梯级水电站群多电网调峰调度及电力跨省区协调分配方法

针对特大型梯级水电站群短期调度需兼顾多个电网调峰的复杂应用需求,以溪洛渡、向家坝梯级水电站为研究对象,提出一种水电站群跨区多电网调峰调度和电力跨省区协调分配方法。从厂网协调的角度出发,以受端电网余荷均方差最小为目标,构建梯级水电站多电网调峰调度模型。在给定电网受电量、电站调峰容量及高压直流输电限额约束下,利用网间负荷互补特性,通过随机搜索算法对面临电网受电计划进行启发式搜索,并逐步迭代调整各电网受电计划,获得水电出力在各受端电网的最优分配方案。仿真结果表明,所提方法制定的溪—向梯级水电站出力网间分配计划能均衡响应各受端电网调峰需求,充分发挥梯级发电能力及调峰潜力,有效解决梯级水电站群多电网调峰调度问题。

多电网调峰负荷分配问题的目标函数选取与求解

大电网平台下,利用优质电源协调多个省级电网间差异负荷对缓解中国电力系统日益严重的调峰压力具有非常突出作用。针对现有网际协调方式和优化方法调峰效果不理想尤其局部时段范围内余荷频繁波动问题,提出一种基于电网理想余荷过程(简称理想解)的调峰建模方法。该方法采用N近邻平滑和分段平滑两种方式均化多个相邻时段余荷以构造理想解,并将计算余荷与理想解偏差最小作为优化目标,以尽可能平滑各电网局部负荷波动。采用邻域搜索算法进行模型求解,通过可变步长动态改变可行搜索区域,以改善收敛速度和结果质量。华东电网直调水火电系统的仿真调度实例表明,所提模型与算法能切实协调上海、江苏、浙江、安徽四省(市)的峰值负荷差异,得到较以往优化建模方法更合理的日调度运行结果。

一种单站多电网短期启发式调峰方法

单一水电站向多个电网送电时,由于受电电网负荷量级以及负荷特性的不同,一般很难制定出既满足电站运行约束又同时满足多电网送电量比例要求的电站出力计划。为此,从发电侧及需求侧的角度出发,提出一种单站多电网短期启发式调峰方法,以受电电网剩余负荷在保证平坦的情况下最小为目标建立多电网调峰模型,通过将电网余荷最值作为启发式信息对电站出力过程进行逐步修正,制定既能满足约束条件又能保证剩余负荷平稳的电站出力计划及网间电力分配方案。将所提方法运用于华中电网下辖二滩水电站多电网送电计划编制中,实例表明该方法在兼顾多电网负荷特性的同时能够充分发挥水电站的调峰容量效益,有效解决了单一水电站向多电网送电时的短期调峰问题。

考虑机组组合的梯级水电站跨省区多电网调峰优化调度方法

在电力大规模跨区消纳背景下,一些大型水电站群需要向多个电网送电、响应多个电网调峰需求,甚至存在单站不同机组分别向不同电网送电的情况。考虑水电站运行约束、多电网调峰需求及跨省区输电限制,提出了一种考虑机组组合的梯级水电站多电网调峰优化调度方法。该方法首先构建了水电站短期出力计算及网间电力分配的混合整数二次规划模型,采用迭代寻优方法计算梯级水电站的理想出力过程;之后以实际出力计划与理想过程相差最小为目标,结合约束简化策略构建梯级水电站短期优化调度模型,对各电站实际出力计划进行求解,并以此为基础,计算梯级水电站机组组合结果与各电网受电过程。基于溪洛渡—向家坝梯级水电站多电网调峰的仿真结果表明,所提方法可满足跨省区送电水电站复杂运行约束,有效响应各受端电网的高峰负荷需求,具有显著的调峰效果。

兼顾多电网调峰与水电消纳的跨流域梯级水电站调度方法

中国云南省的电源结构以水电为主,水电消纳问题异常突出,且云南水电外送的受端调峰压力巨大。为充分挖掘云南电网"西电东送"通道潜力,最大限度消纳云南水电,同时响应多电网的调峰需求,文中构建了兼顾多电网调峰与水电消纳的跨流域梯级水电站调度的混合整数线性规划模型。模型采用目标权重法将多电网调峰问题转化成单目标问题,并通过调整各电网余荷距平绝对值的平均值权重,使得目标兼顾了多电网的调峰需求与水电消纳。同时,通过引入特殊顺序集约束,对最小持续时间约束提出了一种简易的线性化方法,此方法可应用于其他同类型的约束中。最后,以澜沧江干流与金沙江干流的18座水电站为例,验证了模型的可行性与有效性,结果表明所提方法可满足多电网调峰与水电消纳的需求。

基于多电网负荷趋势的梯级水电站群中长期联合优化调度

针对传统梯级水电站群联合优化调度中未考虑梯级送电负荷与所送电网负荷趋势相匹配的问题,考虑多电网负荷趋势,提出了一种基于逐步优化算法的多电网负荷过程拟合误差最小与中长期发电量最大的耦合模型。实例计算结果表明,该模型对梯级发电量及其与多电网负荷趋势的拟合均取得了较好的效果,可提高梯级水电站发电计划的实用性。

