A power management unit （PMU） chip supplying dual panel supply voltage, which has a low electro-magnetic interference （EMI） characteristic and is favorable for miniaturization, is designed. A two-phase charge pump...A power management unit （PMU） chip supplying dual panel supply voltage, which has a low electro-magnetic interference （EMI） characteristic and is favorable for miniaturization, is designed. A two-phase charge pump circuit using external pumping capacitor increases its pumping current and works out the charge-loss problem by using bulk-potential biasing circuit. A low-power start-up circuit is also proposed to reduce the power consumption of the band-gap reference voltage generator. And the ring oscillator used in the ELVSS power circuit is designed with logic devices by supplying the logic power supply to reduce the layout area. The PMU chip is designed with MagnaChip＇s 0.25 μ high-voltage process. The driving currents of ELVDD and ELVSS are more than 50 mA when a SPICE simulation is done.展开更多
To solve the problem of dynamic power resource allocation for cooperative penetration combat,the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a comm...To solve the problem of dynamic power resource allocation for cooperative penetration combat,the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a common payoff function named collaborative detection probability of netted radar countermeasures.Comparing with traditional optimization methods,an obvious advantage of game-based model is an adequate consideration of the opposite potential strategy.This model guarantees a more effective allocation of the both sides′power resource and a higher combat efficiency during a combat.Furthermore,an analysis of the complexity of the proposed model is given and a hierarchical processing method is presented to simplify the calculating process.Simulation results show the validity of the proposed scheme.展开更多
This paper presents an integrated and detailed procedure to improve tile power management feature implemented in the integrated starter-generator （ISG） parallel hybrid electric vehicle. First, the configuration of t...This paper presents an integrated and detailed procedure to improve tile power management feature implemented in the integrated starter-generator （ISG） parallel hybrid electric vehicle. First, the configuration of the single-shaft ISG hybrid vehicle model established in MATLAB-Simulink environment is given. The vehicle model then is validated by comparing the experimental measurements and the simulation predictions of the traditional vehicle. The baseline rule based control strategy and the optimal control strategy using the dynamic programming （DP） algorithm are introduced. Finally, a suboptimal control strategy which employs the new control rules extracted from the optimal control strategy is designed with the remarkable fuel consumption performance.展开更多
In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strat...In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed.Firstly,the construction of the hybrid regenerative braking energy recovery system is explained.Then,based on the power demand of low-voltage load in metro stations,a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions,and the control methods of each system are set.Finally,the correctness and effectiveness of the dual-mode strategy are verified through simulation,and the proposed braking energy utilization scheme is compared with other singleform utilization schemes.The results illustrate that the hybrid system with the dual-mode strategy can effectively recycle the regenerative braking energy of metro train and inhibit the busbar voltage fluctuation;the proposed braking energy utilization scheme has certain advantages on energy recovery and DC bus voltage stabilization compared with other single-form schemes;the proposed power management strategy can correctly allocate the reference power of each system with a lower construction cost.展开更多
Recently, resonant AC/DC converter has been accepted by the industry. However, the efficiency will be decreased at light load. So, a novel topology with critical controlling mode combined with resonant ones is propose...Recently, resonant AC/DC converter has been accepted by the industry. However, the efficiency will be decreased at light load. So, a novel topology with critical controlling mode combined with resonant ones is proposed in this paper. The new topology can correspond to a 90 plus percent of power converting. So,a novel topology of an state of art integrated circuit, which can be used as power management circuit, has been designed based on the above new topology. A simulator which is specifically suitable for the power controller has been founded in this work and it has been used for the simulation of the novel architecture and the proposed integrated circuit.展开更多
The fast acceptance of cloud technology to industry explains increasing energy conservation needs and adoption of energy aware scheduling methods to cloud. Power consumption is one of the top of mind issues in cloud, ...The fast acceptance of cloud technology to industry explains increasing energy conservation needs and adoption of energy aware scheduling methods to cloud. Power consumption is one of the top of mind issues in cloud, because the usage of cloud storage by the individuals or organization grows rapidly. Developing an efficient power management processor architecture has gained considerable attention. However, the conventional power management mechanism fails to consider task scheduling policies. Therefore, this work presents a novel energy aware framework for power management. The proposed system leads to the development of Inclusive Power-Cognizant Processor Controller (IPCPC) for efficient power utilization. To evaluate the performance of the proposed method, simulation experiments inputting random tasks as well as tasks collected from Google Trace Logs were conducted to validate the supremacy of IPCPC. The research based on Real world Google Trace Logs gives results that proposed framework leads to less than 9% of total power consumption per task of server which proves reduction in the overall power needed.展开更多
Integration of hybrid energy storage systems(HESS)into photovoltaic(PV)applications has been a hot topic due to their versatility.However,the proper allocation and power management schemes of HESS are challenges under...Integration of hybrid energy storage systems(HESS)into photovoltaic(PV)applications has been a hot topic due to their versatility.However,the proper allocation and power management schemes of HESS are challenges under diverse mission profiles.In this paper,a cost-effectiveness-oriented two-level scheme is proposed as a guideline for the PV-HESS system(i.e.,PV,Li-ion battery and supercapacitor),to size the system configuration and extend battery lifespan while considering the power ramp-rate constraint.On the first level,a sizing methodology is proposed to balance the self-sufficiency and the energy throughput between the PV system and the grid to achieve the most cost-effectiveness.On the second level,an improved adaptive ramp-rate control strategy is implemented that dynamically distributes the power between the battery and supercapacitor to reduce the battery cycles.The case study presents the whole two-level design process in detail,and verifies the effectiveness of the proposed strategy,where the results show that the battery cycles are reduced by up to 13%over one year without affecting the self-sufficiency of the PV system.展开更多
