators will be disturbed by the large change of loads or the fault of the power system.The marine generators usually installed power system stabilizers to damp power s...In themarine electric power system,the marine generators will be disturbed by the large change of loads or the fault of the power system.The marine generators usually installed power system stabilizers to damp power system oscillations through the excitation control.This paper proposes a novel method to obtain optimal parameter values for Power System Stabilizer(PSS)to suppress low-frequency oscillations in the marine electric power system.In this paper,a newly developed immune clone selection algorithm was improved from the three aspects of the adaptive incentive degree,vaccination,and adaptive mutation strategies.Firstly,the typical PSS implementation type of leader-lag structure was adopted and the objective function was set in the optimization process.The performance of PSS tuned by improved immune clone selection algorithm was compared with PSS tuned by basic immune clone selection algorithm(ICSA)under various operating conditions and disturbances.Then,an improved immune clone selection algorithm(IICSA)optimization technique was implemented on two test systems for test purposes.Based on the simulations,it is found that an improved immune clone selection algorithm demonstrates superiority over the basic immune clone selection algorithm in getting a smaller number of iterations and fast convergence rates to achieve the optimal parameters of the power system stabilizers.Moreover,the proposed approach improves the stability and dynamic performance under various loads conditions and disturbances of the marine electric power system.展开更多
This paper focuses on the small signal stability analysis of Doubly-Fed Induction Generator (DFIG) fed wind power system under three modes of operation. The system stability is affected by the influence of electromech...This paper focuses on the small signal stability analysis of Doubly-Fed Induction Generator (DFIG) fed wind power system under three modes of operation. The system stability is affected by the influence of electromechanical oscillations, which can be damped using Power System Stabilizer (PSS). A detailed modeling of DFIG fed wind system including controller has been carried out. The damping controller is designed using fuzzy logic to damp the oscillatory modes for stability. The robust performance of the system with controllers has been evaluated using eigen value analysis and time domain simulations under various disturbances and wind speeds. The effectiveness of the proposed fuzzy based PSS is compared with the performance of conventional PSS implemented in the wind system.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
This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turb...This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.展开更多
Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid i...Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality.展开更多
This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of re...This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.展开更多
基金supported in part by the Scientific Foundation for Outstanding Young Scientists of Sichuan under Grant No.2021JDJQ0032in part by the National Natural Science Foundation of China under Grant No.52107128in part by the Natural Science Foundation of Sichuan Province under Grant No.2022NSFSC0436.
文摘Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.
基金supported in part by the National Natural Science Foundation of China(61933007, U21A2019, 62273005, 62273088, 62303301)the Program of Shanghai Academic/Technology Research Leader of China (20XD1420100)+2 种基金the Hainan Province Science and Technology Special Fund of China(ZDYF2022SHFZ105)the Natural Science Foundation of Anhui Province of China (2108085MA07)the Alexander von Humboldt Foundation of Germany。
文摘This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.
基金This researchwas supported by the National Natural Science Foundation of China(Nos.51767017 and 51867015)the Basic Research and Innovation Group Project of Gansu(No.18JR3RA133)the Natural Science Foundation of Gansu(No.21JR7RA258).
文摘At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.
文摘The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.
基金funded by the State Grid Hebei Electric Power Co.,Ltd projectthe National Natural Science Foundation of China’s major project,“Research on the Construction of China’s Economic Transformation Mode for Carbon Neutrality(72140001)This study is titled“Research on Novel Power System Development Path”。
文摘Carrying out green energy transformation,implementing clean energy power replacement and supply,and developing a new power system are some primary driving forces needed to fulfill China’s carbon-peak and carbon-neutral strategic goals.The construction of new power systems in China’s provinces and cities is developing rapidly,and the lack of a typical model promotes the application.The new power system path design should be based on the actual development of the power grid in different regions,energy use characteristics,and other actual needs to carry out the differentiated path design.In this context,this study analyzes the characteristics of the new domestic power system based on the policy background of the new domestic power system,constructs a new model for power system development stage identification,and proposes the overall design of the new power system development path from the power supply,transmission and distribution,and load sides.It also uses the Hebei South Network as an example to explore the development stage of the Hebei South Grid based on actual development needs.Finally,this study designs a novel power system development path for the entire supply and demand chain for the Hebei South Grid to propose ideas for constructing a new power system in China and to help green energy transformation.
基金supported by science and technology projects of Gansu State Grid Corporation of China(52272220002U).
文摘Optical Character Recognition(OCR)refers to a technology that uses image processing technology and character recognition algorithms to identify characters on an image.This paper is a deep study on the recognition effect of OCR based on Artificial Intelligence(AI)algorithms,in which the different AI algorithms for OCR analysis are classified and reviewed.Firstly,the mechanisms and characteristics of artificial neural network-based OCR are summarized.Secondly,this paper explores machine learning-based OCR,and draws the conclusion that the algorithms available for this form of OCR are still in their infancy,with low generalization and fixed recognition errors,albeit with better recognition effect and higher recognition accuracy.Finally,this paper explores several of the latest algorithms such as deep learning and pattern recognition algorithms.This paper concludes that OCR requires algorithms with higher recognition accuracy.
