Optimization of Chiller Loading Problem Using Improved Golden Jackal Optimization Algorithm Leads to Reduction in Energy Consumption

This paper proposes a modified golden jackal optimization(IGJO)algorithm to solve the OCL(which stands for optimal cooling load)problem to minimize energy consumption.In this algorithm,many tools have been developed,such as numerical visualization,local field method,competitive selectionmethod,and iterative strategy.The IGJO algorithm is used to improve the research capabilities of the algorithm in terms of global tuning and rotation speed.In order to fully utilize the effectiveness of the proposed algorithm,three famous examples of OCL problems in basic ventilation systems were studied and compared with some previously published works.The results show that the IGJO algorithm can find solutions equal to or better than other methods.Underpinning these studies is the need to reduce energy consumption in air conditioning systems,which is a critical business and environmental decision.The Optimal Chiller Load(OCL)problem is well-known in the industry.It is the best method of operation for the refrigeration plant to satisfy the requirement of cooling.In order to solve the OCL problem,an improved Golden Jackal optimization algorithm(IGJO)was proposed.The IGJO algorithm consists of a number of parts to improve the global optimization and rotation speed.These studies are intended to address more effectively the issue of OCL,which results in energy savings in air-conditioning systems.The performance of the proposed IGJO algorithm is evaluated,and the results are compared with the results of three known OCL problems in the ventilation system.The results indicate that the IGJO method has the same or better optimization ability as other methods and can improve the energy efficiency of the system’s cold air.

China's energy consumption growth picks up, structure improved

China＇s energy consumption in the first three quarters grew at a faster pace as use of renewable energy posted steady momentum, official data showed Tuesday. Coal used in building materials and the electric, steel and chemical industries accounted for 85 percent of overall coal consumption during the first nine months, data released by the National Energy Administration （NEA） showed. While petroleum consumption remained steady,

Energy-Efficient Clustering Using Optimization with Locust Game Theory

Wireless sensor networks(WSNs)are made up of several sensors located in a specific area and powered by a finite amount of energy to gather environmental data.WSNs use sensor nodes(SNs)to collect and transmit data.However,the power supplied by the sensor network is restricted.Thus,SNs must store energy as often as to extend the lifespan of the network.In the proposed study,effective clustering and longer network lifetimes are achieved using mul-ti-swarm optimization(MSO)and game theory based on locust search(LS-II).In this research,MSO is used to improve the optimum routing,while the LS-II approach is employed to specify the number of cluster heads(CHs)and select the best ones.After the CHs are identified,the other sensor components are allo-cated to the closest CHs to them.A game theory-based energy-efficient clustering approach is applied to WSNs.Here each SN is considered a player in the game.The SN can implement beneficial methods for itself depending on the length of the idle listening time in the active phase and then determine to choose whether or not to rest.The proposed multi-swarm with energy-efficient game theory on locust search(MSGE-LS)efficiently selects CHs,minimizes energy consumption,and improves the lifetime of networks.The findings of this study indicate that the proposed MSGE-LS is an effective method because its result proves that it increases the number of clusters,average energy consumption,lifespan extension,reduction in average packet loss,and end-to-end delay.

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the environment.Designing the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the research.Sensor node clustering is a popular approach for WSN.Moreover,the sensor nodes are grouped to form clusters in a cluster-based WSN environment.The battery performance of the sensor nodes is likewise constrained.As a result,the energy efficiency of WSNs is critical.In specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in WSN.In the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was used.The selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed method.It provides the best routing path and increases the lifetime and energy efficiency of the network.End-to-end delay and packet loss rate have also been improved.The proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor nodes.Compared to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.