The use of occupancy information for heating,ventilation,and air conditioning(HVAC)control in smart buildings has become increasingly important for enhancing energy efficiency and occupant comfort.However,residential ...The use of occupancy information for heating,ventilation,and air conditioning(HVAC)control in smart buildings has become increasingly important for enhancing energy efficiency and occupant comfort.However,residential HVAC control presents significant challenges due to the complex dynamic nature of buildings and the uncertainties associated with heat loads and weather conditions.This study addresses this gap in adaptive and energy efficient HVAC control by introducing a quantum reinforcement learning(QRL)based approach.Unlike conventional reinforcement learning techniques,the QRL leverages quantum computing principles to efficiently handle high dimensional state and action spaces,enabling more precise HVAC control in multi-zone residential buildings.The proposed framework integrates real-time occupancy detection using deep learning with operational data,including power consumption patterns,air conditioner control data,and external temperature variations.To evaluate the effectiveness of the proposed approach,simulations were conducted using real world data from 26 residential households over a three month period.The results demonstrate that the QRL based HVAC control significantly reduces energy consumption and electricity costs while maintaining thermal comfort.Compared to the deep deterministic policy gradient method,the QRL approach achieved a 63%reduction in power consumption and a 64.4%decrease in electricity costs.Similarly,it outperformed the proximal policy optimization algorithm,leading to an average reduction of 62.5%in electricity costs and 62.4%in power consumption.展开更多
Nanogenerators utilize nanomaterials to harvest mechanical or thermal energy at the micro-nano scale,thereby providing power for small self-sustaining devices.Compared to traditional generators,nanogenerators offer ad...Nanogenerators utilize nanomaterials to harvest mechanical or thermal energy at the micro-nano scale,thereby providing power for small self-sustaining devices.Compared to traditional generators,nanogenerators offer advantages such as compact size,high flexibility,and broad versatility.Triboelectric nanogenerators(TENGs),based on triboelectric theory,can collect energy from mechanical sources such as vibrations or sliding movements.TENGs hold promise for powering small electronics.However,the high pulse characteristics of their output voltage prevent them from directly charging electronic devices.To address the requirements of the internet of things(IoTs),this paper comprehensively reviews state-of-the-art power management systems used to enhance the current stability and output power of TENGs.First,the working principle and resistive load output characteristics of TENGs are elaborated.Power management circuits(PMCs)based on full-wave rectifiers,half-wave rectifiers,and Bennet's doublers are subsequently analyzed and compared.Mechanical and electronic switches proposed to further improve rectifier performance are also detailed.Mechanical switches are categorized as travel and voltagetriggered switches,while electronic switches include silicon-controlled rectifiers(SCRs),metal-oxide-semiconductor fieldeffect transistors(MOSFETs),and integrated circuits.In conclusion,the characteristics and applications of PMCs are summarized,along with the identification of existing limitations in their application.Subsequently,appropriate solutions and prospects for further development are explored.展开更多
In aerospace systems,wireless sensor networks(WSNs)are widely used for structural health monitoring and environmental data collection.Self-powered sensing technology effectively reduces wiring requirements,enabling di...In aerospace systems,wireless sensor networks(WSNs)are widely used for structural health monitoring and environmental data collection.Self-powered sensing technology effectively reduces wiring requirements,enabling distributed,adaptive,and long-term monitoring.However,the randomness and instability of ambient energy harvesting pose significant challenges for efficient energy extraction,conversion,and storage.This study proposes a six-channel array piezoelectric vibration energy harvester(SA-PVEH)suitable for medium-to-high frequency scenarios,capable of delivering high output power over a broad frequency range.By integrating a parallel synchronized switch harvesting on an inductor(P-SSHI)interface circuit with split inductors and capacitors,along with a threshold-triggered intermittent energy scheduling method,efficient energy conversion and transfer are achieved.Under external excitation with a frequency of 640 Hz and an acceleration of 1 g,the system achieves a maximum output power of 1.17 mW with a power management circuit(PMC)efficiency of 84.7%.Finally,the self-powered aerospace sensing system(SP-ASS)was employed for application in pressure monitoring on the fixed-wing aircraft Aurora SA60L.展开更多
This paper presents an integrated power management unit （PMU） for a battery-operated wireless endoscopic system. This PMU is integrated with a baseband chip in standard 0.18μm CMOS technology,promising low cost, ea...This paper presents an integrated power management unit （PMU） for a battery-operated wireless endoscopic system. This PMU is integrated with a baseband chip in standard 0.18μm CMOS technology,promising low cost, ease in PCB design, and a minimum in system size. The optimized power supply architecture is derived from comparison. Circuits of sub blocks are presented in detail. As a result, only five small off-chip capacitances are required by PMU with an overall quiet current consumption of less than 100μA. Moreover,a digital calibration method is adopted to alleviate the effect of process variation. The achieved performance is also demonstrated with corresponding measurement results.展开更多
