Reinforcement Learning-Based Energy Management for Hybrid Power Systems:State-of-the-Art Survey,Review,and Perspectives

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving.This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems.Additionally,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational technology.First of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a timeline.Then,the comprehensive survey and review are conducted by collecting papers from mainstream academic databases.Enumerating most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research status.Finally,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.

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.

Multi-source heterogeneous data access management framework and key technologies for electric power Internet of Things

The power Internet of Things(IoT)is a significant trend in technology and a requirement for national strategic development.With the deepening digital transformation of the power grid,China’s power system has initially built a power IoT architecture comprising a perception,network,and platform application layer.However,owing to the structural complexity of the power system,the construction of the power IoT continues to face problems such as complex access management of massive heterogeneous equipment,diverse IoT protocol access methods,high concurrency of network communications,and weak data security protection.To address these issues,this study optimizes the existing architecture of the power IoT and designs an integrated management framework for the access of multi-source heterogeneous data in the power IoT,comprising cloud,pipe,edge,and terminal parts.It further reviews and analyzes the key technologies involved in the power IoT,such as the unified management of the physical model,high concurrent access,multi-protocol access,multi-source heterogeneous data storage management,and data security control,to provide a more flexible,efficient,secure,and easy-to-use solution for multi-source heterogeneous data access in the power IoT.

Imperative for long-term management and surveillance in Kawasaki disease

Kawasaki disease(KD)is a significant pediatric vasculitis known for its potential to cause severe coronary artery complications.Despite the effectiveness of initial treatments,such as intravenous immunoglobulin,KD patients can experience long-term cardiovascular issues,as evidenced by a recent case report of an adult who suffered a ST-segment elevation myocardial infarction due to previous KD in the World Journal of Clinical Cases.This editorial emphasizes the critical need for long-term management and regular surveillance to prevent such complications.By drawing on recent research and case studies,we advocate for a structured approach to follow-up care that includes routine cardiac evaluations and preventive measures.

Corroborative Activities and Recognition Between Community Comprehensive Care Unit’s Nurses and Care Managers in Supporting Discharge of Elderly from Hospital - A Secondary Publication

Objective: The purpose of this study was to clarify the collaborative activities and mutual recognition between community comprehensive care unit nurses (Ns) and care managers (CM) in supporting the discharge of the elderly from the hospital. Methods: A total of 300 nurses working in community comprehensive care wards and 360 care managers working in B City in A Prefecture were surveyed using an anonymous self-administered questionnaire. Results: The highest percentage of responses regarding necessary collaborative activities with multiple professions in supporting hospital discharge were the same for Ns and CMs. The items regarding practice with the highest percentages were “relationship as a team” for Ns, and “user-centered awareness” for CM. While these professionals were willing to share information about their patients’ lives after discharge, the percentage of those explaining their expertise was low. It is thought that collaborative activities focusing on these aspects would lead to more appropriate discharge support.

Enhancing perianal disease management with integrated physical and psychological approaches

This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.

ICU患者置入Power PICC导管特殊异位原因分析

目的:探讨ICU患者置入Power PICC导管后头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的相关因素。方法:回顾性分析2021年9月至2022年9月某三甲医院ICU 520例PICC置管患者,通过胸部X线确定PICC导管头端反折向上至对侧和同侧锁骨下静脉、头臂静脉的患者,分析其特殊异位发生因素。结果:胸部X线结果显示25例患者PICC管头端反折向上异位至对侧和同侧锁骨下静脉、头臂静脉或颈内静脉,异位发生率4.8%,不同静脉置管反折异位发生率相比差异无统计学意义,P>0.05。结论:ICU患者PICC置入发生导管头端反折向上至同侧和对侧锁骨下静脉、头臂静脉等特殊异位的发生因素较多,包括同时留置CVC或血透管、正在滴注或泵入多种药物、PICC管头端异位的隐匿性、导管材质、自身疾病及机械通气等危险因素。

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.