基金supported in part by the Natural Science Foundation of Shandong Province(ZR2021QE289)in part by State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22201).
文摘The optimal allocation of integrated energy systemcapacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy,which has attracted many attentions.However,the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters.To solve the above problem,the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms.Firstly,an integrated energy system consisting of the photovoltaic,wind turbine,electrolysis cell,hydrogen storage tank,and energy storage is established.Meanwhile,the minimum economic cost,the maximum wind and PV power consumption rate,and the minimum load shortage rate are considered to be the objective functions.Then,a hybrid method combined the particle swarm combined with non-dominated sorting genetic algorithms-II is proposed to solve the optimal allocation problem.According to the optimal result,the economic cost is 6.3 million RMB,and the load shortage rate is 9.83%.Finally,four comparative experiments are conducted to verify the superiority-seeking ability of the proposed method.The comparative results indicate that the proposed method possesses a strongermerit-seeking ability,resulting in a solution satisfaction rate of 87.37%,which is higher than that of the unimproved non-dominated sorting genetic algorithms-II.
文摘Historical materialism provides the ontology basis to understand the contemporary ecological justice problem,which is the perspective for analyzing ecological interests from the nature,structure,and transition of the social power system.The transcendence of Marx’s thoughts on western mainstream environmental justice theory lies that it does not based on the“speculative ontology”of metaphysics,but on the basis of“realistic ontology”of social power system.
基金supported in part by Science and Technology Projects of Electric Power Research Institute of State Grid Jiangsu Electric Power Co.,Ltd.(J2021171).
文摘The access of unified power flow controllers(UPFC)has changed the structure and operation mode of power grids all across the world,and it has brought severe challenges to the traditional real-time calculation of security correction based on traditionalmodels.Considering the limitation of computational efficiency regarding complex,physical models,a data-driven power system security correction method with UPFC is,in this paper,proposed.Based on the complex mapping relationship between the operation state data and the security correction strategy,a two-stage deep neural network(DNN)learning framework is proposed,which divides the offline training task of security correction into two stages:in the first stage,the stacked auto-encoder(SAE)classification model is established,and the node correction state(0/1)output based on the fault information;in the second stage,the DNN learningmodel is established,and the correction amount of each action node is obtained based on the action nodes output in the previous stage.In this paper,the UPFC demonstration project of NanjingWest Ring Network is taken as a case study to validate the proposed method.The results show that the proposed method can fully meet the real-time security correction time requirements of power grids,and avoid the inherent defects of the traditional model method without an iterative solution and can also provide reasonable security correction strategies for N-1 and N-2 faults.
基金supported in part by the Guizhou Provincial Science and Technology Projects(ZK[2022]149)the Special Foundation of Guizhou University(GZU)([2021]47)+2 种基金the Guizhou Provincial Research Project for Universities([2022]104)the GZU cultivation project of the National Natural Science Foundation of China([2020]80)Shanghai Engineering Research Center of Big Data Management。
文摘Dear Editor,Machine learning(ML) approaches have been widely employed to enable real-time ML-based stability assessment(MLSA) of largescale automated electricity grids. However, the vulnerability of MLSA to malicious cyber-attacks may lead to wrong decisions in operating the physical grid if its resilience properties are not well understood before deployment. Unlike adversarial ML in prior domains such as image processing, specific constraints of power systems that the attacker must obey in constructing adversarial samples require new research on MLSA vulnerability analysis for power systems.
基金supported by Project of Science and Technology Commission of Shanghai Municipality(19510750300,21190780300,20JC1414000)111 Project(D18003)the National Science Foundation of China(92067106)。
文摘Dear Editor,To tackle the global challenges of climate change and energy secu-r ity, building low carbon energy systems has become a research hotspot. Cyber-physical power systems(CPPSs) is an important infrastructure to link both energy and transport systems, two major sectors that are difficult to decarbonize, and it is necessary to establish CPPSs model to consider the integration of both renewable energy and electric vehicle(EV).
基金supported by State Grid Corporation of China(SGCC)Science and Technolgy Project(SGTJDK00DWJS1700060)
文摘This paper proposes the concept and framework of smart operating system based on the artificial intelligence(AI)techniques. The demands and the potential applications of AI technologies in power system control centers is discussed in the beginning of the paper. The discussion is based on the results of a field study in the Tianjin Power System Control Center in China. According to the study, one problem in power systems is that the power system analysis system in the control center is not fast and powerful enough to help the operators in time to deal with the incidents in the power system. Another issue in current power system control center is that the operation tickets are compiled manually by the operators, so that it is less efficient and human errors cannot be avoided. Based on these problems, a framework of the smart operating robot is proposed in this paper, which includes an intelligent power system analysis system and a smart operation ticket compiling system to solve the two problems in power system control centers. The proposed framework is mainly based on the AI techniques, especially the neural network with deep learning, since it is faster and more capable of dealing with the highly nonlinear and complex power system.
