基于多代理方法的配电网故障应急抢修调度

配电网故障应急抢修调度作为电网应急管理系统的重要组成部分,可以为应急管理提供辅助决策支持作用。为此,从当前配电网应急抢修资源配置情况出发,建立了考虑抢修资源分配以及多抢修小队协作机制的配电网故障应急抢修联合优化模型,并结合黑板模式提出了抢修调度多代理方法,设计了由初始层、适应性测度优化层、抢修预案优化层组成的黑板信息处理模式,可在配电网发生多处故障后快速给出抢修资源分组方案及应急抢修预案,以减少停电经济损失。仿真算例验证了该方法的有效性。     

考虑电源车协同调度的配电网应急抢修研究

配电网抢修恢复是灾后电力供应保障能力的关键,为提升配电网抢修恢复效率,本文针对配电网多重故障情况下电源车和抢修队伍的协调优化调度进行研究。考虑抢修队伍的抢修时间和转移时间,基于负荷价值构建应急抢修路径优化模型,提出应急电源车转移策略矩阵,在满足电源车转移时间和孤立网络功率平衡的条件下,以停电损失最小为优化目标,通过离散二进制粒子群优化算法对两个模型进行协同求解,得到最佳抢修恢复策略。最后,在IEEE33节点系统上验证了所提方法的合理性和有效性。     

含分布式电源的配电网灾后分阶段抢修策略

针对灾后配电网故障抢修需优先保证重要负荷供电的实际情况,建立了含分布式电源(DG)的配电网灾后多小队分阶段抢修策略的优化模型,DG通过形成微网、孤岛运行及时恢复部分负荷的供电。定义设备故障经济损失特征值,用以保证故障抢修的优先级,同时将联络开关当作虚拟故障,利用其倒闸操作以及应急发电车的临时供电配合小队抢修,提高抢修效率。采用改进的离散细菌群体趋药性算法(DBCC)优化,快速得到抢修方案。算例结果证明了所提抢修策略优化模型以及智能优化算法的有效性和正确性。     

含分布式电源的配电网多故障抢修与恢复协调优化策略

针对含分布式电源(DG)的配电网发生多故障时的快速故障抢修和供电恢复问题,根据动态规划原理,建立了含DG的配电网多故障分阶段、分层的抢修与恢复协调优化模型。在紧急抢修与恢复阶段,以负荷恢复价值最大和综合经济损失最小分别作为内、外层优化目标;在抢修与恢复网架阶段,以网损最小和抢修时间最短分别作为内、外层优化目标,得到最优抢修顺序和供电恢复方案。针对内、外层模型的不同特点,分别采用了改进蚁群算法和离散化处理的细菌群体趋药性(DBCC)算法进行模型求解。同时,在抢修与恢复过程中,利用DG孤岛、可控负荷联盟及应急发电车的动态调度优先恢复重要负荷的供电,并采用馈线等效法及故障等效法来简化求解流程。以改进的IEEE 69节点系统为例,验证了所述策略的可行性和有效性。     

基于改进惯性权重粒子群算法的抢修小组快速调配策略

为减少电网抢修人员的调度时间以及提高电网的抢修效率,从前期保障角度建立了基于最短距离的抢修小组驻地选择模型;为解决后期多点故障发生后的调度问题,建立了基于最小维修时间的抢修小组调度模型。通过引入动态调整的惯性权重对粒子群算法（particle swarm optimization,PSO）进行改进,使算法的局部收敛性和全局收敛性均有所提高。同时针对旅行商（traveling salesman problem,TSP）问题,增强了算法解决高维度、顺序优化问题的能力。某城市50节点算例的仿真研究表明,所提方法能够准确有效地确定抢修小组驻地位置,当电网发生多处故障后能够迅速高效地确定应急抢修顺序方案、减小抢修工作调配时间,从而降低了因停电所造成的损失。     

计及交通流量动态变化的配电网灾后修复多时间断面优化策略

针对极端灾害下交通流量的动态变化特性对配电网故障修复过程的影响,在电网与交通网耦合的背景下,计及移动式和固定式2类应急恢复资源与故障抢修间的协调调度,提出了配电网灾后故障修复多时间断面优化策略。首先,采用元胞传输模型建立了交通网络模型,预测了抢修小队和移动式储能车的行驶时间。其次,建立了以负荷削减量与恢复资源调度成本最小为目标,故障设备的抢修顺序和恢复资源的调度计划为决策变量的混合整数线性规划模型,并采用多时间断面优化方法求解。此外,提出了一种网架动态重构方法,通过增加虚拟根节点与各失电节点构成一个虚拟孤岛,并随网架改变动态添加和删减该孤岛中的节点数目,保证了整个配电网始终能够满足辐射状约束,提高了算法对故障场景的适应性。最后,采用算例仿真验证了所提方法提升配电网韧性的有效性。     

