基于地区电网经济运行的无功综合效益优化

采用地区电网无功综合效益优化模型，从经济运行角度，兼顾地区电网有功网损最小和因数达到要求值，使电网的年运行费用达到最小。优化算法将仿射变换内点法与简化分枝定界法（内点－分枝定界法）综合应用于优化过程中，计算结果表明它是一种有效的无功优化算法。     

基于粗糙集理论的多目标电网规划最优化模型

为综合解决电网规划中经济性与可靠性问题，提出以供电方投资开发成本最小和基于风险评估的负荷缺电风险成本最小为目标的优化模型。应用粗糙集理论分析每个目标函数的约束度，以确定每个目标函数在优化模型中的权值。采用改进混合遗传模拟退火算法来求解该模型下的多目标电网规划问题，并采用19节点的电网扩展规划算例验证了该模型的有效性。 关键词：；；；     

电力市场环境下的输电网扩展规划

电网规划的主要目标是尽可能经济地确保可靠的满足要求的电力供应.在电力市场环境下,提出一个优化的输电网扩展规划.在满足潮流和安全约束的条件下,使电力不足期望值、投资费用最小,使效益成本最大,采用非支配遗传算法解决多目标优化问题,在风险分析中,用最大最小后悔值确定最优方案.新的方法用最少的投资达到最大化投资效益,增加了输电公司的竞争优势.在改进的RBTS中取得了好的效果.     

电压无功优化控制系统在地区电网中的应用

介绍了地区电网电压无功优化控制系统的结构、技术特点及功能。系统针对电力系统无功优化调度分层、分区的实际特点,按分层控制结构设计,其优化算法以网损最小为目标函数,考虑电压质量、控制代价等约束条件。系统在徐州地区电网的实际应用中达到降低运行劳动强度、提高电压合格率、降低网损等效果。     

基于免疫算法的地区电网无功综合效益优化

电力系统无功优化分析中引入的免疫算法（IA）是根据生物免疫原理提出的,具有抗体的多样性、促进性、抑制性以及记忆等功能,是一种全局优化的概率搜索算法。将该算法应用到地区电网的无功综合效益分析中,在兼顾地区电网有功网损最小和功率因数达到要求值的同时,可使电网的无功综合效益达到最优。为此,基于Matlab7．0编制了无功优化程序,并与传统的遗传算法（GA）和Broden非线性规划法进行了比较,结果表明,该算法能加快计算速度,为地区电网经济运行带来可观的经济效益。     

地区电网故障恢复的实用化研究

地区电网的故障恢复是一个多目标、多约束、复杂的优化问题,其优化的效率是其能否在线应用的关键。对地区电网故障恢复的实用化进行了研究,构建了一种用于故障恢复处理的电网分析模型,提出了一种面向在线应用的改进型最小生成树故障恢复处理算法。该算法在对复杂地区电网进行模型化的基础,根据模型中子系统当前属性和即时路径权值,动态调整最小树的搜索范围和生长方向,从而实现最优恢复路径的快速搜索。实际电网故障恢复事例已证明,本算法能够实现地区电网故障最优恢复路径的快速搜索。     

地区电网故障恢复的实用化研究

地区电网的故障恢复是一个多目标、多约束、复杂的优化问题,其优化的效率是其能否在线应用的关键.对地区电网故障恢复的实用化进行了研究,构建了一种用于故障恢复处理的电网分析模型,提出了一种面向在线应用的改进型最小生成树故障恢复处理算法.该算法在对复杂地区电网进行模型化的基础,根据模型中子系统当前属性和即时路径权值,动态调整最小树的搜索范围和生长方向,从而实现最优恢复路径的快速搜索.实际电网故障恢复事例已证明,本算法能够实现地区电网故障最优恢复路径的快速搜索.     

衢州电网并联补偿器优化运行的离散规划

用离散规划方法探讨了无功补偿设备分级调节的优化运行，优化计算采用“截值法”。文中以衢州电网并联电容器优化投切为例，以补偿节电最大为目标函数，通过利用地区的ＳＣＡＤＡ系统可做到实时在线计算，达到并联电容器的优化运行。     

全寿命周期成本及其在电网规划中的应用

在电网规划中应用全寿命周期成本（Life-CycleCost）管理理念可以使电力企业获得更大更长远的经济效益。首先阐述了电网全寿命周期成本概念及各子成本含义;然后在综合考虑电网安全可靠性与经济性基础上,建立了以电网全寿命周期成本最小为目标函数的电网规划数学模型,介绍了模型求解方法以及在电网规划中的具体应用流程;最后以华东某地区电网规划应用为例,说明了本研究工作的有效性。     

最优状态检修方案的选择和设备合理更新

运用马尔可夫分析模型分析设备各种状态下检修期望值，使期望值达到最小，从而制定最优检修计划，取代现在固定时间和工期的检修方式，使电网的运行方式更加灵活，提高电网的经济效益。利用运筹学中的更新论来讨论设备合理更新的最佳时间，为电网的规划和远期运行方式的制定提供必要的理论依据。     

A real and reactive power control approach for battery energystorage system

A power control method using the power flow concept is described. The authors formulate a new and general control equation for the real-time control of a battery energy storage system (BESS). A control strategy for a BESS to operate in a real power mode and a reactive power mode is discussed. Simulations for a demand-side BESS are presented, together with experiments on operating system set-up in a power laboratory using a real time control implementation. The real and reactive power control of a BESS were tested using a 10 kVA/30 kWh laboratory system. The results illustrate that the proposed method is effective and easy     