The penetration of renewable energy sources(RESs)in the distribution system becomes a challenge for the reliable and safe operation of the existing power system.The sporadic characteristics of sustainable energy sourc...The penetration of renewable energy sources(RESs)in the distribution system becomes a challenge for the reliable and safe operation of the existing power system.The sporadic characteristics of sustainable energy sources along with the random load variations greatly affect the power quality and stability of the system.Hence,it requires storage systems with both high energy and high power handling capacity to coexist in microgrids.An efficient energy management structure is designed in this paper for a grid-connected PV system combined with hybrid storage of supercapacitor and battery.The combined supercapacitor and battery storage system grips the average and transient power changes,which provides a quick control for the DC-link voltage,i.e.,it stabilizes the system and helps achieve the PV power smoothing.The average power distribution between the power grid and battery is done by checking the state of charge(SOC)of a battery,and an effective and efficient energy management scheme is proposed.Additionally,the use of a supercapacitor lessens the current stress on the battery system during unexpected disparity in the generated power and load requirement.The performance and efficacy of the proposed energy management scheme are justified by simulation studies.展开更多
The existing power management schemes for interlinked AC-DC microgrids have several operational drawbacks.Some of the existing control schemes are designed with the main objective of sharing power among the interlinke...The existing power management schemes for interlinked AC-DC microgrids have several operational drawbacks.Some of the existing control schemes are designed with the main objective of sharing power among the interlinked microgrids based on their loading conditions,while other schemes regulate the voltage of the interlinked microgrids without considering the specific loading conditions.However,the existing schemes cannot achieve both objectives efficiently.To address these issues,an autonomous power management scheme is proposed,which explicitly considers the specific loading condition of the DC microgrid before importing power from the interlinked AC microgrid.This strategy enables voltage regulation in the DC microgrid,and also reduces the number of converters in operation.The proposed scheme is fully autonomous while it retains the plug-nplay features for generators and tie-converters.The performance of the proposed control scheme has been validated under different operating scenarios.The results demonstrate the effectiveness of the proposed scheme in managing the power deficit in the DC microgrid efficiently and autonomously while maintaining the better voltage regulation in the DC microgrid.展开更多
Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units ba...Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units based on predictions of event occurrences. However, since each mode change induces some overhead in its own right, guaranteeing DPM＇s eificiency is no mean feat in environments exhibiting non-determinism and uncertainty with unknown statistics. Our solution suite in this paper, collectively referred to as cognitive power management （CPM）, is a principled attempt toward enabling DPM in statistically unknown settings and gives two different analytical guarantees. Our first design is based on learning automata and guarantees better-than-pure-chance DPM in the face of non-stationary event processes. Our second solution caters tor an even more general setting in which event occurrences may take on an adversarial character. In this case, we formulate the interaction of an individual mote with its environment in terms of a repeated zero-sum game in which the node relies on a no-external-regret procedure to learn its mini-max strategies in an online fashion. We conduct numerical experiments to measure the performance of our schemes in terms of network lifetime and event loss percentage.展开更多
Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing the...Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing their power consumption. In this paper, we propose GreenCHT, a reliable power management scheme for consistent hashing based distributed key value storage systems. It consists of a multi-tier replication scheme, a reliable distributed log store, and a predictive power mode scheduler （PMS）. Instead of randomly placing replicas of each object on a number of nodes in the consistent hash ring, we arrange the replicas of objects on nonoverlapping tiers of nodes in the ring. This allows the system to fall in various power modes by powering down subsets of servers while not violating data availability. The predictive PMS predicts workloads and adapts to load fluctuation. It cooperates with the multi-tier replication strategy to provide power proportionality for the system. To ensure that the reliability of the system is maintained when replicas are powered down, we distribute the writes to standby replicas to active servers, which ensures failure tolerance of the system. GreenCHT is implemented based on Sheepdog, a distributed key value storage system that uses consistent hashing as an underlying distributed hash table. By replaying 12 typical real workload traces collected from Microsoft, the evaluation results show that GreenCHT can provide significant power savings while maintaining a desired performance. We observe that GreenCHT can reduce power consumption by up to 35%-61%.展开更多
This paper proposes a novel power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning algorithm.Three parallel soft actor-critic(SAC)networks are trained for high speed,medium...This paper proposes a novel power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning algorithm.Three parallel soft actor-critic(SAC)networks are trained for high speed,medium speed,and low-speed conditions respectively;the reward function is designed as minimizing the cost of energy cost and battery aging.During operation,the driving condition is recognized at each moment for the algorithm invoking based on the learning vector quantization(LVQ)neural network.On top of that,a driving cycle reconstruction algorithm is proposed.The historical speed segments that were recorded during the operation are reconstructed into the three categories of high speed,medium speed,and low speed,based on which the algorithms are online updated.The SAC-based control strategy is evaluated based on the standard driving cycles and Shenyang practical data.The results indicate the presented method can obtain the effect close to dynamic programming and can be further improved by up to 6.38%after the online update for uncertain driving conditions.展开更多
