This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor...This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.展开更多
The increasing flexibility of active distribution systems(ADSs)coupled with the high penetration of renewable distributed generators(RDGs)leads to the increase of the complexity.It is of practical significance to achi...The increasing flexibility of active distribution systems(ADSs)coupled with the high penetration of renewable distributed generators(RDGs)leads to the increase of the complexity.It is of practical significance to achieve the largest amount of RDG penetration in ADSs and maintain the optimal operation.This study establishes an alternating current(AC)/direct current(DC)hybrid ADS model that considers the dynamic thermal rating,soft open point,and distribution network reconfiguration(DNR).Moreover,it transforms the optimal dispatching into a second-order cone programming problem.Considering the different control time scales of dispatchable resources,the following two-stage dispatching framework is proposed.d dispatch uses hourly input data with the goal(1)The day-ahea of minimizing the grid loss and RDG dropout.It obtains the optimal 24-hour schedule to determine the dispatching plans for DNR and the energy storage system.(2)The intraday dispatch uses 15-min input data for 1-hour rolling-plan dispatch but only executes the first 15 min of dispatching.To eliminate error between the actual operation and dispatching plan,the first 15 min is divided into three 5-min step-by-step executions.The goal of each step is to trace the tie-line power of the intraday rolling-plan dispatch to the greatest extent at the minimum cost.The measured data are used as feedback input for the rolling-plan dispatch after each step is executed.A case study shows that the comprehensive cooperative ADS model can release the line capacity,reduce losses,and improve the penetration rate of RDGs.Further,the two-stage dispatching framework can handle source-load fluctuations and enhance system stability.展开更多
With the increasing penetration of renewable energy,power grid operators are observing both fast and large fluctuations in power and voltage profiles on a daily basis.Fast and accurate control actions derived in real ...With the increasing penetration of renewable energy,power grid operators are observing both fast and large fluctuations in power and voltage profiles on a daily basis.Fast and accurate control actions derived in real time are vital to ensure system security and economics.To this end,solving alternating current(AC)optimal power flow(OPF)with operational constraints remains an important yet challenging optimization problem for secure and economic operation of the power grid.This paper adopts a novel method to derive fast OPF solutions using state-of-the-art deep reinforcement learning(DRL)algorithm,which can greatly assist power grid operators in making rapid and effective decisions.The presented method adopts imitation learning to generate initial weights for the neural network(NN),and a proximal policy optimization algorithm to train and test stable and robust artificial intelligence(AI)agents.Training and testing procedures are conducted on the IEEE 14-bus and the Illinois 200-bus systems.The results show the effectiveness of the method with significant potential for assisting power grid operators in real-time operations.展开更多
随着数据中心的快速发展,不间断电源(Uninterruptible Power Supply,UPS)交流电源作为保障数据中心稳定供电的关键设备,其接入方案的选择变得至关重要。探讨了数据中心UPS交流电源的接入方案,重点考虑了数据中心运行环境要求和方案设计...随着数据中心的快速发展,不间断电源(Uninterruptible Power Supply,UPS)交流电源作为保障数据中心稳定供电的关键设备,其接入方案的选择变得至关重要。探讨了数据中心UPS交流电源的接入方案,重点考虑了数据中心运行环境要求和方案设计的因素。首先,介绍了UPS交流电源的概述和特性;其次,分析了数据中心对UPS交流电源的要求,在接入方案的考虑因素中,着重考虑了数据中心的运行环境要求以及方案设计中的UPS电源容量选择计算和蓄电池配置计算;最后,提出了合理的方案电气原理。通过研究和分析,可以为数据中心UPS交流电源的接入提供有益的参考和指导,确保数据中心的稳定供电和运行安全。展开更多
In view of the imbalanced distribution of power load and resources, including the status of “electric shortage” in some cities in our country, the article discusses the long-distance transmission technology. It main...In view of the imbalanced distribution of power load and resources, including the status of “electric shortage” in some cities in our country, the article discusses the long-distance transmission technology. It mainly analyzed two ways of the long-distance transmission: UHV AC transmission and UHV DC transmission. The fractional frequency transmission technology and half wavelength AC transmission technology of AC transmission are introduced. Some key technologies of long-distance transmission are described. It has a guess for long-distance transmission future direction.展开更多
