Regenerative Braking Energy Recovery System of Metro Train Based on Dual-Mode Power Management

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.

Power management unit chip design for automobile active-matrix organic light-emitting diode display module

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.

Optimal Power Management for Antagonizing Between Radar and Jamming Based on Continuous Game Theory

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.

A novel design of power management integrated circuit with 90 plus efficiency used in AC/DC converter

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.

Energy Aware Processor Architecture for Effective Scheduling and Power Management in Cloud Using Inclusive Power-Cognizant Processor Controller

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.

IoT-Enabled Plant Monitoring System with Power Optimization and Secure Authentication

Global food security is a pressing issue that affects the stability and well-being of communities worldwide.While existing Internet of Things(IoT)enabled plant monitoring systems have made significant strides in agricultural monitoring,they often face limitations such as high power consumption,restricted mobility,complex deployment requirements,and inadequate security measures for data access.This paper introduces an enhanced IoT application for agricultural monitoring systems that address these critical shortcomings.Our system strategically combines power efficiency,portability,and secure access capabilities,assisting farmers in monitoring and tracking crop environmental conditions.The proposed system includes a remote camera that captures images of surrounding plants and a sensor module that regularly monitors various environmental factors,including temperature,humidity,and soil moisture.We implement power management strategies to minimize energy consumption compared to existing solutions.Unlike conventional systems,our implementation utilizes the Amazon Web Services(AWS)cloud platform for reliable data storage and processing while incorporating comprehensive security measures,including Two-Factor Authentication(2FA)and JSON Web Tokens(JWT),features often overlooked in current agricultural IoT solutions.Users can access this secure monitoring system via a developed Android application,providing convenient mobile access to the gathered plant data.We validate our system’s advantages by implementing it with two potted garlic plants on Okayama University’s rooftop.Our evaluation demonstrates high sensor reliabil-ity,with strong correlations between sensor readings and reference data,achieving determination coefficients(R2)of 0.979 for temperature and 0.750 for humidity measurements.The implemented power management strategies extend battery life to 10 days on a single charge,significantly outperforming existing systems that typically require daily recharging.Furthermore,our dual-layer security implementation utilizing 2FA and JWT successfully protects sensitive agricultural data from unauthorized access.

An Integrated Power Management Unit for a Battery-Operated Wireless Endoscopic System

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.

Study on green power supply modes for heavy load in Remote Areas

In this study,the present situation and characteristics of power supply in remote areas are summarized.By studying the cases of power supply projects in remote areas,the experience is analyzed and described,and the applicability of related technologies,such as grid-forming storage and power load management,is studied,including grid-connection technologies,such as grid-forming converters and power load management.On this basis,three power-supply modes were proposed.The application scenarios and advantages of the three modes were compared and analyzed.Based on the local development situation,the temporal sequences of the three schemes are described,and a case study was conducted.The study of the heavy-load power supply mode in remote areas contributes to solving the problem of heavy-load green power consumption in remote areas and promoting the further development of renewable energy.

A Power Management Scheme for Grid-connected PV Integrated with Hybrid Energy Storage System

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.

Autonomous Power Management for Interlinked AC-DC Microgrids

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.

Cognitive Power Management in Wireless Sensor Networks

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.

A reliable power management scheme for consistent hashing based distributed key value storage systems

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%.

Power Management of Parallel Hybrid Electric Power Train

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.

Online power management strategy for plug-in hybrid electric vehicles based on deep reinforcement learning and driving cycle reconstruction

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.

A power management circuit with 50%efficiency and large load capacity for tribo-electric nanogenerator

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.

Unified fuzzy logic controller and power management for an isolated residential hybrid PV/diesel/battery energy system

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%.

Practicality of power load management system in Chongqing City verified

Began from early 1992, Chongqing Power Supply Bureau had spent 3 and half years to build up a power load management system consisting of I master station, 6 relay stations, 1280 terminals and the distributed monitoring device. This system distributes in the hilly and mountainous areas where geographically complicated and the load widely scatters, it can supervise about 72% load and curtail more than 15% load

Power Production Management of Three Gorges Project

The Three Gorges Hydropower Plant is the one with the largest installed capacity in the world today and has a decisive and important influence upon the security of the national power grids. It has been operated stably and supplied the East China, Central China, South China, Sichuan and Chongqing with clean renewable energy. This paper presents the management of the project’s dispatch, operation and maintenance and puts forward new ideas and new methods for the plant management, which may provide valuable references for the operation of oversized hydropower plants.

Technical Management in Power Plant Constructionfor Export Contract

Regarding the technical management during construction of Thailand PTA Co-generation, there are some problems due to the typical method in electric power construction in China, which show the differences between international methods and ours. In order to do the technical management in the project for export contract, it is necessary to do the work based on the Contract, to know the related laws and regulations, and national conditions, to coordinate the relationship among various parties well, and to carry out the management ahead of time.