Recently, triboelectric nanogenerators （TENGs）, as a collection technology with characteristics of high reliability, high energy density and low cost, has attracted more and more attention. However, the energy comin...Recently, triboelectric nanogenerators （TENGs）, as a collection technology with characteristics of high reliability, high energy density and low cost, has attracted more and more attention. However, the energy coming from TENGs needs to be stored in a storage unit effectively due to its unstable ac output. The traditional energy storage circuit has an extremely low energy storage efficiency for TENGs because of their high internal impedance. This paper presents a new power management circuit used to optimize the energy using efficiency of TENGs, and realize large load capacity. The power management circuit mainly includes rectification storage circuit and DC-DC management circuit. A rotating TENG with maximal energy output of 106 mW at 170 rpm based on PCB is used for the experimental verification. Experimental results show that the power energy transforming to the storage capacitor reach up to 53 mW and the energy using efficiency is calculated as 50%. When different loading resistances range from 0.82 to 34.5 k^2 are connected to the storage capacitor in parallel, the power energy stored in the storage capacitor is all about 52.5 mW. Getting through the circuit, the power energy coming from the TENGs can be used to drive numerous conventional electronics, such as wearable watches.展开更多
Hybrid systems based on renewable energies for the electrification of remote sites controlled by power management systems(PMSs)aim to reduce fossil fuels and increase the efficiency of renewable energy sources to mini...Hybrid systems based on renewable energies for the electrification of remote sites controlled by power management systems(PMSs)aim to reduce fossil fuels and increase the efficiency of renewable energy sources to minimize greenhouse gas emissions.The influential role of the PMS contributes to improving the efficiency and effectiveness of these systems by ensuring a balance between the different sources and loads in all operating modes.However,the abrupt transitions between the various operational modes selected by the PMS generate power loss and imbalance.To handle this issue,a fuzzy logic controller(FLC)-based PMS controlling a photovoltaic(PV)and diesel hybrid system with a battery storage element connected to a DC bus is proposed in this paper.The proposed PMS is wholly based on FLC to ensure a smooth transition between the different modes of the system.The success of using the suggested PMS lies in how well the FLC parameters are chosen before the system is processed.For this purpose,the particle swarm optimization algorithm is adapted to tune the FLC parameters.The resulting optimal intelligent PMS is tested and compared with a classical one using comprehensive simulations performed in a Simscape ElectricalTM MATLAB®environment.The obtained results show an overshoot attenuation at the DC-bus voltage of 2%when changing the mode and an improvement in the PV generator efficiency by 99.5%.展开更多
This first quarter of the 21st century is increasingly marked by population growth,digital and industrial developments,a growing need for electricity supply,and climate change.All these,to name just a few,have made th...This first quarter of the 21st century is increasingly marked by population growth,digital and industrial developments,a growing need for electricity supply,and climate change.All these,to name just a few,have made the establishment of a stable,flexible,controlled,well-designed,extensive,and clean power system a necessity.Consequently,distributed microgrid generation based on alternative/renewable energies and/or low-carbon technologies has emerged.In this paper,we study the modeling,the control,and the power management strategy of a grid-connected hybrid alternating/direct current(AC/DC)microgrid based on a wind turbine generation system using a doubly fed induction generator,a photovoltaic generation system,and storage elements including hydrogen storage system and batteries.Adequate modeling is described,and the overall system monitoring is presented and applied to manage appropri-ate power sharing and to control active and reactive powers,in order to match load and weather fluctuation behavior.Simulations are carried out using a MATLAB/Simulink simulation tool.Simulations reveal convenient results in terms of the bidirectional interlinking converter capabilities regarding power balance establishment between the two subgrids,reactive power compensation to ensure a unity power factor,and DC-bus voltage regulation at 1200 V.In addition,the primary and secondary controls are approved for each distributed generation of the studied system to attain the assigned power references,regardless of whether the subgrid is heavily or lightly loaded throughout the four considered case studies,showing satisfactory tracking and interacting performances,and thus stimulating a stable system implementation.展开更多
With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total co...With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total costs of fuel cell systems are still too high,thus limiting the further development of fuel cell hybrid electric vehicles.This paper presents an energy management strategy(EMS)based on deep reinforcement learning for the energy management of fuel cell hybrid electric vehicles.The energy management model of a fuel cell hybrid electric bus and its main components are established.Considering the power response characteristics of the fuel cell system,the power change rate of the fuel cell system is reasonably limited and introduced as action variables into the network of Double Deep Q-Learning(DDQL),and a novel DDQL-based EMS is developed for the fuel cell hybrid electric bus.Subsequently,a comparative test is conducted with the DP-based and the Rule-based EMS to analyze the performance of the DDQL-based EMS.The results indicate that the proposed EMS achieves good fuel economy performance,with an improvement of 15.4%compared to the Rule-based EMS under the training scenarios.In terms of generalization performance,the proposed EMS also achieves good fuel economy performance,which improves by 13.3%compared to the Rule-based energy management strategy under the testing scenario.展开更多
文摘A power management unit （PMU） chip supplying dual panel supply voltage, which has a low electro-magnetic interference （EMI） characteristic and is favorable for miniaturization, is designed. A two-phase charge pump circuit using external pumping capacitor increases its pumping current and works out the charge-loss problem by using bulk-potential biasing circuit. A low-power start-up circuit is also proposed to reduce the power consumption of the band-gap reference voltage generator. And the ring oscillator used in the ELVSS power circuit is designed with logic devices by supplying the logic power supply to reduce the layout area. The PMU chip is designed with MagnaChip＇s 0.25 μ high-voltage process. The driving currents of ELVDD and ELVSS are more than 50 mA when a SPICE simulation is done.
