最小化旁瓣的MIMO雷达发射方向图优化算法

为了获得低旁瓣的MIMO雷达发射方向图,该文提出一种新的最小化峰值旁瓣或积分旁瓣的MIMO雷达方向图优化算法.由于最小化峰值旁瓣或积分旁瓣的优化问题为非凸问题,该算法通过两步来得到此非凸优化问题的全局最优解.第1步通过对发射总功率的约束进行松弛,将原问题转变为一个凸优化问题,第2步则将第1步得到的解进行尺度变换使其满足发射总功率的约束,从而得到原问题的全局最优解.仿真实验表明了该算法相比于已有算法可以获得更低的峰值旁瓣或更低的积分旁瓣.     

异步I/O连接算法的峰值功率建模

峰值功率是影响数据中心能效的一个重要因素.本文提出一种功率感知数据库系统中连接算法的峰值功率估算方法,非运行时峰值功率的估算的挑战在于没有运行时的系统信息作为模型的输入.为克服估算困难,提出使用CPU密集度作为CPU功耗指示量,理论上分析了异步I/O连接算法在峰值功率发生阶段的特性,通过模拟连接算法峰值功率发生阶段算法行为来估算该阶段最大CPU密集度,通过CPU密集度与CPU功率的内在联系建立异步I/O连接算法的峰值功率预测模型.实验对数据库系统中采用异步I/O机制的四个连接算法时模型准确性进行了验证,结果表明所提预测方法具有较好的预测准确性,平均相对误差低于7%.     

协作异构网络中的用户接入与功率控制联合优化

本文研究协作异构网络下行传输中的用户接入和功率控制问题。考虑多基站采用协作传输来回避小区间干扰,在满足用户数据率需求、单基站功率约束、以及给定每个用户最多接入基站个数的限制下,最小化所有基站的总发射功率。该问题属于包含0/1变量和连续变量的组合优化问题,其全局最优解可以通过遍历搜索得到,但会导致很高的计算复杂度。为了降低复杂度,本文提出了一种基于几何规划的用户接入和功率控制联合优化方法。所提出的方法首先将问题中的0/1变量表示为连续函数,进而将得到的优化问题转化为几何规划问题并进行求解。仿真结果表明,相比于现有的用户接入最近基站方法、用户接入信号最强基站方法、以及偏移接收能量最大方法,所提出的方法能够有效地平衡网络中各小区负载,因而可以支持更高的用户数据率需求,在相同的用户数据率需求下能够大幅降低系统的总发射功率。      

云计算数据中心可扩展服务器的能耗管理与优化

最近几年来,伴随着计算机规模的不断扩大,云计算数据中心可扩展服务器的能耗管理已经成为计算机领域较为突出的问题,其严重的限制着云计算的发展。科学合理的资源配置和云计算数据任务调度是可以有效的去降低云计算系统空闲能耗与执行能耗的,从而在一定程度上实现云计算数据中心扩展服务器能耗优化的管理。文中主要是针对云计算书籍中心可扩展服务器的能耗管理与优化相关问题进行详细的分析,并通过相关设计要来提出针对降低能耗的有效措施,在支持DVFS的相关技术能耗特征上,提出相应优化措施。通过转移高负载,经转化高负载主机成为低负载主机,从而在一定程度上去让云计算数据中心可扩展服务器能耗得到优化管理。     

基于QoS保证的负载均衡频谱决策算法

针对不同无线网络间频谱资源利用率不均衡的问题,在IEEE 1900.4标准的框架下提出了基于服务质量(QoS)保证的负载均衡算法,使得认知终端可以通过频谱决策动态地接入不同的无线接入网频段,从而提高频谱利用效率。该算法以网络吞吐量的优化为目标,在资源约束和QoS保证的条件下,通过简化算法而减少开销。仿真结果表明,基于QoS保证的负载均衡频谱决策算法较之传统的基于信噪比(SNR)的频谱接入算法能够使网络的吞吐量得到大幅的提升。     

基于CSP的能耗高效云计算资源调度模型与算法

利用约束满足问题对异构云数据中心的能耗优化资源调度问题建模,通过求解建立的约束模型可以获得能耗最优的资源分配方式,并在此基础上提出了能耗优化的资源分配算法dynamicpower (DY)。与已有的算法MinPM、FFD、BFD相比,算法DY考虑了资源的异构性,能够降低云数据中心物理服务器的能耗。最后,利用Choco实现了提出的算法DY,并将DY与MinPM、FFD、BFD进行实验比较,实验结果表明,提出的算法在能耗上有明显优势。     

基于mean-variance的服务集群负载均衡方法

大量并发请求任务进行分配时,负载调度机制是通过最小化响应时间及最大化节点利用率实现网络中节点的负载均衡,在基于遗传算法的负载均衡算法中,适应度函数设计对服务集群负载均衡效率产生重要的影响.对此提出了一种基于mean-variance的服务集群负载均衡方法对适应度函数进行优化,采用投资组合选择模型mean-variance进行最小化响应时间,以得到每个服务器资源利用率的权重,从而获得最优的分配组合,进而提高适应度函数的准确性和有效性.在不同服务环境下与其他模型进行比较,仿真结果表明,本文的负载均衡算法在节点利用率和响应时间方面使服务集群得到了更好的均衡.     

