Fuel-optimal trajectory design using solar electric propulsion under power constraints and performance degradation

The fuel-optimal transfer trajectories using solar electric propulsion are designed considering the power constraints and solar array performance degradation.Three different performance degradation models including linear,positive and negative exponential degradations are used in the analysis of three typical rendezvous missions including Apophis,Venus and Ceres,respectively.The optimal control problem is formulated using the calculus of variations and Pontryagin’s maximum principle,which leads to a bang-bang control that is solved by indirect method combined with a homotopic technique.In demonstrating the effects of the power constraints and solar array performance degradation on the power budget and fuel consumption,the time histories of the power profile and the fuel consumptions are compared for the three missions.This study indicates that it is necessary to consider the power constraints and solar array performance degradation for the SEP-based low-thrust trajectory design,espacially for long-duration outbound flights.

Power allocation in cooperative MIMO systems under individual power constraints

allocation （PA） plays an important role in capacity improvement for cooperative multiple-input multipleoutput （Co-MIMO） systems. Many contributions consider a total power constraint （TPC） on the sum of transmit power from all nodes in addressing PA problem. However, in practical implementations, each transmit node is equipped with its own power amplifier and is limited by individual power constraint （IPC）. Hence these PA methods under TPC are not realizable in practical systems. Meanwhile, the PA problem under IPC is essential, but it has not been studied. This paper extends the traditional non-cooperative water-filling PA algorithm to IPC-based Co-MIMO systems. Moreover, the PA matrix is derived based on the compound channel matrix from all the cooperative nodes to the user. Therefore, the cooperative gain of the IPC-based Co-MIMO systems is fully exploited, and further the maximal instantaneous capacity is achieved. Numerical simulations validate that, under the same IPC conditions, the proposed PA scheme considerably outperforms the non-cooperative water-filling PA and uniform PA design in terms of ergodic capacity.

Joint Power Control and Spectrum Allocation for Cognitive Radio with QoS Constraint

Spectrum sharing with quality of service (QoS) requirement and power constraint on cognitive users is studied. The objective is to maximize the system throughput. This problem is modeled as a mixed integer nonlinear programming problem and then transformed to a continuous nonlinear programming problem through eliminating integer variables. We propose the joint power control and spectrum allocation algorithm based on particle swarm optimization to obtain the global optimal solution. Simulation results show that the proposed method can achieve higher system throughput and spectrum utilization under the constraints of transmit power and QoS requirement.

OPTIMAL POWER ALLOCATION FOR COGNITIVE RADIO UNDER INTERFERENCE OUTAGE CONSTRAINT

Cognitive radio is able to share the spectrum with primary licensed user,which greatly improves the spectrum efficiency.We study the optimal power allocation for cognitive radio to maximize its ergodic capacity under interference outage constraint.An optimal power allocation scheme for the secondary user with complete channel state information is proposed and its approxi-mation is presented in closed form in Rayleigh fading channels.When the complete channel state in-formation is not available,a more practical transmitter-side joint access ratio and transmit power constraint is proposed.The new constraint guarantees the same impact on interference outage prob-ability at primary user receiver.Both the optimal power allocation and transmit rate under the new constraint are presented in closed form.Simulation results evaluate the performance of proposed power allocation schemes and verify our analysis.

Taking into Account of Functional Constraints in Optimization of Modes of Power Systems by Genetic Algorithms

The development of the capabilities of computational tools has created up new possibilities for the effective use of a number of classical mathematical methods and algorithms for solving many important problems in the power engineering. In particular, a set of algorithms are developed to optimize the modes of electric power systems based on genetic algorithms. At the same time, the issues of taking into account functional constraints in solving such problems by genetic algorithms need to be improved. In accordance with it in this article the problems of taking into account of different constraints in optimization of modes of power systems using genetic algorithms are considered. The algorithm of optimization by genetic algorithm taking into account of functional constraints in forms of equality and inequality by penalty functions is proposed. The results of research of proposed algorithm’s efficiency in example of optimization of mode of power system with 8 buses, 4 thermal power plants and 3 transmission lines with controlled power flow are presented.