兼顾本地与直流受端电网调峰需求的水电站群短期优化调度模型

面对巨型水电站群高压直流送端电网和受端电网日益严峻的调峰压力,建立了一种兼顾本地与直流受端电网调峰需求的梯级水电站群短期优化调度模型。模型以多电网剩余负荷最大值最小为目标,考虑常规梯级水电站群水力、电力约束,以及复杂高压直流输电线路运行约束,并引入直流线路与水电站之间耦合运行约束。在模型求解阶段,引入辅助变量将目标函数、水电运行约束、直流运行约束线性化,并采用大M法对直流线路与水电站之间双向区间耦合约束进行线性化,将原模型转换为混合整数线性规划模型。以中国西南地区某巨型水电站群冬季和夏季典型日为实例研究,结果表明:送端电网负荷峰谷差降幅高达100%,受端电网负荷峰谷差降幅分别达28.1%和31.6%。所提模型能够利用高压直流输电线路共享水电灵活性,有效实现多电网调峰,并保证直流输电线路运行在安全区间,可以为巨型梯级水电站群短期多电网调峰提供参考和借鉴。

多级协同模式下华中电网大规模水电站群跨网调峰调度研究

根据华中区域大规模电站群跨省电力输送运行实际,针对水电站群优化调度需兼顾多电网调峰需求、电站出力计划编制复杂问题,提出了一种多级协同模式(MLCM)下大规模水电站群跨网调峰调度方法。以各受端省级电网余荷均方差最小为目标建立电站群联合跨网调峰调度模型,通过流域梯级电站群层级排序获得电站优化次序,简化电站间复杂耦合关系,将约束处理耦合至电站出力网间二次分配过程中,逐步迭代调整各受电网受电计划,获得满足多电网调峰需求的电站出力计划与电网受电过程。所提方法通过华中区域三葛梯级、清江梯级、沅水梯级水电站群调度模拟得到验证,应用结果显示电站出力计划在兼顾多电网调峰需求的同时充分发挥了水电站群联合调峰容量效益,具有工程实用价值。

复杂需求下巨型水电站跨省交易电量曲线分解方法

西南巨型水电站参与电力市场涉及多省、多品种、多时间尺度等多维电量曲线分解难题,给水电市场化运行带来很大挑战。该文依托溪洛渡右岸电站实际工程,考虑电网调峰与企业效益复杂需求,提出巨型水电站月度电量曲线分解多目标协调方法。以余荷均方差最小构建多电网调峰目标,利用多品种差异电价和峰平谷分段市场电价构建发电效益目标,引入理想点法实现目标分级进而将多目标优化转换为一系列差异约束边界的单目标问题;采用分段线性技术处理非线性水力约束、三角剖分技术处理电站出力特性曲线,利用混合整数线性规划(mixed integer linear programming,MILP)方法实现模型高效求解。采用溪右电站月度电量交易申报实际数据进行验证分析。结果表明,该文模型可以得到合理的月度电量分日、分时、分省、分品种的发电曲线过程,并通过两个实例分析不同来水和计划电量对调峰与收益的影响,发现汛期较枯期影响更大,且计划电量比例是协调调峰和发电收益的重要因素。

雅砻江下游梯级水电站联合优化调度研究

为了合理规划雅砻江下游梯级水电站多电网输电能力,应用梯级水电站水库蓄放水判别规则,建立了面向多电网供电的梯级水电站联合优化调度模型和算法。通过实例研究,该模型能够在考虑不同水电站送电电网设计负荷特性的基础上,充分发挥雅砻江下游梯级水电站发电规模效益,为面向多电网供电的雅砻江下游梯级水电站联合优化调度提供了解决办法。

巨型水电站跨省调峰多目标优化方法

结合西南干流跨省送电工程实际,提出巨型水电站跨省调峰多目标优化方法,构建了短期多电网调峰模型,基于正、负理想点采用目标贴近度策略高效处理多目标问题,耦合出力和流量两类约束优化策略提出自适应遗传算法进行多目标问题高效求解,以便快速得到多电网调峰Pareto解集。以溪洛渡水电站送电两个省级电网实际问题进行验证,结果显示本方法能够有效响应多个电网的差异化负荷调节需求,利用多目标Pareto解集能够明晰不同电网间的调峰影响关系,有利于快速得到合理实用的跨省送电方案。

Three-dimensional forward modeling of DC resistivity using the aggregation-based algebraic multigrid method

To speed up three-dimensional （3D） DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method （AGMG）. We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner （AGMG-CG） to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling （3DDCXH）. In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.