通信电源配置方法优化对降低运营成本的探讨

文章从通信电源配置方法入手,结合实际通信设备负载特性,指出＂最大功耗＂的不合理性,并引入了＂平均功耗＂概念,进行了配置优化,从而减少了基本建设费用CAPEX（CAPital Expenditure）和运维费用OPEX（OPeration EX-penditure）。这种方法同样适用于UPS和太阳能电源等动力设备。     

宽带稀布线阵的多约束优化设计

针对有阵列孔径、单元数、最小和最大单元约束的宽带稀布直线阵的综合问题,提出一种基于目标向量映射的差分进化算法。通过引入目标向量与需要布阵单元间距之间的映射关系,使单元间距的多约束转化为非约束优化问题,从根本上消除了优化过程中的不可行解,减小了布阵空间,降低了优化算法的计算量。以改善稀布线阵峰值旁瓣电平为目的进行仿真,仿真实验结果表明,稀布阵可以在给定的工作频段内有效的抑制阵列方向图的副瓣,能比现有方法处理更多的约束条件且算法具有好的收敛性和稳健性。     

基于EVM约束的预留子载波峰均比抑制

传统预留子载波(Tone Reservation, TR)技术要求预留的子载波与数据子载波正交,占据的带宽受限,因而其降低峰值平均功率比(Peak-to-Average Power Ratio, PAPR)能力有限。提出了一种基于误差适量幅度(Error Vector Magnitude, EVM)约束的TR算法,将传统的预留子载波扩展至数据子载波生成峰值消除信号,从而大幅度降低峰值功率。基于系统误码率的考虑,在优化问题中加入数据子载波上会出现的最大EVM约束,采用凹凸过程(Concave-convex Procedure, CCCP)优化算法求解提出的优化问题。仿真结果表明,所提算法在发送端峰均比改善5.6 dB的同时,接收端解调性能仅损失1 dB。     

基于微网并网的智能电网用户用电福利研究

考虑需求侧响应的微网并网运行机制能够引导用户合理用电,对研究智能电网用户用电福利具有重要意义。综合光伏、风能发电的不稳定性,提出微网并网运行机制下需求侧响应策略,以微网运行成本最小和需求侧用电效用最大为目标,建立了考虑需求侧响应的微网并网运行福利模型。仿真结果表明所建立的模型可达到用户最大用电福利,且有利于削峰填谷,降低供电压力,提升用户参与建设微网的积极性。     

An Optimal Power Scheduling Method Applied in Home Energy Management System Based on Demand Response

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real‐time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost‐effective way possible. In our research, to avoid the high peak‐to‐average ratio (PAR) of power, we combine the real‐time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.     

Whither metering?

Privatisation of the electricity industry has been enacted, with the stated aim of bringing an improved customer service at lower cost through competition and greater choice. Developments in electronics and communications have meant the development of improved electricity meters which show the cost of electricity at that instant and so give the customers an incentive to reduce their demand at times of peak load     

移动性感知的边缘服务迁移策略

针对移动边缘计算网络中由于用户位置动态变化而导致边缘服务器间负载不均衡、用户服务质量降低的问题,提出了一种移动性感知的边缘服务迁移算法。首先,以最小化用户服务请求感知时延为目标,将优化问题建模为混合整数非线性规划问题。其次,基于Lyapunov优化方法将时延优化问题解耦为边缘服务迁移子问题与无线接入子问题。再次,提出快速边缘决策算法求解出给定无线接入策略情况下最优的资源分配与边缘服务迁移方案。最后,提出异步最佳响应算法迭代出最优无线接入策略。仿真结果表明,与现有服务迁移策略相比较,所提算法能够在保证服务迁移成本稳定的情况下降低用户服务请求的感知时延。     

Cold Thermal Storage and Peak Load Reduction for Office Buildings in Saudi Arabia