基于Power图求解容量限制P-中值问题

针对稠密需求下连续域上的容量P-中值问题,提出基于质心的容量限制Power图(CCCPD)理论,对连续P-中值问题进行近似建模,并加快计算过程。扩展Balzer试位法构造Power图,施加质心限制满足P-中值要求,施加容量限制满足需求密度下的容量要求。实验结果表明所提算法可快速得到近似可行解,同Alper Murata方法相比,计算效率高;同质心容量限制Voronoi图(CCCVT)相比,具有容量限制精确度高等优点,并能适应各种复杂需求密度函数。

New Optimal Power Allocation for Bidirectional Communications in Cognitive Relay Network Using Analog Network Coding

Cognitive radio and cooperative communication can greatly improve the spectrum efficiency in wireless communications.We study a cognitive radio network where two secondary source terminals exchange their information with the assistance of a relay node under interference power constraints.In order to enhance the transmit rate and maintain fairness between two source terminals,a practical 2-phase analog network coding protocol is adopted and its optimal power allocation algorithm is proposed.Numerical results verify the superiority of the proposed algorithm over the conventional direct transmission protocol and 4-phase amplify-and-forward relay protocol.

容量限制Power图快速计算算法（英文）

与Voronoi图不同,Power图有着精确限容的特性,可应用于众多领域.在普通Power图上,通过给每个站点增加权重来添加容量限制约束,即得到容量限制Power图.现有容量限制Power图的生成算法时间复杂度高,速度较慢.本文首先对Power图权值对于容量的单调性进行理论证明,然后提出了一种Power图权值的快速计算方法,相比于现有的试位法,能大幅提升容量限制Power图的生成性能.实验结果表明,文中算法具有速度快,精确度高,便于计算,密度适应性强等优点.

An Energy-Efficient Wireless Power Transmission-Based Forest Fire Detection System

Compared with the traditional techniques of forest fires detection,wireless sensor network(WSN)is a very promising green technology in detecting efficiently the wildfires.However,the power constraint of sensor nodes is one of the main design limitations of WSNs,which leads to limited operation time of nodes and late fire detection.In the past years,wireless power transfer(WPT)technology has been known as a proper solution to prolong the operation time of sensor nodes.In WPT-based mechanisms,wireless mobile chargers(WMC)are utilized to recharge the batteries of sensor nodes wirelessly.Likewise,the energy of WMC is provided using energy-harvesting or energy-scavenging techniques with employing huge,and expensive devices.However,the high price of energy-harvesting devices hinders the use of this technology in large and dense networks,as such networks require multiple WMCs to improve the quality of service to the sensor nodes.To solve this problem,multiple power banks can be employed instead of utilizing WMCs.Furthermore,the long waiting time of critical sensor nodes located outside the charging range of the energy transmitters is another limitation of the previous works.However,the sensor nodes are equipped with radio frequency(RF)technology,which allows them to exchange energy wirelessly.Consequently,critical sensor nodes located outside the charging range of the WMC can easily receive energy from neighboring nodes.Therefore,in this paper,an energy-efficient and cost-effective wireless power transmission(ECWPT)scheme is presented to improve the network lifetime and performance in forest fire detection-based systems.Simulation results exhibit that ECWPT scheme achieves improved network performance in terms of computational time(12.6%);network throughput(60.7%);data delivery ratio(20.9%);and network overhead(35%)as compared to previous related schemes.In conclusion,the proposed scheme significantly improves network energy efficiency for WSN.

Solution of Combined Heat and Power Economic Dispatch Problem Using Direct Optimization Algorithm

This paper presents the solution to the combined heat and power economic dispatch problem using a direct solution algorithm for constrained optimization problems. With the potential of Combined Heat and Power (CHP) production to increase the efficiency of power and heat generation simultaneously having been researched and established, the increasing penetration of CHP systems, and determination of economic dispatch of power and heat assumes higher relevance. The Combined Heat and Power Economic Dispatch (CHPED) problem is a demanding optimization problem as both constraints and objective functions can be non-linear and non-convex. This paper presents an explicit formula developed for computing the system-wide incremental costs corresponding with optimal dispatch. The circumvention of the use of iterative search schemes for this crucial step is the innovation inherent in the proposed dispatch procedure. The feasible operating region of the CHP unit three is taken into account in the proposed CHPED problem model, whereas the optimal dispatch of power/heat outputs of CHP unit is determined using the direct Lagrange multiplier solution algorithm. The proposed algorithm is applied to a test system with four units and results are provided.