Analysis and management strategies for the low voltage problems of rural power grid based on the distribution network flow calculation method

For a long time, because of the lack of investment capital and enough attentions, the overall constructions of rural power grid were far behind than the urban power grid in Chongqing Jiangbei Power Company. The low voltage problems were highlighted in the rural power grid due to the characteristics of rural power grid. Using the distribution network flow calculation method, we evaluated the low voltage problems of the rural power grid which belongs to Chongqing Jiangbei Power Company. In addition, we collected the data of distribution transformers in electricity consumption peak period. Some practical management strategies were proposed by the analysis and evaluation of potential and appeared low voltage problems.

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.

Power-balancing Instantaneous Optimization Energy Management for a Novel Series-parallel Hybrid Electric Bus

Energy management（EM） is a core technique of hybrid electric bus（HEB） in order to advance fuel economy performance optimization and is unique for the corresponding configuration. There are existing algorithms of control strategy seldom take battery power management into account with international combustion engine power management. In this paper, a type of power-balancing instantaneous optimization（PBIO） energy management control strategy is proposed for a novel series-parallel hybrid electric bus. According to the characteristic of the novel series-parallel architecture, the switching boundary condition between series and parallel mode as well as the control rules of the power-balancing strategy are developed. The equivalent fuel model of battery is implemented and combined with the fuel of engine to constitute the objective function which is to minimize the fuel consumption at each sampled time and to coordinate the power distribution in real-time between the engine and battery. To validate the proposed strategy effective and reasonable, a forward model is built based on Matlab/Simulink for the simulation and the dSPACE autobox is applied to act as a controller for hardware in-the-loop integrated with bench test. Both the results of simulation and hardware-in-the-loop demonstrate that the proposed strategy not only enable to sustain the battery SOC within its operational range and keep the engine operation point locating the peak efficiency region, but also the fuel economy of series-parallel hybrid electric bus（SPHEB） dramatically advanced up to 30.73% via comparing with the prototype bus and a similar improvement for PBIO strategy relative to rule-based strategy, the reduction of fuel consumption is up to 12.38%. The proposed research ensures the algorithm of PBIO is real-time applicability, improves the efficiency of SPHEB system, as well as suite to complicated configuration perfectly.

数据可视化Power BI在职业院校学生管理中的应用

职业院校学生管理是一个重要而复杂的任务,需要学校管理人员的精心组织和有效执行。随着信息技术的发展和校园信息化建设的需求,部分职业院校的学生管理服务系统已初步建成。BI数据可视化可以有效地利用大量的系统数据,为院校管理者提高决策和治理水平提供依据。本文通过对BI数据可视化过程和结构进行分析,比较Power BI与传统型BI的差异,通过对Power BI数据可视化在职业院校学生管理中的应用分析和实践案例,验证数据可视化PowerBI在学生管理中的重要作用。

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power U+0028 CCHP U+0029 with storage systems. Initially, the initiative optimization operation strategy of CCHP system in the cooling season, the heating season and the transition season was formulated. The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency, minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy. Furthermore, the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm. Ultimately, the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution U+0028 TOPSIS U+0029 method. A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method. The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method. The CCHP system has achieved better energy efficiency, environmental protection and economic benefits. © 2014 Chinese Association of Automation.

Optimal Energy Management for Virtual Power Plant with Renewable Generation

The nature of variable and uncertainty from renewable energy sources (RESs) makes them challenging to be integrated into the main grid separately. A Virtual Power Plant (VPP) is proposed to aggregate the capacities of RESs and facilitate the integration and management in a decentralized manner. In this paper, a novel framework for optimal energy management of VPP considering key features such as handling uncertainties with RESs, reducing operating costs and regulating system voltage levels is proposed, and a two-stage stochastic simulation is formulated to address the uncertainties of RESs generation and electricity prices. Simulation result show that the framework can benefit from ensuring the energy balance and system security, as well as reducing the operation costs.