Incorporating Network Coding into TCP Grounded on Network Utility Maximization in Multi-Radio Multi-Channel Wireless Mesh Networks

A new approach, named TCP-I2NC, is proposed to improve the interaction between network coding and TCP and to maximize the network utility in interference-free multi-radio multi-channel wireless mesh networks. It is grounded on a Network Utility Maxmization (NUM) formulation which can be decomposed into a rate control problem and a packet scheduling problem. The solutions to these two problems perform resource allocation among different flows. Simulations demonstrate that TCP-I2NC results in a significant throughput gain and a small delay jitter. Network resource is fairly allocated via the solution to the NUM problem and the whole system also runs stably. Moreover, TCP-I2NC is compatible with traditional TCP variants.

Radio ＂Echo of Moscow＂ （Ekho Moskvy） as a Multimedia Project

The paper deals the popular news-talk radio station ＂Echo of Moscow＂ which is one of the most interesting and successful one in Moscow FM range. It provides thorough analysis of different previous and nowadays programs and web projects in comparison with main multimedia sphere trends. A particular attention is paid to ＂Echo of Moscow＂ web page as multimedia portal strongly packed with different functions such as its integration with social nets.

Distributed Spectrum Sharing Scheme for Multiuser Orthogonal Frequency-Division Multiplexing Cognitive Radio Networks

This paper presents a novel spec- trum sharing design aiming at optimising the performance of a Multiuser Orthogonal Freq- uency-Division Multiplexing （MU-OFDM） Co- gnitive Radio Network （CRN） that consists of multiple secondary Transmitter-Receiver （Tx-Rx） pairs. For most MU-OFDM systems, the Exc- lusive Subchannel Assignment （ESA） is an efficient resource allocation method. Noneth- eless, it is inappropriate for the network consi- dered in this paper, because subchannels shar- ing among secondary Tx-Rx pairs can further improve the system performance. We investi- gate the Weighted Sum Rate （WSR） maximi- zation problem under the Shared Subchannel Assignment （SSA）, where each subchannel is shared by multiple secondary Tx-Rx pairs. With Lagrangian duality technique, we decompose the original resource allocation problem into sev- eral sub-problems on each subchannel and pro- pose a duality-based suhchannel sharing ap- proach. For practical realisation in the cogni- tive systems without central control entity, a distributed duality-based WSR maximization scheme is presented. Simulation results mani- fest that the proposed scheme achieves sig- nificantly better performance than ESA duality scheme.

Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties

This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.

Optimal Power Allocation for Multiuser Underlay Cognitive Radio Networks under QoS and Interference Temperature Constraints

Power allocation is an important issue for Cognitive Radio Networks(CRNs),since it needs to consider the Quality of Service(QoS) for Secondary Users(SUs) while maintaining the interference power to Primary User(PU) below the Interference Temperature(IT) threshold. In this paper, based on Euclidean projection, we propose a distributed power control algorithm with QoS requirements to minimise the total power consumption of SUs under the time-varying channel scenario. Considering the maximum transmit power constraints and the minimum signal to interference plus noise constraints for each SU, together with the IT constraints for each PU, the power allocation problem is transformed into a convex optimization problem without auxiliary variables, and is solved by the Lagrangian dual method with less information exchange.Simulation results demonstrate that the proposed scheme is superior to the Iterative Water-Filling Algorithm(IWFA).

Extracting invariable fault features of rotating machines with multi-ICA networks

This paper proposes novel multi-layer neural networks based on Independent Component Analysis for feature extraction of fault modes. By the use of ICA, invariable features embedded in multi-channel vibration measurements under different operating conditions (rotating speed and/or load) can be captured together.Thus, stable MLP classifiers insensitive to the variation of operation conditions are constructed. The successful results achieved by selected experiments indicate great potential of ICA in health condition monitoring of rotating machines.

On Channel Assignment for Multicast in Multi-Radio Multi-Channel Wireless Mesh Networks:A Survey

The major challenge faced by wireless mesh networks is the capacity reduction caused by interference,and interference can be reduced or even eliminated through appropriate channel assignment.This article presents a comprehensive survey of channel assignment schemes for multicast in multi-radio multi-channel wireless mesh networks.We analyze the state-of-the-art channel assignment schemes for multicast and provide comprehensive taxonomy of the latest work.In general,we classify the channel assignment schemes for multicast into two types,that is,sequential multicast routing and channel assignment(SMRCA)and joint multicast routing and channel assignment(JMRCA).Detailed review of channel assignment schemes in each category is provided.Possible future research directions and corresponding solutions are also explored to motivate research interests in the field of channel assignment for multicast in wireless mesh networks.

Optimization of Multiband Spectrum Sensing for Cognitive Radio Networks under Sensing Capability Constrains

This paper addresses the problem of joint optimization of subchannel selection and spectrum sensing time for multiband cognitive radio networks under the sensing capability constrains. In particular, we construct a multiband spectrum sensing framework, and derive the probabilities of detection and false alarm taking the different subchannel gain into account. Furthermore, we formulate the multi- band sensing as a two-parameter optimization prob- lem under the sensing capability constrains and guaranteeing the QoS of the secondary user. Moreover, we develop a semi-analytical optimization scheme to achieve the optimal solution.