Solution of Combined Heat and Power Economic Dispatch Problem Using Genetic Algorithm

This research proposes a synergistic meta-heuristic algorithm for solving the extreme operational complications of combined heat and power economic dispatch problem towards the advantageous economic outcomes on the cost of generation. The combined heat and power (CHP) is a system that provides electricity and thermal energy concurrently. For its extraordinary efficiency and significant emission reduction, it is considered a promising energy prospect. The broad application of combined heat and power units requires the joint dispatch of power and heating systems, in which the modelling of combined heat and power units plays a vital role. The present research employs the genetic optimization algorithm to evaluate the cost function, heat and power dispatch values encountered in a system with simple cycle cogeneration unit and quadratic cost function. The system was first modeled to determine the various parameters of combined heat and power units towards solving its economic dispatch problem directly. In order for modelling to be done, a general structure of combined heat and power must be defined. The test system considered consists of four units: two conventional power units, one combined heat and power unit and one heat-only unit. The algorithm was applied to test system while taking into account the power and heat units, bounds of the units and feasible operation region of cogeneration unit. Output decision variables of 4-unit test systems plus cost function from Genetic Algorithm (GA), was determined using appropriate codes. The proposed algorithm produced a well spread and diverse optimal solution and also converged reasonably to the actual optimal solution in 51 iterations. The result obtained compared favourably with that obtained with the direct solution algorithm discussed in a previous paper. We conclude that the genetic algorithm is quite efficient in dealing with non-convex and constrained combined heat and power economic dispatch problem.

Evaluation of Shunt Reactive Power Compensation Effect on ATC Using Linear Methods

Most power transfer studies involve contingencies and multi pattern scenarios that often can only be performed in reasonable time with the use of linear methods. In these works, the effect of reactive power flows in line loading is neglected while formulating the problem for ATC （available transfer capability） calculations. This paper presents the determination of shunt reactive power compensation in the presence of FACTS （flexible AC transmission system） devices like： SSSC （static synchronous series compensator） and UPFC （unified power flow controller） for enhancement of power transfer capability of a power system incorporating the reactive power flows in ATC calculations. In doing so, redistribution of power flow takes place and therefore improves ATC of the system. Studies on a sample 5-bus power system model are carried out to illustrate the effect of shunt compensation along with line flow control.

水电富集区域电量送出能力提升的源储协同优化运行方法

针对可再生能源出力的强波动性、间歇性导致电力外送断面出现短时间尺度重过载、清洁能源送出消纳困难等问题,提出了水电富集区域电量送出能力提升的源储协同优化运行方法,该方法定义了衡量断面外送电量的量化指标,以系统发电成本最小、断面输出电量最大、储能消耗电量最小为目标,建立多目标优化模型,通过求解帕累托前沿,结合熵权双基点法,得到折中最优点。对我国某省级电网算例的仿真结果表明,该方法可有效通过水电、火电和储能的协同优化运行提升断面外送可再生能源的发电量,在保证系统安全稳定运行的前提下提升了可再生能源的消纳率。

考虑电力网络约束的工业园区虚拟电厂调控边界求解方法

构建以新能源为主体的新型电力系统,亟须挖掘负荷侧灵活调节资源参与电网调控。含电解铝、矿热炉等高耗能负荷的工业园区具备良好的调控潜力,但是考虑园区内部电力网络约束,其精确调控边界求解面临着变量维数高、约束非线性的难题,现有方法不能较好地兼顾计算效率和精度。对此,文中将上述问题抽象为高维非线性状态空间在P-Q耦合平面的投影问题:分别建立考虑工业园区安全运行线性化和非线性约束的调控边界投影求解模型,采用一种新颖的高维状态空间投影算法,通过顶点“搜索-映射”的两步式求解过程,得到工业园区型虚拟电厂调控边界的精确投影。算例结果表明,采用所提方法求解的调控边界可由线性不等式组完全表征,与现有调度系统完全兼容,结合与叠加柔性资源调控能力和传统采样方法的对比,验证了该方法的可行性以及高求解精度和效率。