Improving SINR via Joint Beam and Power Management for GEO and LEO Spectrum-Sharing Satellite Communication Systems

In this paper,we investigate a geosynchronous earth orbit(GEO)and low earth orbit(LEO)coexisting satellite communication system.To decrease the interference imposed on the GEO user caused by LEO satellites,we propose a joint beammanagement and power-allocation(JBMPA)scheme to maximize signal-to-interference plus noise ratio(SINR)at the GEO user,whilst maintaining the ongoing wireless links spanning from LEO satellites to their corresponding users.Specifically,we first analyze the overlapping coverage among GEO and LEO satellites,to obtain the LEO-satellite set in which their beams impose interference on the GEO user.Then,considering the traffic of LEO satellites in the obtained set,we design a beam-management method to turn off and switch interference beams of LEO satellites.Finally,we further propose a deep Q-network(DQN)aided power allocation algorithm to allocate the transmit power for the ongoing LEO satellites in the obtained set,whose beams are unable to be managed.Numerical results show that comparing with the traditional fixed beam with power allocation(FBPA)scheme,the proposed JBMPA can achieve a higher SINR and a lower outage probability,whilst guaranteeing the ongoing wireless transmissions of LEO satellites.

Research on Performance Optimization of Liquid Cooling and Composite Phase Change Material Coupling Cooling Thermal Management System for Vehicle Power Battery

The serpentine tube liquid cooling and composite PCM coupled cooling thermal management system is designed for 18650 cylindrical power batteries,with the maximum temperature and temperature difference of the power pack within the optimal temperature operating range as the target.The initial analysis of the battery pack at a 5C discharge rate,the influence of the single cell to cooling tube distance,the number of cooling tubes,inlet coolant temperature,the coolant flow rate,and other factors on the heat dissipation performance of the battery pack,initially determined a reasonable value for each design parameter.A control strategy is used to regulate the inlet flow rate and coolant temperature of the liquid cooling system in order to make full use of the latent heat of the composite PCM and reduce the pump’s energy consumption.The simulation results show that the maximum battery pack temperature of 309.8 K and the temperature difference of 4.6 K between individual cells with the control strategy are in the optimal temperature operating range of the power battery,and the utilization rate of the composite PCM is up to 90%.

Machine Learning Empowered Beam Management for Intelligent Reflecting Surface Assisted MmWave Networks

Recently,intelligent reflecting surface(IRS)assisted mmWave networks are emerging,which bear the potential to address the blockage issue of the millimeter wave(mmWave)communication in a more cost-effective way.In particular,IRS is built by passive and programmable electromagnetic elements that can manipulate the mmWave propagation channel into a more favorable condition that is free of blockage via judicious joint base station(BS)-IRS transmission design.However,the coexistence of IRSs and mmWave BSs complicates the network architecture,and thus poses great challenges for efficient beam management(BM)that is one critical prerequisite for high performance mmWave networks.In this paper,we systematically evaluate the key issues and challenges of BM for IRS-assisted mmWave networks to bring insights into the future network design.Specifically,we carefully classify and discuss the extensibility and limitations of the existing BM of conventional mmWave towards the IRS-assisted new paradigm.Moreover,we propose a novel machine learning empowered BM framework for IRS-assisted networks with representative showcases,which processes environmental and mobility awareness to achieve highly efficient BM with significantly reduced system overhead.Finally,some interesting future directions are also suggested to inspire further researches.

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.

Fuzzy Assessment Method and Its Application to Selecting Project Managers

Open competition is a new form of the assessment of candidates and selection of project managers. This has many merits compared to the traditional administrative method of appointment. This article introduces a method of fuzzy assessment of project manager candidates. Fuzzy assessment unifies objective qualitative and quantitative appraisal and can be used for improving decision-making in the selection process.

Large-Scale Distributed Photovoltaic Power Dispatching and Operation Management Review

Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper analyzes development status, technical requirement and dispatching and operation management situation of distributed PV in Germany and China. Then introduce the preparation of distributed PV dispatching and operation management criterion. Through summarizing the experiences and lessons of large-scale distributed PV development in Germany, it gives advice to the development of distributed PV dispatching and operation management in China.