Optimal operation of large-scale power systems

A method for optimal operation of large-scale power systems is presented that it is similar to the one utilized by the Houston Lighting and Power Company. The main objective is to minimize the system fuel costs while maintaining an acceptable system performance in terms of limits on generator real and reactive power outputs, transformer tap settings, and bus voltage levels. Minimizing the fuel costs of such large-scale systems enhances the performance of optimal real power generator allocation and of optimal power flow that results in an economic dispatch. To handle large-scale systems of this nature, the problem is decomposed into a real and a reactive power optimization problem. The control variables are generator real power outputs for the real power optimization problem and generator reactive power outputs, compensating capacitors, and transformer tap settings for the reactive power optimization. The gradient projection method (GPM) is utilized to solve the optimization problems. It is an iterative procedure for finding an extremum of a function of several constraint variables without using penalty functions or Lagrange multipliers. Mathematical models are developed to represent the sensitivity relationships between dependent and control variables for both real and reactive-power optimization procedures and thus eliminate the use of B-coefficients     

Security-constrained optimal rescheduling of real power usingHopfield neural network

A new method for security-constrained corrective rescheduling of real power using the Hopfield neural network is presented. The proposed method is based on solution of a set of differential equations obtained from transformation of an energy function. Results from this work are compared with the results from a method based on dual linear programming formulation of the optimal corrective rescheduling. The minimum deviations in real power generations and loads at buses are combined to form the objective function for optimization. Inclusion of inequality constraints on active line flow limits and equality constraint on real power generation load balance assures a solution representing a secure system. Transmission losses are also taken into account in the constraint function     

Optimal real and reactive power dispatch

This paper presents a method for optimal real and reactive power dispatch for the economic operation of power systems. As in other methods, the problem is decomposed into a P-optimization module and a Q-optimization module, but in this method both modules use the same generation cost objective function. The control variables are generator real power outputs for the real power module; and generator reactive power outputs, shunt capacitors/reactors, and transformer tap settings for the reactive power module. The constraints are the operating limits of the control variables, power line flows, and bus voltages.The optimization problem is solved using the gradient projection method (GPM) which is used for the first time in the power systems study. Among other advantages, the GPM allows the use of functional constraints without the need for penalty functions or Lagrange multipliers.Mathematical models are developed to represent the sensitivity relationships between dependent and control variables for both (real and reactive power) optimization modules, and thus eliminate the use of B-coefficients. Results of two test systems are presented and compared with conventional methods.     

基于灰色－辨识模型的风电功率短期预测

为了准确预测风电机组的输出功率,针对实际风场,给出一种基于灰色GM(1,1)模型和辨识模型的风电功率预测建模方法,采用残差修正的方法对风速进行预测,得出准确的风速预测序列。同时为了提高风电功率预测的精度,引入FIR-MA迭代辨识模型,从分段函数的角度对风电场实际风速-风电功率曲线进行拟合,取得合适的FIR-MA模型。利用该模型对额定容量为850 kW的风电机组进行建模,采用平均绝对误差和均方根误差,以及单点误差作为评价指标,与风电场的实测数据进行比较分析。仿真结果表明,基于灰色-辨识模型的风电机组输出功率预测方法是有效和实用的,该模型能够很好地预测风电机组的实时输出功率,从而提高风电场输出功率预测的精确性。     

优选电网规划方案的灰色关联法

研究电网规划的经济性和可靠性具有重大的现实意义,在简要介绍了电网规划的两个阶段的基础上,针对优选电网规划方案进行了研究,提出了一种新的基于灰色关联法的电网规划方案优选方法,从经济性和技术性上全面考虑了影响电网规划的重要因素。以一个实际电网接入系统规划设计为例说明了所提出的新方法的有效性,结果表明该方法简单并且可以快速地优选出最优的电网规划方案,对电力系统的设计和规划人员起到一定的辅助作用。     

以GPS为基础的电力系统实时网损计算研究

要利用实时数据进行网损计算,需要解决实时采集数据不全的问题、数据中的 异地采集的数据同时 问题,舍此不能完成网损的实时计算。本文则旨在阐述解决上述问题的途径。通过接口程序,电网运行参数直接由历史数据库中读取,并利用快速ＰＱ分解状态估计法对这些原始数据进行加工,继而计算出准确的电网损耗,并说明了如何利用全球卫星定位系统（ＧＰＳ）保证数据的同时性。文中对实现实时网损计算的《安徽省２２０ＫＶ主网网损在线     

发电厂高压厂用电系统中性点接地方式探讨

分析了高压厂用电系统中性点的几种接地方式 ,结合工程实践 ,提出了高压厂用电系统中性点应采用电阻接地方式 ,并介绍了改进的中电阻接地方案 ,在电厂的应用表明其优点和效果是明显的。     

交流励磁发电机运行及控制原理

详细分析了交流励磁发电机内部的基本电磁关系，有功、无功的调节，并提出了在同步坐标轴系下，实现有功、无功解耦控制的新方法。本文为交流励磁发电机的设计及其励磁控制的建立提供了理论依据。     

Achieving more efficient control of the power output of power units through the use of differentiation in the boiler controller regulating steam pressure upstream of the turbine

Different versions of systems for automatic closed-loop control of the power output of power units are analyzed. A new version of the automatic power control system is proposed together with a method for tuning it. Results from model studies and tests of the proposed automatic power control system structure at a real plant are presented.