基于图模一体化的配电网多点故障抢修调度辅助平台设计

为了提升配电网多点故障抢修调度自动化水平，设计一种基于图模一体化的配电网多点故障抢修调度辅助平台。依据图模一体化理论，使用C/S与B/S相结合的方式设计由数据层、图模一体化平台和应用功能层组成的配电网多点故障抢修调度辅助平台。结果表明：平台为用户提供的配电网单馈线图和动画告警等功能信息全面清晰，可有效缩短配电网抢修调度耗时，抢修调度应急预案具备较好的完整性和针对性，三维监控效果较好。可见平台的实际应用性较强、应用效果好，值得推广和应用。可有效缩短配电网多点故障抢修调度耗时。     

基于改进人工蜂群算法的SVG综合补偿容量优化研究

基于SVG的三相不平衡和无功补偿综合治理可以有效提高低压配电网电能质量。针对SVG补偿容量的动态分配问题,提出了基于改进人工蜂群算法的SVG补偿容量优化配置方法。首先提出基于补偿度的SVG容量动态分配优化模型;然后引入改进的Tent混沌映射序列提高传统人工蜂群算法的收敛性能,并通过改进的人工蜂群算法求解最优SVG容量分配方案,实时调整三相不平衡和无功的补偿度;最后通过Simulink仿真验证所提方法的合理性和有效性。结果表明所提出的基于改进人工蜂群算法的SVG容量动态分配控制方法可以有效综合治理配电网的三相不平衡和无功补偿问题。     

基于改进离散多目标BCC算法的配电网灾后抢修策略

根据配电网的实际情况,建立了配电网突发多处故障情况下的故障抢修和故障恢复相结合的多目标优化模型,将模型中的开关操作变量作为虚拟故障点处理并与抢修控制变量有机结合,考虑了一种多队协同抢修的恢复策略.在多目标细菌群体趋药性(BCC)算法的基础上引入区间归位方案,改善了多目标BCC算法解决离散域问题的性能,同时引入局部更新机...     

基于省地县一体化调度运行管理系统的配电网抢修信息管理

基于省地县一体化调度运行管理系统,设计开发了配电网故障抢修信息管理系统。充分分析了该平台的技术架构,研究了省地县故障抢修纵深调度的业务协同技术和大规模系统的准实时数据共享技术,实现了省地县纵向故障抢修信息的准实时同步及故障抢修与横向系统间的准实时数据同步。同时,研究了多维度数据可视化建模技术,实现了全省业务范围内多维度故障抢修数据的多样化同步展示。该系统能实现配电网故障抢修的纵深调度和抢修实时跟踪,提升故障异常应急响应速度,简化抢修管理工作,提高配电网故障的抢修工作效率。     

Emergency rush repair task scheduling of distribution networks in large-scale blackouts

This paper focuses on the emergency rush-repair task scheduling of distribution networks in power grid emergencies. As there are many characteristics in distribution network emergency rush-repair such as large number of rush repair points, diverse but with limited repair resources and urgent repair time, this paper takes constraint conditions, such as a variety of execution modes and repair resources into consideration during the model building process of the emergency rush repair scheduling, and we study emergency repair strategies, such as using the emergency generator vehicle, nearby repair strategy and ordinary repair strategy. In order to obtain the optimal solution and satisfy the constraints of the distribution network repair model, this paper improves the traditional serial schedule generation mechanism to a distribution network repair serial schedule generation mechanism by using improved SA algorithm and hierarchical optimization method to search the optimal solution. Finally, we use the model to an example and analyze it. It is validated that the two schedule generation mechanisms that use nearby repair strategy and ordinary repair strategy are both effective. Both the advantages and disadvantages of two mechanisms, and the feasibility and rationality of the model are analyzed in this paper.     

Reactive Power Optimization Using Hybrid CABC-DE Algorithm

Reactive power optimization is closely related to voltage quality and network loss, and it has great significance for the safety, reliability, and economical operation of the power system. Differential evolution (DE) algorithm has been currently applied to reactive power optimization. In order to mitigate the shortcomings of poor local search ability and premature convergence in DE, this paper presents a novel hybrid algorithm–chaotic artificial bee colony differential evolution (CABC-DE) algorithm, which improves the DE algorithm based on artificial bee colony algorithm and ideas of chaotic search. It introduces the observation bees' acceleration operation and the detective bees' chaotic search operation into CABC-DE. The validity of the proposed method is examined using IEEE-14 and IEEE-30 bus system. The experimental results show that CABC-DE algorithm is more effective than regular DE algorithm for reactive power optimization. The algorithm can save the search time greatly and get a better solution for optimization, thus making it suitable for solving reactive power optimization problems.     