基于MSTSO算法的冷水机组负荷分配模型研究

为降低空调系统的运行能耗,优化冷水机组的负荷分配,提出了一种多策略改进的金枪鱼优化算法(MSTSO),引入黄金正弦觅食机制和非线性惯性权重来加强算法对最优解的全局定位能力;通过蜜獾随机搜索策略赋予算法更强的性能以跳出局部最优;利用双向长短期记忆网络(BiLSTM)搭建能效预测模型并对各机组的能效比(COP)进行预测,同时使用MSTSO算法对网络的初始参数进行寻优从而获得最佳训练效果;提出BiLSTM-MSTSO负荷分配模型,对多台冷水机组的部分负荷率(PLR)进行合理分配与优化;实验结果表明,优化后的BiLSTM预测模型拥有更高的预测精度,MSTSO算法相较其他智能优化算法可以减少更多的能耗并最大化提升冷水机组的运行效率;因此BiLSTM-MSTSO智能模型适用于多冷水机组的能耗预测与优化。

基于EnergyPlus的冷水机组能耗评估工具

集中式空调系统的能耗占公共建筑能耗的50%左右,其中冷水机组作为主要能耗部分,其能耗评估是空调系统设计中的必要环节。在工程应用中,常采用COP和IPLV评估冷水机组能效水平,也采用建筑能耗模拟仿真工具进行评估。本文介绍基于建筑能耗模拟仿真软件EnergyPlus开发的冷水机组能耗评估工具CPEAT,可以评估不同气候区内各类型冷水机组在不同控制模式下的全年能耗,供工程设计参考。

基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法

为实现煤矿内所有耗能设备的动态监控,为节能优化措施的提出提供重要依据,进一步贯彻落实国家绿色低碳环保的发展理念,提出基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法。结合自动控制理论和计算机技术,根据分站控制原理,合理划分煤矿内能源消耗设备的类型,并为每个设备配备可编程控制器。通过极大似然估计法构建线性方程,确定各组设备的监测节点位置。利用多种通信协议,在三层网络结构中部署B/S监测架构,从计量终端收集煤矿能耗设备的运行数据。基于免疫多Agent技术构建学习模型,分析并推理接收到的数据信息,实现对煤矿综合能耗的动态监测。结果表明:以不同的能耗设备为测试对象,基于免疫多Agent技术的煤矿综合能耗B/S动态监控方法可以准确地获取全部运行信息,有效实现能耗设备的动态监测,能够全面监控煤矿中所有耗能设备的运行情况,并为其后期运行和管理提供理论依据,具有应用价值。

Path selection and mechanism innovation of improving railway energy efficiency–from foreign experience and Chinese practice

Purpose–Under the dual pressure of resources and environment,many countries have focused on the role of railways in promoting low-carbon development of integrated transportation and of even the whole society.This paper aims to provide a comprehensive study on methods to improve railway energy efficiency in other national railways and achievements made by China’s railways in the past practice,and then to propose ways in which in the future China’s railways could rationally select the path of improving energy efficiency regarding the needs of the nation’s ever-shifting development and carry out the re-engineering for mechanism innovation in energy conservation and emission reduction process.Design/methodology/approach–This paper first studies other national railways that have tried to promote the improvement of railway energy efficiency by the ways of technology,management and structural reconstruction to reduce energy consumption and carbon emissions.Among them,the effect of structural energy conservation and emission reduction has become more prominent.It has become the main energy conservation and emission reduction measure adopted by foreign railway sectors.The practice of energy conservation and emission reduction of railways in various countries has tended to shift from a technical level to a structural one.Findings–Key aspects in improving energy efficiency include re-optimization of energy structure,reinnovation of energy-saving technologies and optimization of transportation organization.Path selection includes continuing to promote electrified railway construction,increasing the use of new and renewable energy sources,and promoting the reform of railway transportation organizations.Originality/value–This paper provides further challenges and research directions in the proposed area and has referential value for the methodologies,approaches for practice in a Chinese context.To achieve the expected goals,relevant supporting policies and measures need to be formulated,including actively guiding integrated transportation toward railway-oriented development,promoting innovation in energy-saving and emission reduction mechanisms and strengthening policy incentives,focusing on improving the energy efficiency of railways through market behavior.At the same time,it is necessary to pay attention to new phenomena in the railway industry for track and analysis.