基金Supported by the National Natural Science Foundation of China(60774064,61305133)the National Research Foundation for the Doctoral Program of Higher Education of China(20116102110026)+1 种基金the Aerospace Technology Support Foundation(2013-HT-XGD)the Aeronautical Science Foundation of China(2013zc53037)
文摘To solve the problem of dynamic power resource allocation for cooperative penetration combat,the continuous game theory is introduced and a two-person general-sum continuous-game-based model is put forward with a common payoff function named collaborative detection probability of netted radar countermeasures.Comparing with traditional optimization methods,an obvious advantage of game-based model is an adequate consideration of the opposite potential strategy.This model guarantees a more effective allocation of the both sides′power resource and a higher combat efficiency during a combat.Furthermore,an analysis of the complexity of the proposed model is given and a hierarchical processing method is presented to simplify the calculating process.Simulation results show the validity of the proposed scheme.
基金the Special Project on the Integration of Industry,Education and Research of Guangdong Province,China(No.2011A090200077)
文摘This paper presents an integrated and detailed procedure to improve tile power management feature implemented in the integrated starter-generator （ISG） parallel hybrid electric vehicle. First, the configuration of the single-shaft ISG hybrid vehicle model established in MATLAB-Simulink environment is given. The vehicle model then is validated by comparing the experimental measurements and the simulation predictions of the traditional vehicle. The baseline rule based control strategy and the optimal control strategy using the dynamic programming （DP） algorithm are introduced. Finally, a suboptimal control strategy which employs the new control rules extracted from the optimal control strategy is designed with the remarkable fuel consumption performance.
基金funded by Project supported by the Natural Science Foundation of Gansu Province,China(Grant No.22JR5RA318).
文摘In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage,a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed.Firstly,the construction of the hybrid regenerative braking energy recovery system is explained.Then,based on the power demand of low-voltage load in metro stations,a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions,and the control methods of each system are set.Finally,the correctness and effectiveness of the dual-mode strategy are verified through simulation,and the proposed braking energy utilization scheme is compared with other singleform utilization schemes.The results illustrate that the hybrid system with the dual-mode strategy can effectively recycle the regenerative braking energy of metro train and inhibit the busbar voltage fluctuation;the proposed braking energy utilization scheme has certain advantages on energy recovery and DC bus voltage stabilization compared with other single-form schemes;the proposed power management strategy can correctly allocate the reference power of each system with a lower construction cost.
基金supported by Program for New Century Excellent Talents in University(NCET)(2008)Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality+1 种基金 (PHR(IHLB)) and Beijing Novel Research Star(2005B01)Ministry of Beijing Science and Technology
文摘Recently, resonant AC/DC converter has been accepted by the industry. However, the efficiency will be decreased at light load. So, a novel topology with critical controlling mode combined with resonant ones is proposed in this paper. The new topology can correspond to a 90 plus percent of power converting. So,a novel topology of an state of art integrated circuit, which can be used as power management circuit, has been designed based on the above new topology. A simulator which is specifically suitable for the power controller has been founded in this work and it has been used for the simulation of the novel architecture and the proposed integrated circuit.
文摘The fast acceptance of cloud technology to industry explains increasing energy conservation needs and adoption of energy aware scheduling methods to cloud. Power consumption is one of the top of mind issues in cloud, because the usage of cloud storage by the individuals or organization grows rapidly. Developing an efficient power management processor architecture has gained considerable attention. However, the conventional power management mechanism fails to consider task scheduling policies. Therefore, this work presents a novel energy aware framework for power management. The proposed system leads to the development of Inclusive Power-Cognizant Processor Controller (IPCPC) for efficient power utilization. To evaluate the performance of the proposed method, simulation experiments inputting random tasks as well as tasks collected from Google Trace Logs were conducted to validate the supremacy of IPCPC. The research based on Real world Google Trace Logs gives results that proposed framework leads to less than 9% of total power consumption per task of server which proves reduction in the overall power needed.