This paper involves the investigations of the chilled water and ice cold thermal storage technologies along with the associated operating strategies for the air conditioning (AC) systems of the typical office buildings in Saudi Arabia, so as to reduce the electricity energy consumption during the peak load periods. In Saudi Arabia, the extensive use of AC for indoor cooling in offices composes a large proportion of the annual peak electricity demand. The very high temperatures over long summer periods, extending from May to October, and the low cost of energy are the key factors in the wide and extensive use of air conditioners in the kingdom. This intense cooling load adds up to the requirement increase in the capacity of power plants, which makes them under utilized during the off-peak periods. Thermal energy storage techniques are one of the effective demand-side energy management methods. Systems with cold storage shifts all or part of the electricity requirement from peak hours to off-peak hours to reduce demand charges and/or take advantage of off-peak rates. The investigations reveal that the cold thermal energy storage techniques are effective from both technical and economic perspectives in the reduction of energy consumption in the buildings during peak periods.     

The timing of EV recharging and its effect on utilities

Electric vehicles (EV's) represent an important future load on the electric utility system which, if properly managed, could increase power plant utilization and reduce the average cost of generating electricity. A future EV population of 7.5 million is addressed, together with its characteristics, vehicle use, consequent recharging loads, and the impact of EV's on electric utilities in terms of the generation of electric power, fuel use, and costs. The impact on utilities will depend in part on when the vehicles are recharged. If the price of electricity is uniform throughout the day, recharging is likely to begin when vehicles are parked at home. Most of the recharging would then occur during late afternoon and early evening hours when other demands for electricity are high. In the year 2000, peak electricity demand would increase by 5700 MW, and oil- and gas-fired power plants would generate 39 percent of the recharge power. Marginal generating costs would average 7.6 cents/kWh in 1982 dollars. If electricity were priced by time of day, recharging could shift to late night hours when the other demands for electricity are low. The peak demand would increase by only 400 MW; 27 percent of the power would come from oil and gas, and marginal generating costs would average only 5.1 cents/kWh, some 25 percent less than the marginal cost of the system load without EV's. The fuels to recharge EV's were found to vary from one region of the country to the next. Utilities in the northeast would use the most oil and gas for recharging (more than 75 percent), while those in the central part of the country would use the least.     

基于分时电价和用户侧储能的配电网调度优化策略

针对分布式电源接入及负荷波动引起配电网线路损耗增加的问题,文中提出将分时电价机制协同用户侧储能参与配电网的优化运行模型。基于分时电价建立用户负荷响应模型,构建以用户日用电成本、配电网网损最小为目标函数的配电网运行优化模型。采用评价函数法将多目标转化成单目标,并在传统遗传算法中引入模拟退火Metropolis准则对用户侧储能充放电策略寻优。仿真结果证明了文中所提策略能有效降低配电网网损及用户用电成本,所提算法寻优速度较快,收敛性能较好。     

基于需求响应的风电-抽水蓄能系统调度模型

针对大规模风电并网影响电网稳定运行的问题,基于日前用户侧电力负荷预测和实时电价预测,文中提出了一种电网吸纳风能的新模型。以最小化风电—抽水蓄能联合系统发电成本为目标,在目标求解过程中确定最佳自弹性系数和互弹性系数,运用基于实时电价的需求价格来弹性引导电力用户以实现负荷转移。考虑到用户侧电价弹性限制的约束,该方法采用遗传优化算法编程求解。仿真结果表明,需求侧资源主动参与优化调度可降低负荷峰谷差,利于系统稳定运行,并且可以减少发电成本,提高联合系统经济性。     

一种峰值功耗约束下的SoC蚁群测试调度算法

基于扫描链技术的SoC芯片测试可产生比正常使用模式下更大的功耗,这将会对器件可靠性产生不利影响,故在测试时需要将芯片测试功耗控制在允许峰值功耗之下.文中采用蚁群优化思路设计SoC测试调度算法,用于在峰值功耗和TAM总线最大宽度约束下降低SoC测试时间.实验结果表明,本方法优于先前已发表的相关方法.     

Power Optimization Strategy Considering Electric Vehicle in Home Energy Management System

With the development of smart grid, residents have the opportunity to schedule their household appliances (HA) for the purpose of reducing electricity expenses and alleviating the pressure of the smart grid. In this paper, we introduce the structure of home energy management system (EMS) and then propose a power optimization strategy based on household load model and electric vehicle (EV) model for home power usage. In this strategy, the electric vehicles are charged when the price is low, and otherwise, are discharged. By adopting this combined system model under the time-of-use electricity price (TOUP), the proposed scheduling strategy would effectively minimize the electricity cost and reduce the pressure of the smart grid at the same time. Finally, simulation experiments are carried out to show the feasibility of the proposed strategy. The results show that crossover genetic particle swarm optimization algorithm has better convergence properties than traditional particle swarm algorithm and better adaptability than genetic algorithm.