文摘One method for eliminating oscillations in power systems is using stabilizers.By applying an appropriate control signal in the excitation system of a generator,a power system stabilizer improves the dynamic stability of power systems.However,the issue that is of high importance is the correct design of these stabilizers.These stabilizers must be designed to have proper performance when operating conditions change.When designed incorrectly,not only they do not improve the stability margin,but also increase the oscillations.In this paper,the robust design of power system stabilizers on a four-machine power system has been performed.For this purpose,the differential evolution algorithm has been used.The studies have been repeated as three scenarios by producing different loading conditions for the generators.The performances of the conventional stabilizer and the optimized one have been compared.Simulation results indicate that the designed robust stabilizer outperforms other stabilizers in different conditions and has damped the interarea and intra-area oscillation modes in the shortest time with minimum amplitude.
基金This work is supported by Shanghai Science and Technology Planning Project(Project No.20040501200).
文摘In themarine electric power system,the marine generators will be disturbed by the large change of loads or the fault of the power system.The marine generators usually installed power system stabilizers to damp power system oscillations through the excitation control.This paper proposes a novel method to obtain optimal parameter values for Power System Stabilizer(PSS)to suppress low-frequency oscillations in the marine electric power system.In this paper,a newly developed immune clone selection algorithm was improved from the three aspects of the adaptive incentive degree,vaccination,and adaptive mutation strategies.Firstly,the typical PSS implementation type of leader-lag structure was adopted and the objective function was set in the optimization process.The performance of PSS tuned by improved immune clone selection algorithm was compared with PSS tuned by basic immune clone selection algorithm(ICSA)under various operating conditions and disturbances.Then,an improved immune clone selection algorithm(IICSA)optimization technique was implemented on two test systems for test purposes.Based on the simulations,it is found that an improved immune clone selection algorithm demonstrates superiority over the basic immune clone selection algorithm in getting a smaller number of iterations and fast convergence rates to achieve the optimal parameters of the power system stabilizers.Moreover,the proposed approach improves the stability and dynamic performance under various loads conditions and disturbances of the marine electric power system.
文摘This paper focuses on the small signal stability analysis of Doubly-Fed Induction Generator (DFIG) fed wind power system under three modes of operation. The system stability is affected by the influence of electromechanical oscillations, which can be damped using Power System Stabilizer (PSS). A detailed modeling of DFIG fed wind system including controller has been carried out. The damping controller is designed using fuzzy logic to damp the oscillatory modes for stability. The robust performance of the system with controllers has been evaluated using eigen value analysis and time domain simulations under various disturbances and wind speeds. The effectiveness of the proposed fuzzy based PSS is compared with the performance of conventional PSS implemented in the wind system.
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.
基金supported by National Natural Science Foundation of China(60904008,61273336)the Fundamental Research Funds for the Central Universities(2018MS025)the National Basic Research Program of China(973 Program)(B1320133020)
文摘This paper addresses a terminal sliding mode control(T-SMC) method for load frequency control(LFC) in renewable power systems with generation rate constraints(GRC).A two-area interconnected power system with wind turbines is taken into account for simulation studies. The terminal sliding mode controllers are assigned in each area to achieve the LFC goal. The increasing complexity of the nonlinear power system aggravates the effects of system uncertainties. Radial basis function neural networks(RBF NNs) are designed to approximate the entire uncertainties. The terminal sliding mode controllers and the RBF NNs work in parallel to solve the LFC problem for the renewable power system. Some simulation results illustrate the feasibility and validity of the presented scheme.
基金support by National Natural Science Foundation of China(61202354,51507084)Nanjing University of Post and Telecommunications Science Foundation(NUPTSF)(NT214203)
文摘Risk assessment is essential for the safe and reliable operation of cyber physical power system. Traditional security risk assessment methods do not take integration of cyber system and physical system of power grid into account. In order to solve this problem, security risk assessment algorithm of cyber physical power system based on rough set and gene expression programming is proposed. Firstly, fast attribution reduction based on binary search algorithm is presented. Secondly, security risk assessment function for cyber physical power system is mined based on gene expression programming. Lastly, security risk levels of cyber physical power system are predicted and analyzed by the above function model. Experimental results show that security risk assessment function model based on the proposed algorithm has high efficiency of function mining, accuracy of security risk level prediction and strong practicality.
基金supported in part by the National Natural Science Foundation of China(61673161)the Natural Science Foundation of Jiangsu Province of China(BK20161510)+2 种基金the Fundamental Research Funds for the Central Universities of China(2017B13914)the 111 Project(B14022)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.
