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.

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.

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%.

Energy Management System with Power Offering Strategy for a Microgrid Integrated VPP

In the context of both the Virtual Power Plant (VPP) and microgrid(MG), the Energy Management System (EMS) is a key decision-maker forintegrating Distributed renewable Energy Resources (DERs) efficiently. TheEMS is regarded as a strong enabler of providing the optimized schedulingcontrol in operation and management of usage of disperse DERs and RenewableEnergy reSources (RES) such as a small-size wind-turbine (WT) andphotovoltaic (PV) energies. The main objective to be pursued by the EMSis the minimization of the overall operating cost of the MG integrated VPPnetwork. However, the minimization of the power peaks is a new objective andopen issue to a well-functional EMS, along with the maximization of profitin the energy market. Thus, both objectives have to be taken into accountat the same time. Thus, this paper proposes the EMS application incorporatingpower offering strategy applying a nature-inspired algorithm such asParticle Swarm Optimization (PSO) algorithm, in order to find the optimalsolution of the objective function in the context of the overall operating cost,the coordination of DERs, and the energy losses in a MG integrated VPPnetwork. For a fair DERs coordination with minimized power fluctuationsin the power flow, the power offering strategies with an active power controland re-distribution are proposed. Simulation results show that the proposedMG integrated VPP model with PSO-based EMS employing EgalitarianreDistribution (ED) power offering strategy is most feasible option for theoverall operating cost of VPP revenue. The total operating cost of the proposedEMS with ED strategy is 40.98$ compared to 432.8$ of MGs only withoutEMS. It is concluded that each MGs in the proposed VPP model intelligentlyparticipates in energy trading market compliant with the objective function,to minimize the overall cost and the power fluctuation.

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。

Development of Energy Management System for Micro Grid Operation

The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy consumption.The aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential buildings.The proposed micro-grid model includes four power generators:solar power,wind power,Electricity Board(EB)source,and a Diesel Generator(DG)set,with solar and wind power performing as major sources and the EB supply and DG set serving as backup sources.The core issue in direct current to alternate current conversion is harmonics distortion,a five-stage multilevel inverter is employed with the assistance of an intelligent control system is simulated and the optimum system configuration is estimated to reduce harmonics and improve the power quality.The monthly demand for residential buildings is 13-15 Megawatts.So,almost 433 Kilo-Watts(KW)of electricity is required every day,and if it is used for 8 h per day,50-60 KW of electricity is needed per hour.The overall micro-grid model’s operation and performance are established using MATLAB/SIMULINK software,and simulation results are provided.The simulation results show that the developed system is both cost-effective and environment friendly resulting in yearly cost reductions.

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.

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.

Conceptual Strategy for Mitigating the Risk of Hydrogen as an Internal Hazard in Case of Severe Accidents at Nuclear Power Plant Considering Existing Risks and Uncertainties Associated with the Use of Traditional Strategies

Hydrogen challenge mitigation stands as one of the main objectives in the management of severe accidents at Nuclear Power Plants (NPPs). Key strategies for hydrogen control include atmospheric inertization and hydrogen removal with Passive Autocatalytic Recombiners (PARs) being a commonly accepted approach. However, an examination of PAR operation specificity reveals potential inefficiencies and reliability issues in certain severe accident scenarios. Moreover, during the in-vessel stage of severe accident development, in some severe accident scenarios PARs can unexpectedly become a source of hydrogen detonation. The effectiveness of hydrogen removal systems depends on various factors, including the chosen strategies, severe accident scenarios, reactor building design, and other influencing factors. Consequently, a comprehensive hydrogen mitigation strategy must effectively incorporate a combination of strategies rather than be based on one strategy, taking into consideration the probabilistic risks and uncertainties associated with the implementation of PARs or other traditional methods. In response to these considerations, within the framework of this research it has been suggested a conceptual strategy to mitigate the hydrogen challenge during the in-vessel stage of severe accident development.

Design of Power Communication Data Network Management System and Implementation of Data Acquisition Module

The power communication network is a separate network from the power grid whose primary purpose is to ensure the power grid's safe operation.This paper expounds the composition of the comprehensive network management architecture of the power communication data network and the implementation of the data acquisition module in the network management system through theoretical analysis,for the reference of relevant personnel,in order to better promote the collection of power grid communication network data.