地方金融监管权力法治化的反思与重塑

地方金融监管权力的法治化塑造,不仅旨在保证地方金融监管权力来源的法定,更关注法治对地方金融监管权力运行进行制约与监督的规范效用,而这需要借助职权法定、行政自制和理性制衡三者协同完成。为回应中央与地方金融监管权责失衡之实践异化,地方金融监管权力法治化的核心要义便是地方金融监管权责的对等化设计,具体是以职权与职责在量上的实质均衡为内核,来完成主体维度中央和地方关系的均衡处理与事项维度规则制定和监管执法的分项设计。当然,地方金融监管权力法治化的实践展开,应当借助地方金融监管权责事项的清单化管理展开,即分别按照“以权定责”和“以责定权”的逻辑来设置权力清单与责任清单各自不同的要素构成,并在“属地管理”观念的统一指引下完成“以块统条”和“以条带块”管理模式的差别化设计。

基于绿电和自愿减排量交易的园区低碳电力运营优化

为保证园区电力运营经济性,提高清洁电能的使用比例,文章提出了一种基于绿电和自愿减排量交易的园区低碳电力运营优化模型。该模型综合考虑了绿电和火电的购电成本、光伏发电成本及自愿减排量收益,以总运营成本最小为目标函数,结合随机概率约束,分中长期、日前和实时三阶段对绿电、火电电量以及光伏发电量进行优化。以南京市某企业园区的数据为基础,在自愿减排量价格合理的前提下,该优化模型可小幅降低园区总运营成本,并且显著提高了清洁电能的使用比例和园区应对扰动的能力。另外,就自愿减排量价格以及置信度取值对优化结果的影响进行了分析。

马克思廉价政府思想的理论考察与当代价值

廉政建设是推进全面从严治党、党的自我革命的有力保障。马克思在《法兰西内战》中总结了廉价政府的一系列思想,阐释了廉政机制保障,提出了约束贪腐的罢免制度,明确了揭露腐败的监督机制,揭示了规范权力运行的法律制度等。马克思廉价政府思想在本质上要求廉政建设必须具有自我革命的实践性、整合重构的系统性、管党治党的权威性。当代中国廉政建设实践对马克思廉价政府思想的创新发展取得突出成效,以建设党内法规体系保证党对廉政建设的坚强领导,以改革纪检监察体制保证党的执政地位长期巩固,以健全党和国家监督体系保证党的自我革命不断深化。马克思廉价政府思想的当代价值要求我们必须持续加强党对廉政建设的坚强领导和自我革命的政治使命,持续强化廉政建设的科学性和时代变迁的适应性,持续探索增强廉政建设执行力的内在动因和运行规律,持续提升中国特色社会主义廉政建设成果和治理效能。

计及实时最大功率约束的高速磁浮列车再生制动能量存储利用

针对高速磁浮列车牵引供电系统结构及运行规则特殊性导致再生制动能量无法主动利用、能量回馈方式对局域网电压影响大的问题,在对高速磁浮列车牵引供电系统结构和能量流动机理进行分析的基础上,给出基于地面式超级电容储能的高速磁浮列车再生制动能量回收利用系统拓扑结构;考虑高速磁浮列车再生制动能量回收系统容量配置小、超级电容工作电压变化明显的特性,以高效回收再生制动能量为目标,将储能系统实时的可运行最大功率作为约束功率,制定相应的能量管理策略,实现系统不同工况下的能量管理,并通过分层控制策略实现整个再生制动能量利用系统的高效运行。通过仿真验证所提再生制动能量回收利用系统及控制策略的有效性,结果表明:所提方案可使高速磁浮列车牵引能耗降低21.83%;与储能系统采用固定功率约束的功率分配方式相比,再生制动能量利用率提高了11.9%。