文摘Integration of hybrid energy storage systems(HESS)into photovoltaic(PV)applications has been a hot topic due to their versatility.However,the proper allocation and power management schemes of HESS are challenges under diverse mission profiles.In this paper,a cost-effectiveness-oriented two-level scheme is proposed as a guideline for the PV-HESS system(i.e.,PV,Li-ion battery and supercapacitor),to size the system configuration and extend battery lifespan while considering the power ramp-rate constraint.On the first level,a sizing methodology is proposed to balance the self-sufficiency and the energy throughput between the PV system and the grid to achieve the most cost-effectiveness.On the second level,an improved adaptive ramp-rate control strategy is implemented that dynamically distributes the power between the battery and supercapacitor to reduce the battery cycles.The case study presents the whole two-level design process in detail,and verifies the effectiveness of the proposed strategy,where the results show that the battery cycles are reduced by up to 13%over one year without affecting the self-sufficiency of the PV system.
基金partly supported by Korea Evaluation Institute of Industrial Technology(KEIT)grant funded by the Korea government(MOTIE)(No.RS-2025-04752989,Quantum battery core technology for ultra-fast charging 100x faster than traditional lithium-ion batteries)Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2025-02304333,Development of digital innovation element technology to achieve full-cycle zero-touch in AX-based manufacturing and service)。
文摘The use of occupancy information for heating,ventilation,and air conditioning(HVAC)control in smart buildings has become increasingly important for enhancing energy efficiency and occupant comfort.However,residential HVAC control presents significant challenges due to the complex dynamic nature of buildings and the uncertainties associated with heat loads and weather conditions.This study addresses this gap in adaptive and energy efficient HVAC control by introducing a quantum reinforcement learning(QRL)based approach.Unlike conventional reinforcement learning techniques,the QRL leverages quantum computing principles to efficiently handle high dimensional state and action spaces,enabling more precise HVAC control in multi-zone residential buildings.The proposed framework integrates real-time occupancy detection using deep learning with operational data,including power consumption patterns,air conditioner control data,and external temperature variations.To evaluate the effectiveness of the proposed approach,simulations were conducted using real world data from 26 residential households over a three month period.The results demonstrate that the QRL based HVAC control significantly reduces energy consumption and electricity costs while maintaining thermal comfort.Compared to the deep deterministic policy gradient method,the QRL approach achieved a 63%reduction in power consumption and a 64.4%decrease in electricity costs.Similarly,it outperformed the proximal policy optimization algorithm,leading to an average reduction of 62.5%in electricity costs and 62.4%in power consumption.
基金supported by the National Natural Science Foundation of China(Grant Nos.62225308,62001281)Shanghai Science and Technology Committee(Grant No.22dz1204300)。
文摘Nanogenerators utilize nanomaterials to harvest mechanical or thermal energy at the micro-nano scale,thereby providing power for small self-sustaining devices.Compared to traditional generators,nanogenerators offer advantages such as compact size,high flexibility,and broad versatility.Triboelectric nanogenerators(TENGs),based on triboelectric theory,can collect energy from mechanical sources such as vibrations or sliding movements.TENGs hold promise for powering small electronics.However,the high pulse characteristics of their output voltage prevent them from directly charging electronic devices.To address the requirements of the internet of things(IoTs),this paper comprehensively reviews state-of-the-art power management systems used to enhance the current stability and output power of TENGs.First,the working principle and resistive load output characteristics of TENGs are elaborated.Power management circuits(PMCs)based on full-wave rectifiers,half-wave rectifiers,and Bennet's doublers are subsequently analyzed and compared.Mechanical and electronic switches proposed to further improve rectifier performance are also detailed.Mechanical switches are categorized as travel and voltagetriggered switches,while electronic switches include silicon-controlled rectifiers(SCRs),metal-oxide-semiconductor fieldeffect transistors(MOSFETs),and integrated circuits.In conclusion,the characteristics and applications of PMCs are summarized,along with the identification of existing limitations in their application.Subsequently,appropriate solutions and prospects for further development are explored.
基金supported by the Key Program of the National Natural Science Foundation of China(Grant No.U22B2089)the Fundamental Research Funds for the Central Universities(Grant No.2024CDIGF-005)+1 种基金the Science Fund for Distinguished Young Scholars of Chongqing(Grant No.CSTB2022 NSCQ-JQX0006)Open Project of the Defense Key Disciplines Lab of Novel Micro-nano Devices and System Technology。
文摘In aerospace systems,wireless sensor networks(WSNs)are widely used for structural health monitoring and environmental data collection.Self-powered sensing technology effectively reduces wiring requirements,enabling distributed,adaptive,and long-term monitoring.However,the randomness and instability of ambient energy harvesting pose significant challenges for efficient energy extraction,conversion,and storage.This study proposes a six-channel array piezoelectric vibration energy harvester(SA-PVEH)suitable for medium-to-high frequency scenarios,capable of delivering high output power over a broad frequency range.By integrating a parallel synchronized switch harvesting on an inductor(P-SSHI)interface circuit with split inductors and capacitors,along with a threshold-triggered intermittent energy scheduling method,efficient energy conversion and transfer are achieved.Under external excitation with a frequency of 640 Hz and an acceleration of 1 g,the system achieves a maximum output power of 1.17 mW with a power management circuit(PMC)efficiency of 84.7%.Finally,the self-powered aerospace sensing system(SP-ASS)was employed for application in pressure monitoring on the fixed-wing aircraft Aurora SA60L.