某酒店制冷机房运行策略优化

对华东地区某酒店制冷机房运行策略进行了优化,利用能耗模拟软件对多种运行方案进行了仿真分析。结果表明:原方案仅对冷水泵采用变频控制,制冷机房能效比为4.62;优化方案1采取传统变频方式,对冷水泵、冷却水泵、冷却塔风机采用变频控制,制冷机房能效比达到5.32,与原方案相比提升了15.1%;优化方案2通过对冷水机组、冷水泵、冷却水泵、冷却塔风机进行优化控制,制冷机房能效比为5.48,与原方案相比能效比提升了18.6%,且每年可减少约79 t碳排放量,节能效果显著。

基于B/S架构的用户用能信息采集系统研究

为了提高用户用能信息采集能力,提出基于B/S架构的用户用能信息采集系统设计方法。通过物联网和RFID标签识别技术,构建用户用能信息采集系统的射频标签信息采集模块,采用B/S架构和总线传输协议实现用户用能信息采集的信息化传输和调度,实现用户用能信息采集。测试结果表明方法进行用户用能信息采集的智能性和准确性较好。

全国能源消费结构低碳化的空间非均衡性及动态演进

剖析中国能源消费结构低碳化趋势、衡量其空间非均衡状态是推进能源革命及绿色发展的关键环节。文章根据2003—2020年我国各省市能源消费的面板数据,利用泰尔指数和空间自相关法,探究全国能源消费结构低碳化的空间非均衡性及动态演进特征。结果显示:1)我国能源消费结构低碳化指数总体呈稳步上升的趋势,由2003年的5.298上升至2020年的5.862;2)全国能源消费结构低碳化分布的空间非均衡性较弱,呈现先升后降态势,即泰尔指数总体呈现先上升后下降发展态势,区域间能源消费结构低碳化的差异对总体差异的影响越来越大;3)全国能源消费结构低碳化存在明显的空间正相关,空间集聚效应现象,且近年来总体空间格局分布变化较小。江浙沪地区始终呈现高高聚集的特征,而西南和华中地区则处于弱弱聚集。根据分析结果,提出构建区域利益共同体,通过技术交流等多种方式互惠互助、合作共赢,共同促进能源低碳化发展;推动产业结构高级化,激发社会创造力和市场活力,破解落后高耗能产业的模式锁定和路径依赖;优化能源产业结构,积极推进能源消费转型等政策建议。

无线传感器网络S-MAC协议能量有效性改进

针对无线传感器网络中节点能量受限的特点,对目前典型的无线传感器网络信道接入协议(S-MAC)的休眠机制进行了改进。改进后的协议(ES-MAC)根据传感/转发事件发生间隔的变化而自适应调整各节点的休眠时长以节省空闲监听的能量消耗,从而延长整个网络的生存时间。仿真结果表明,在传感/转发事件发生间隔较长的情况下,改进后的协议能够很好地工作,并提高了原协议的能量有效性。

基于制冷季逐时能耗模拟的地铁车站冷源方案分析方法

提出了一种综合室外典型年逐时气象参数、列车发车对数、客流量变化等因素,在制冷季逐时负荷基础上进行能耗模拟的冷源方案分析思路。首先建模计算得到地铁车站制冷季逐时空调负荷,然后基于逐时室外气象条件修正冷水机组的实际性能。以某地铁车站公共区为例,对水冷螺杆式冷水机组和水冷涡旋式模块化冷水机组2种空调冷源方案进行了对比。结果显示,虽然水冷螺杆式冷水机组的额定COP高于水冷涡旋式模块化冷水机组,但针对该地铁车站的负荷特点,采用水冷涡旋式模块化冷水机组方案制冷站年能耗比采用水冷螺杆式冷水机组方案低11.6%。