多微电源混合系统在微电网中最优定位和规划研究

合理利用多种形式能源为负荷供电可以有效提高微电网运行经济和可靠性,然而目前微电源的前期选址定容和后期优化运行均孤立考虑,为了充分发挥其灵活供电能力,提出一种基于光伏、电池组以及柴油发电机的混合供电系统规划策略。首先,给出了光伏-电池组-柴油发电机混合供电系统能量运行方式,提高其运行经济性和灵活性;其次,提出了综合考虑多电源定位规划和运行优化的多目标优化模型,不仅减小总投资、运行维护成本、上级电网输送功率引起的网损及紧急情况引起的切负荷发生概率,同时可以使剩余能量反送给上级电网;最后,给出了基于粒子群优化人工蜂群算法改进求解方法,有效提高收敛速度。仿真结果证明,所提出的规划策略可显著提高微电网运行的经济性和可靠性。     

基于改进人工蜂群算法的电力系统无功优化

针对电力系统无功优化存在的问题,提出了一种基于改进人工蜂群算法的无功优化。运用反学习法对人工蜂群算法进行了优化,克服了人工蜂群算法本身容易陷入局部收敛的缺点,并且对IEEE30节点进行仿真计算,结果表明该算法对于求解复杂无功优化问题的可行性和有效性。     

改进自适应蜂群优化算法在变压器故障诊断中的应用

为增强神经网络对变压器故障诊断的能力,同时避免蜂群算法出现局部最优和易早熟,提出一种改进自适应搜索策略蜂群优化算法。该方法通过自适应调整种群更新步长来协调蜂群算法的全局和局部搜索能力,避免出现局部最优状况,同时引入Levy变异因子提高局部搜索的性能。利用改进的蜂群算法优化BP神经网络权值和阈值,通过反复迭代算法,直到达到目标精度要求。该方法以变压器数据为依据进行测试。仿真结果表明,改进后的方法收敛速度更快、判别故障准确率更高。     

An adaptive chaotic artificial bee colony algorithm for short-term hydrothermal generation scheduling

Short-term hydrothermal scheduling (SHS) is a complicated nonlinear optimization problem with a set of constraints, which plays an important role in power system operations. In this paper, we propose to use an adaptive chaotic artificial bee colony (ACABC) algorithm to solve the SHS problem. In the proposed method, chaotic search is applied to help the artificial bee colony (ABC) algorithm to escape from a local optimum effectively. Furthermore, an adaptive coordinating mechanism of modification rate in employed bee phase is introduced to increase the ability of the algorithm to avoid premature convergence. Moreover, a new constraint handling method is combined with the ABC algorithm in order to solve the equality coupling constraints. We used a hydrothermal test system to demonstrate the effectiveness of the proposed method. The numerical results obtained by ACABC are compared with those obtained by the adaptive ABC algorithm (AABC), the chaotic ABC algorithm (CABC) and other methods mentioned in literature. The simulation results indicate that the proposed method outperforms those established optimization algorithms.     

基于最优场景生成算法的主动配电网无功优化

针对间歇性分布式电源输出功率的不确定性和随机性,提出采用Wasserstein距离指标和K-means聚类场景削减技术生成最优场景,将随机优化问题转换为确定性优化问题。建立了风—光—荷多场景树模型,并以有功网损最小、电压偏差最小作为目标函数,考虑储能荷电状态约束影响,建立含间歇性分布式电源的主动配电网无功优化数学模型,并采用人工蜂群算法对模型进行求解。仿真分析得出基于Wasserstein距离指标和K-means聚类场景削减技术生成的最优场景能较精确地体现分布式电源有功出力的随机特性。最后,以IEEE-33节点配电系统为例进行仿真分析,验证了所提方法的有效性和可行性。     

Optimal allocation,sizing of PHEV parking lots in distribution system

The emerging of plug-in-hybrid electric vehicles (PHEV) results in the increase in the utilization of vehicles batteries for grid support. This paper presents a multi-objective algorithm to optimally determine the number of parking lots to be allocated in a distribution system. In addition, the algorithm optimally selects the locations and sizes of these parking lots. The proposed algorithms determine also the corresponding energy scheduling of the system resources. The objective of the proposed algorithm is to minimize the overall energy cost of the system. The problem is formulated as an optimization problem which is solved using artificial bee colony (ABC) and firefly algorithm taking into consideration the power system and PHEV operational constraints. The proposed algorithms are applied to a 33-bus radial distribution network. The test results indicate an improvement in the operational conditions of the system.     

主动配电网的源-网-荷多层博弈经济调度策略

考虑到主动配电网具有多级管控的特点,提出了一种基于博弈论的源-网-荷多层博弈经济调度方法。为协调微网、配网和负荷的关系,将调度策略划分为三层,分别为微网与配网之间的合作博弈、配网与负荷之间的合作博弈以及负荷之间的非合作博弈。微网与配网的相互备用构成其合作关系,同时最优化可平移负荷使负荷之间的博弈达到纳什均衡,并引入顺序变量描述调度优先级。建立了以发电运行成本最小、网损最小和电压偏移合格率最高为目标的多目标优化调度模型,运用综合定权法将其化为单目标,并采用改进微分进化算法对其求解。算例证明,所提方法能够提高主动配电网对可再生能源的消纳能力,提升系统经济性。