Modern power systems are experiencing larger fluctuations and more uncertainties caused by increased penetration of renewable energy sources(RESs) and power electronics equipment. Therefore, fast and accurate correcti...Modern power systems are experiencing larger fluctuations and more uncertainties caused by increased penetration of renewable energy sources(RESs) and power electronics equipment. Therefore, fast and accurate corrective control actions in real time are needed to ensure the system security and economics. This paper presents a novel method to derive realtime alternating current(AC) optimal power flow(OPF) solutions considering the uncertainties including varying renewable energy and topology changes by using state-of-the-art deep reinforcement learning(DRL) algorithm, which can effectively assist grid operators in making rapid and effective real-time decisions. The presented DRL-based approach first adopts a supervised-learning method from deep learning to generate good initial weights for neural networks, and then the proximal policy optimization(PPO) algorithm is applied to train and test the artificial intelligence(AI) agents for stable and robust performance. An ancillary classifier is designed to identify the feasibility of the AC OPF problem. Case studies conducted on the Illinois 200-bus system with wind generation variation and N-1 topology changes validate the effectiveness of the proposed method and demonstrate its great potential in promoting sustainable energy integration into the power system.展开更多
Triggered vacuum switches(TVSs)have fast growing applications in the field of power system and pulse power.The relation between triggering parameters of triggering system,such as triggering voltage and triggering powe...Triggered vacuum switches(TVSs)have fast growing applications in the field of power system and pulse power.The relation between triggering parameters of triggering system,such as triggering voltage and triggering power,between the triggering time delay and its scatter of TVS had been obtained through series of experiments.The result can be adopted as the steering for high-power controller design and application of TVS.A steepened high-voltage triggering pulse is introduced in the main high-voltage generating circuit.As a result,the triggering time delay and its scatter can be decreased remarkably.Synchronous switch technology is imported to control the triggering phase at the crest of applied voltage on TVS.The Triggering characteristic of TVS under alternating current(AC)and direct current(DC)load has been investigated emphatically.Given the identical triggering parameter of triggering system,DC condition is prior to AC on the triggering probability and stability markedly.Such conclusion can be drawn,for AC condition,TVS would require much for the triggering system.展开更多
基金supported by National Natural Science Foundation of China(Nos.61104072 and 11271309)
文摘This paper presents a backstepping control method for speed sensorless permanent magnet synchronous motor based on slide model observer. First, a comprehensive dynamical model of the permanent magnet synchronous motor(PMSM) in d-q frame and its space-state equation are established. The slide model control method is used to estimate the electromotive force of PMSM under static frame, while the position of rotor and its actual speed are estimated by using phase loop lock(PLL) method. Next,using Lyapunov stability theorem, the asymptotical stability condition of the slide model observer is presented. Furthermore, based on the backstepping control theory, the PMSM rotor speed and current tracking backstepping controllers are designed, because such controllers display excellent speed tracking and anti-disturbance performance. Finally, Matlab simulation results show that the slide model observer can not only estimate the rotor position and speed of the PMSM accurately, but also ensure the asymptotical stability of the system and effective adjustment of rotor speed and current.
基金supported by Universiti Sains Malaysia through Research University Team(RUTeam)Grant Scheme(No.1001/PELECT/8580011)。
文摘The increasing flexibility of active distribution systems(ADSs)coupled with the high penetration of renewable distributed generators(RDGs)leads to the increase of the complexity.It is of practical significance to achieve the largest amount of RDG penetration in ADSs and maintain the optimal operation.This study establishes an alternating current(AC)/direct current(DC)hybrid ADS model that considers the dynamic thermal rating,soft open point,and distribution network reconfiguration(DNR).Moreover,it transforms the optimal dispatching into a second-order cone programming problem.Considering the different control time scales of dispatchable resources,the following two-stage dispatching framework is proposed.d dispatch uses hourly input data with the goal(1)The day-ahea of minimizing the grid loss and RDG dropout.It obtains the optimal 24-hour schedule to determine the dispatching plans for DNR and the energy storage system.(2)The intraday dispatch uses 15-min input data for 1-hour rolling-plan dispatch but only executes the first 15 min of dispatching.To eliminate error between the actual operation and dispatching plan,the first 15 min is divided into three 5-min step-by-step executions.The goal of each step is to trace the tie-line power of the intraday rolling-plan dispatch to the greatest extent at the minimum cost.The measured data are used as feedback input for the rolling-plan dispatch after each step is executed.A case study shows that the comprehensive cooperative ADS model can release the line capacity,reduce losses,and improve the penetration rate of RDGs.Further,the two-stage dispatching framework can handle source-load fluctuations and enhance system stability.