基于B/S架构的高速公路建设能耗统计分析系统设计与开发

高速公路建设项目能源消耗大,利用信息技术对高速公路建设期能源消耗进行统计分析,有助于进行工程统筹安排,提高效率,实现节能减排目的。以河南三淅高速公路为例,采用B/S三层结构设计高速公路能耗统计分析系统,并采用JAVA开发语言,通过Java Server Pages网页技术进行实现。系统能满足高速公路建设、监理、施工单位不同用户要求,实现能耗数据录入、编辑、审核、统计、分析、任务提醒、日志管理等功能,及时准确地反映建设项目能源消耗状况,对合理安排工期、增加投资收益、控制污染排放发挥重要作用。

基于改进DEPSO算法的冷水机组负荷优化方法

针对目前单一优化算法对最优冷水机组负荷(OCL)的求解过程存在收敛性能不佳的问题,提出一种改进的具有差分进化算子的粒子群优化算法(改进DEPSO算法)求解夏季典型日的OCL,并利用k均值聚类算法对系统冷负荷进行分类,以最大限度降低多冷水机组系统的能耗。通过实际案例验证该方法的节能效果和有效性,结果表明,与粒子群优化算法和差分进化算法相比,所提方法能以较少的迭代次数搜索到最小系统能耗值,且获得较优的平均最小系统能耗值。

基于仿真对比的某办公建筑空调系统改造分析

对某办公建筑的老旧空调系统进行改造,比较了冷水机组与多联机2种改造方案,探讨了人员加班情况对系统选择的影响。首先,对建筑改造区域进行了负荷模拟,针对每种方案进行设备选型。然后,对2种方案供冷、供暖季的空调系统能耗进行了仿真和比对,多联机系统能耗更低,投资回收期仅4.6 a。最后,针对不同的加班模式和加班率进行了仿真分析,绘制了能耗-加班率曲线,发现多联机系统更适用于有人员加班情况出现的建筑。当独立办公室加班率为10%时,改造区域多联机系统的供冷季能耗比冷水机组系统低41.7%。

无线传感器网络S-MAC协议的节能改进

无线传感器网络S-MAC协议中,节点之间的同步侦听与睡眠机制使得不需要发送和接收数据的节点过早醒来,参与到侦听信道的活动当中,增加了节点能量的消耗。文章针对这一问题,提出了一种改进方案;通过同步RTS发送的机制,有效地减少了节点的空闲侦听时间,节省了网络能量的消耗;并通过仿真实验证明了该方案的有效性。

工业部门的终端能源消费“S”形模型研究

工业部门作为终端能源消费中三大主要部门之一,对经济发展具有重要作用。本文系统分析了15个发达经济体100多年来工业部门终端能源消费与人口和经济发展(GDP)的关系,发现随着人均GDP的增长,工业部门的人均终端能源消费显现缓慢增长、加速增长、减速增长到零增长或负增长的"S"形轨迹,并可分为高、中、低三个类型。通过重点解剖美、日、德、法和意大利等典型国家工业部门终端能源消费与经济发展的历史,标定了不同类型"S"形曲线的起飞点、转折点和零增长点,讨论了工业部门终端能源消费与能源消费强度、二产比例、城市化率和人均钢铁消费的内在联系,建立了"S"形曲线的一般性数学模型。工业部门终端能源消费与经济发展定量关系的确定对于国家,特别是发展中国家把握工业化过程能源消费趋势、预测能源需求和制定相关能源政策具有重要意义。

WSN中S-MAC协议的能量消耗分析及改进

S-MAC协议是针对无线传感器网络的MAC协议。本文对协议中的节点能量消耗问题进行了详细地分析,从而推导出节点工作时各因素对能量消耗的影响。针对S-MAC的能量节省是以高延迟为代价;网络节点所分配的统一占空比使得传感器网络不能很好的适应网络流量变化的缺陷,提出了节点利用率这个概念。根据节点间利用率不相同的特点,为各节点分配带有不同占空比的周期性侦听机制,并采用动态分配占空比的方法来适应网络的变化。结果显示:通过这些改进达到了能量消耗和延迟的平衡,从而使S-MAC进一步得到优化。