基金the National Natural Science Foundation of China(No.60475018)~~
文摘This paper presents an integrated power management unit （PMU） for a battery-operated wireless endoscopic system. This PMU is integrated with a baseband chip in standard 0.18μm CMOS technology,promising low cost, ease in PCB design, and a minimum in system size. The optimized power supply architecture is derived from comparison. Circuits of sub blocks are presented in detail. As a result, only five small off-chip capacitances are required by PMU with an overall quiet current consumption of less than 100μA. Moreover,a digital calibration method is adopted to alleviate the effect of process variation. The achieved performance is also demonstrated with corresponding measurement results.
文摘The penetration of renewable energy sources(RESs)in the distribution system becomes a challenge for the reliable and safe operation of the existing power system.The sporadic characteristics of sustainable energy sources along with the random load variations greatly affect the power quality and stability of the system.Hence,it requires storage systems with both high energy and high power handling capacity to coexist in microgrids.An efficient energy management structure is designed in this paper for a grid-connected PV system combined with hybrid storage of supercapacitor and battery.The combined supercapacitor and battery storage system grips the average and transient power changes,which provides a quick control for the DC-link voltage,i.e.,it stabilizes the system and helps achieve the PV power smoothing.The average power distribution between the power grid and battery is done by checking the state of charge(SOC)of a battery,and an effective and efficient energy management scheme is proposed.Additionally,the use of a supercapacitor lessens the current stress on the battery system during unexpected disparity in the generated power and load requirement.The performance and efficacy of the proposed energy management scheme are justified by simulation studies.
文摘The existing power management schemes for interlinked AC-DC microgrids have several operational drawbacks.Some of the existing control schemes are designed with the main objective of sharing power among the interlinked microgrids based on their loading conditions,while other schemes regulate the voltage of the interlinked microgrids without considering the specific loading conditions.However,the existing schemes cannot achieve both objectives efficiently.To address these issues,an autonomous power management scheme is proposed,which explicitly considers the specific loading condition of the DC microgrid before importing power from the interlinked AC microgrid.This strategy enables voltage regulation in the DC microgrid,and also reduces the number of converters in operation.The proposed scheme is fully autonomous while it retains the plug-nplay features for generators and tie-converters.The performance of the proposed control scheme has been validated under different operating scenarios.The results demonstrate the effectiveness of the proposed scheme in managing the power deficit in the DC microgrid efficiently and autonomously while maintaining the better voltage regulation in the DC microgrid.
文摘Dynamic power management （DPM） in wireless sensor nodes is a well-known technique for reducing idle energy consumption. DPM controls a node＇s operating mode by dynamically toggling the on/off status of its units based on predictions of event occurrences. However, since each mode change induces some overhead in its own right, guaranteeing DPM＇s eificiency is no mean feat in environments exhibiting non-determinism and uncertainty with unknown statistics. Our solution suite in this paper, collectively referred to as cognitive power management （CPM）, is a principled attempt toward enabling DPM in statistically unknown settings and gives two different analytical guarantees. Our first design is based on learning automata and guarantees better-than-pure-chance DPM in the face of non-stationary event processes. Our second solution caters tor an even more general setting in which event occurrences may take on an adversarial character. In this case, we formulate the interaction of an individual mote with its environment in terms of a repeated zero-sum game in which the node relies on a no-external-regret procedure to learn its mini-max strategies in an online fashion. We conduct numerical experiments to measure the performance of our schemes in terms of network lifetime and event loss percentage.
文摘Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing their power consumption. In this paper, we propose GreenCHT, a reliable power management scheme for consistent hashing based distributed key value storage systems. It consists of a multi-tier replication scheme, a reliable distributed log store, and a predictive power mode scheduler （PMS）. Instead of randomly placing replicas of each object on a number of nodes in the consistent hash ring, we arrange the replicas of objects on nonoverlapping tiers of nodes in the ring. This allows the system to fall in various power modes by powering down subsets of servers while not violating data availability. The predictive PMS predicts workloads and adapts to load fluctuation. It cooperates with the multi-tier replication strategy to provide power proportionality for the system. To ensure that the reliability of the system is maintained when replicas are powered down, we distribute the writes to standby replicas to active servers, which ensures failure tolerance of the system. GreenCHT is implemented based on Sheepdog, a distributed key value storage system that uses consistent hashing as an underlying distributed hash table. By replaying 12 typical real workload traces collected from Microsoft, the evaluation results show that GreenCHT can provide significant power savings while maintaining a desired performance. We observe that GreenCHT can reduce power consumption by up to 35%-61%.
基金National Natural Science Foundation of China(51977029,52177210)Liaoning Provincial Science and Technology planned project(2021JH6/10500135)+1 种基金Fundamental Research Funds for the Central Universities(N2003002)Any opinions expressed in this paper are solely those of the authors and do not represent those of the sponsors.
文摘This paper proposes a novel power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning algorithm.Three parallel soft actor-critic(SAC)networks are trained for high speed,medium speed,and low-speed conditions respectively;the reward function is designed as minimizing the cost of energy cost and battery aging.During operation,the driving condition is recognized at each moment for the algorithm invoking based on the learning vector quantization(LVQ)neural network.On top of that,a driving cycle reconstruction algorithm is proposed.The historical speed segments that were recorded during the operation are reconstructed into the three categories of high speed,medium speed,and low speed,based on which the algorithms are online updated.The SAC-based control strategy is evaluated based on the standard driving cycles and Shenyang practical data.The results indicate the presented method can obtain the effect close to dynamic programming and can be further improved by up to 6.38%after the online update for uncertain driving conditions.