基金supported by State Grid Science and Technology Program“Research on Real-time Autonomous Control Strategies for Power Grid Based on AI Technologies”(No.5700-201958523A-0-0-00)
文摘With the increasing penetration of renewable energy,power grid operators are observing both fast and large fluctuations in power and voltage profiles on a daily basis.Fast and accurate control actions derived in real time are vital to ensure system security and economics.To this end,solving alternating current(AC)optimal power flow(OPF)with operational constraints remains an important yet challenging optimization problem for secure and economic operation of the power grid.This paper adopts a novel method to derive fast OPF solutions using state-of-the-art deep reinforcement learning(DRL)algorithm,which can greatly assist power grid operators in making rapid and effective decisions.The presented method adopts imitation learning to generate initial weights for the neural network(NN),and a proximal policy optimization algorithm to train and test stable and robust artificial intelligence(AI)agents.Training and testing procedures are conducted on the IEEE 14-bus and the Illinois 200-bus systems.The results show the effectiveness of the method with significant potential for assisting power grid operators in real-time operations.
文摘随着数据中心的快速发展,不间断电源(Uninterruptible Power Supply,UPS)交流电源作为保障数据中心稳定供电的关键设备,其接入方案的选择变得至关重要。探讨了数据中心UPS交流电源的接入方案,重点考虑了数据中心运行环境要求和方案设计的因素。首先,介绍了UPS交流电源的概述和特性;其次,分析了数据中心对UPS交流电源的要求,在接入方案的考虑因素中,着重考虑了数据中心的运行环境要求以及方案设计中的UPS电源容量选择计算和蓄电池配置计算;最后,提出了合理的方案电气原理。通过研究和分析,可以为数据中心UPS交流电源的接入提供有益的参考和指导,确保数据中心的稳定供电和运行安全。
文摘In view of the imbalanced distribution of power load and resources, including the status of “electric shortage” in some cities in our country, the article discusses the long-distance transmission technology. It mainly analyzed two ways of the long-distance transmission: UHV AC transmission and UHV DC transmission. The fractional frequency transmission technology and half wavelength AC transmission technology of AC transmission are introduced. Some key technologies of long-distance transmission are described. It has a guess for long-distance transmission future direction.
文摘Modern power systems are experiencing larger fluctuations and more uncertainties caused by increased penetration of renewable energy sources(RESs) and power electronics equipment. Therefore, fast and accurate corrective control actions in real time are needed to ensure the system security and economics. This paper presents a novel method to derive realtime alternating current(AC) optimal power flow(OPF) solutions considering the uncertainties including varying renewable energy and topology changes by using state-of-the-art deep reinforcement learning(DRL) algorithm, which can effectively assist grid operators in making rapid and effective real-time decisions. The presented DRL-based approach first adopts a supervised-learning method from deep learning to generate good initial weights for neural networks, and then the proximal policy optimization(PPO) algorithm is applied to train and test the artificial intelligence(AI) agents for stable and robust performance. An ancillary classifier is designed to identify the feasibility of the AC OPF problem. Case studies conducted on the Illinois 200-bus system with wind generation variation and N-1 topology changes validate the effectiveness of the proposed method and demonstrate its great potential in promoting sustainable energy integration into the power system.
基金This work was carried out under the support of Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology(No.0842006_025_Z).
文摘Triggered vacuum switches(TVSs)have fast growing applications in the field of power system and pulse power.The relation between triggering parameters of triggering system,such as triggering voltage and triggering power,between the triggering time delay and its scatter of TVS had been obtained through series of experiments.The result can be adopted as the steering for high-power controller design and application of TVS.A steepened high-voltage triggering pulse is introduced in the main high-voltage generating circuit.As a result,the triggering time delay and its scatter can be decreased remarkably.Synchronous switch technology is imported to control the triggering phase at the crest of applied voltage on TVS.The Triggering characteristic of TVS under alternating current(AC)and direct current(DC)load has been investigated emphatically.Given the identical triggering parameter of triggering system,DC condition is prior to AC on the triggering probability and stability markedly.Such conclusion can be drawn,for AC condition,TVS would require much for the triggering system.