Power BI在移民信息管理中的应用研究

信息技术的应用是提高水利工程移民信息化水平的重要手段,针对现有移民信息管理系统灵活性和通用性低的问题,分析了微软Power BI系列软件实现移民信息管理的可行性。以山东省老岚水库移民项目为例,使用该软件依次快捷完成移民信息的收集、整理和分析工作,并设计出交互式可视化界面,从多个维度展示和查询各类移民信息以及实现移民数据的多端实时共享。研究表明:运用Power BI系列软件虽然在结合地理信息方面仍存在不足,但能够以较低的使用难度和投入成本完成移民信息管理及可视化工作,提高工作效率。验证了其在移民信息管理方面的实用性和适用性,具备一定的推广价值。

基于Power BI的医院智能化运营管理平台构建研究

本文以H医院为例,探讨基于Power BI的智能化运营管理平台构建。H医院引入Power BI构建集成运营管理平台,整合病案首页、临床路径和Drg费用管理等关键业务功能,提供战略层、经营层和业务层可视化报告以支持用户做出更精准的管理与决策。实例表明,智能化运营管理平台的构建解决了传统运营管理的难点,成为医院提升运营效益和服务质量的有利工具,展现信息化建设在推动医院管理现代化方面的巨大潜力和价值。

"Emperor's Power Far Away from the Countryside"and"Town in Charge of Village Affairs":The Extreme Grass-roots Management System is Not Conducive to the Healthy Development of the Countryside

This paper compares the two different rural management methods of"emperor’s power far away from the countryside"and"town in charge of village affairs",which shows that the extreme grass-roots management system is not conducive to rural development.This paper also points out that rural development needs to find a road of sustainable development in line with its own characteristics,which is the fundamental shortcut to change poverty and become rich for a long time.

基于PMS 3.0系统的设备运检大数据精益化管理

为适应电网内外部形势,解决传统设备(资产)运维精益管理系统(PMS 2.0)存在支撑能力不足等问题,以保障设备资产精益管理高效运营为核心,构建新一代设备资产精益管理系统(PMS 3.0)。通过PMS 3.0系统建设和应用过程中的经验,详细阐述了其建设的背景意义、实施方法、具体应用以及实践成效。推进“技术架构、安全策略、应用协同”三个升级,实现“设备、作业、管理、协同”四个数字化,有效提升了巡视效率,缩短停电时间,减少负荷损失,提升百姓的生活质量。

基于Power BI的螺栓拧紧数据智能管理系统

为保证整车装配的安全和质量,需要采用大量带监控拧紧工具完成整车零部件的装配工作,并借助拧紧数据完成拧紧工作的日常管理。然而,该过程产生的数据量庞大,传统方式采用人工统计分析拧紧数据,存在统计效率低下、数据处理工作繁琐、可视化效果不佳等问题。为了解决该问题,文章基于智能分析软件Power BI对拧紧数据进行建模处理,并搭建螺栓拧紧数据智能管理系统,实现拧紧数据的自动化管理和分析。该系统包含了海量拧紧数据的自动加载、自动统计和自动生成可视化报表等功能,业务人员可以随时访问系统查询报表,大幅提升了现场拧紧管理的工作效率。

LMP Congestion Management Using Enhanced STF-LODF in Deregulated Power System

Nowadays electricity market industry is become a major impact on power system for privatization and deregulation of power in global wise. As per the limitation of the transmission system, the complexity arises and the supply fact will be with demand at the time of balancing. The congestion of the power system is occurring based on the transmission limits of the power desire and amount for operating the system. In order to avoid transmission line congestion, enhanced STF-LODF method is proposed. It shows the regulated line transmission flow with generating units by implementing renewable energy resources (RER) based on enhanced STF-LODF in power systems. It avoids the congestion of transmission line frequently in the power system and manages price based on pricing and sensitivity approach, and also manages optimal location of congestion transmission and instability issues of voltage. The congestion management of Locational Marginal Pricing (LMP) is performed with minimum line loss, less cost, line flow, better sensitivity and better performances in optimal power flow and control flow. The efficiency of the proposed power system is analyzed and verified by the simulation results of tested IEEE 14 bus system.

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

Load Management Scheme Using Air Conditioning Electric Power Consumption and Photovoltaic Power System Generation

In the last few decades, in the world and also in the European Union, considerable resources had been invested in the rapid development of renewable energy sources and distributed generation in general. At the same time, power consumption is continuously increasing, and consumers are becoming more complex, which ultimately requires new investments in the distribution network. Concept of smart grids is generally accepted as a possible solution. Smart grid is a concept with many elements, where monitoring and control of every element in the chain of production, transmission, distribution and final consumption enable much more efficient delivery and use of electricity. One of the elements of smart grid efficiency is the ability of real-time demand-supply balancing. This balancing is carried out by monitoring of consumption and redistribution of electricity among individual end users, according to their needs. The aim of this paper is creating algorithm for real-time load management using power measurements. Algorithm for real-time load management at the ETFOS （Faculty of Electrical Engineering in Osijek）, Croatia is created based on measurements of photovoltaic power plant production, the power consumption of air conditioning system and the faculty building total electricity consumption. Expected result of real-time re-dispatching of air conditioners consumption, depending on the level of electricity production in photovoltaic power plant is decreasing peak demand of the faculty.