文摘Recently, triboelectric nanogenerators （TENGs）, as a collection technology with characteristics of high reliability, high energy density and low cost, has attracted more and more attention. However, the energy coming from TENGs needs to be stored in a storage unit effectively due to its unstable ac output. The traditional energy storage circuit has an extremely low energy storage efficiency for TENGs because of their high internal impedance. This paper presents a new power management circuit used to optimize the energy using efficiency of TENGs, and realize large load capacity. The power management circuit mainly includes rectification storage circuit and DC-DC management circuit. A rotating TENG with maximal energy output of 106 mW at 170 rpm based on PCB is used for the experimental verification. Experimental results show that the power energy transforming to the storage capacitor reach up to 53 mW and the energy using efficiency is calculated as 50%. When different loading resistances range from 0.82 to 34.5 k^2 are connected to the storage capacitor in parallel, the power energy stored in the storage capacitor is all about 52.5 mW. Getting through the circuit, the power energy coming from the TENGs can be used to drive numerous conventional electronics, such as wearable watches.
文摘Hybrid systems based on renewable energies for the electrification of remote sites controlled by power management systems(PMSs)aim to reduce fossil fuels and increase the efficiency of renewable energy sources to minimize greenhouse gas emissions.The influential role of the PMS contributes to improving the efficiency and effectiveness of these systems by ensuring a balance between the different sources and loads in all operating modes.However,the abrupt transitions between the various operational modes selected by the PMS generate power loss and imbalance.To handle this issue,a fuzzy logic controller(FLC)-based PMS controlling a photovoltaic(PV)and diesel hybrid system with a battery storage element connected to a DC bus is proposed in this paper.The proposed PMS is wholly based on FLC to ensure a smooth transition between the different modes of the system.The success of using the suggested PMS lies in how well the FLC parameters are chosen before the system is processed.For this purpose,the particle swarm optimization algorithm is adapted to tune the FLC parameters.The resulting optimal intelligent PMS is tested and compared with a classical one using comprehensive simulations performed in a Simscape ElectricalTM MATLAB®environment.The obtained results show an overshoot attenuation at the DC-bus voltage of 2%when changing the mode and an improvement in the PV generator efficiency by 99.5%.
文摘This first quarter of the 21st century is increasingly marked by population growth,digital and industrial developments,a growing need for electricity supply,and climate change.All these,to name just a few,have made the establishment of a stable,flexible,controlled,well-designed,extensive,and clean power system a necessity.Consequently,distributed microgrid generation based on alternative/renewable energies and/or low-carbon technologies has emerged.In this paper,we study the modeling,the control,and the power management strategy of a grid-connected hybrid alternating/direct current(AC/DC)microgrid based on a wind turbine generation system using a doubly fed induction generator,a photovoltaic generation system,and storage elements including hydrogen storage system and batteries.Adequate modeling is described,and the overall system monitoring is presented and applied to manage appropri-ate power sharing and to control active and reactive powers,in order to match load and weather fluctuation behavior.Simulations are carried out using a MATLAB/Simulink simulation tool.Simulations reveal convenient results in terms of the bidirectional interlinking converter capabilities regarding power balance establishment between the two subgrids,reactive power compensation to ensure a unity power factor,and DC-bus voltage regulation at 1200 V.In addition,the primary and secondary controls are approved for each distributed generation of the studied system to attain the assigned power references,regardless of whether the subgrid is heavily or lightly loaded throughout the four considered case studies,showing satisfactory tracking and interacting performances,and thus stimulating a stable system implementation.
基金Supported by National Natural Science Foundation of China(Grant Nos.U1864205,Grant No.52172377).
文摘With increasingly serious environmental pollution and the energy crisis,fuel cell hybrid electric vehicles have been considered as an ideal alternative to traditional hybrid electric vehicles.Nevertheless,the total costs of fuel cell systems are still too high,thus limiting the further development of fuel cell hybrid electric vehicles.This paper presents an energy management strategy(EMS)based on deep reinforcement learning for the energy management of fuel cell hybrid electric vehicles.The energy management model of a fuel cell hybrid electric bus and its main components are established.Considering the power response characteristics of the fuel cell system,the power change rate of the fuel cell system is reasonably limited and introduced as action variables into the network of Double Deep Q-Learning(DDQL),and a novel DDQL-based EMS is developed for the fuel cell hybrid electric bus.Subsequently,a comparative test is conducted with the DP-based and the Rule-based EMS to analyze the performance of the DDQL-based EMS.The results indicate that the proposed EMS achieves good fuel economy performance,with an improvement of 15.4%compared to the Rule-based EMS under the training scenarios.In terms of generalization performance,the proposed EMS also achieves good fuel economy performance,which improves by 13.3%compared to the Rule-based energy management strategy under the testing scenario.
