共查询到18条相似文献,搜索用时 125 毫秒
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针对现有电力系统相量测量装置(PMU)在系统中的最优配置问题,进一步考虑了系统发展过程中PMU数量增加的最优配置问题.以电力系统线性量测模型为基础,通过拓扑分析方法,以全系统可观为约束,以系统最大冗余度为目标,并使用改进的粒子群算法进行计算,实现PMU数量增加过程中的最优配置.通过算例证明了算法的有效可靠. 相似文献
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以电力系统状态信息完全可观测为前提,配置相量测量单元PMU(phasor measurement unit)数目最少为目标,建立PMU优化配置问题的数学模型,并应用一种变权重蛙跳算法进行求解。首先以混合蛙跳算法为基础,建立考虑PMU配置数目和系统可观性的适应度函数;然后通过改变蛙体基因段的权重,指引蛙体跳跃的方向,解决了收敛性较差和跳出局部最优解较慢的缺点,实现了最优配置方案多样性;最后进行冗余度比较确定最优方案。通过新英格兰39母线系统和IEEE 57母线系统的仿真分析,验证本文方法较一般算法具有更佳的收敛效果和全局性。 相似文献
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考虑高风险连锁故障的PMU配置方法 总被引:2,自引:0,他引:2
针对连锁故障会导致广域测量系统(WAMS)丧失对电力系统完全可观测能力的问题,提出了一种考虑高风险连锁故障的最优相量测量单元(PMU)配置方法.首先使用隐性故障模型和风险理论对电力系统的连锁故障进行模拟仿真和统计分析,从而对系统中的高风险连锁故障进行辨识;进而通过最优PMU配置保证在单一高风险连锁故障发生的情况下WAMS能够保持对电网的完全可观测.以IEEE 39节点系统为例进行了PMU配置和分析,实验结果表明该方法在经济性和鲁棒性之间能够取得较好的平衡. 相似文献
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电力系统PMU最优配置数字规划算法 总被引:16,自引:3,他引:16
随着相量量测装置(PMU)硬件技术的逐渐成熟和高速通信网络的发展,PMU在电力系统中的状态估计、动态监测和稳定控制等方面得到了广泛应用.为达到系统完全可观,在所有的节点上均装设PMU既不可能也没有必要.文中提出一种基于系统拓扑可观性理论的数字规划算法,利用PMU和系统提供的状态信息,最大限度地对网络拓扑约束方程式进行了简化,以配置PMU数目最小为目标,形成了PMU最优配置问题,并采用禁忌搜索算法求解该问题.其突出优点是利用了系统混合测量集数据,即不仅考虑了PMU实测数据,同时计及了可用的潮流数据.在IEEE14节点和IEEE 118节点系统的仿真结果表明,与常规的PMU最优配置算法相比,所提出的数字规划算法可以实现安装较少数量的PMU而整个系统可观的目标. 相似文献
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船舶电力系统相量测量单元多目标优化配置问题 总被引:3,自引:1,他引:2
为实现船舶电力系统潮流方程直接可解,同时保证相量测量单元(PMU)配置数目最少和N-1电压相量可解冗余度最高,提出了船舶电力系统PMU多目标优化配置方法。首先根据船舶电力系统不同工况下潮流方程的特点,分析得到PMU配置方案是否满足不同工况下潮流方程直接可解的判断方法;在此基础上,着重考虑最大运行工况下PMU配置数目最少和N-1电压相量可解冗余度最高的要求,建立了PMU多目标优化配置模型,并采用量子遗传优化算法对模型进行求解。以24节点典型船舶电力系统为例对所提方法进行了说明和验证,结果表明,该方法可实现全局多目标寻优,从而找到准确而完整的Pareto最优前沿。得到的PMU优化配置方案可为船舶电力系统配置PMU提供参考。 相似文献
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基于电网脆弱性和经济性评估的PMU 最优配置新方法 总被引:1,自引:0,他引:1
基于 GPS 时钟同步技术的同步相量测量装置(phasor measurement unit,PMU)为直接观测电力系统的动态行为提供了重要手段.若电网发生 N?1故障,传统的 PMU 配置不能满足全网可观的要求.若考虑 N?1情况,PMU 配置个数较传统配置多,成本大大增加.针对上述问题,提出一种新的 PMU 最优配置方案.该方案利用广义特勒根定理对电网母线与支路进行脆弱度分析,然后对全网进行 PMU 配置及考虑 N?1情况的 PMU 配置.通过脆弱度排序、经济指标、鲁棒性分析,确定 PMU 配置新方案.以 IEEE 14标准节点系统为算例,验证了该方法的可行性. 相似文献
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用免疫BPSO算法和N-1原则多目标优化配置PMU 总被引:1,自引:1,他引:0
为了在满足全网的完全可观测的前提下实现PMU安装投入的性价比最高,通过理论分析得出判断电网节点拓扑可观测的依据,并提出以N-1可靠性检验原则对PMU配置方案进行冗余性检验,由此以全网完全可观测、PMU数目最少和N-1量测冗余度最高为目标建立了PMU多目标优化配置数学模型,并设计了一种结合免疫系统信息处理机制的二进制粒子群优化算法对模型进行求解。该算法综合了粒子群优化算法简单快速和免疫系统种群多样性的优点,明显改善了进化后期算法的收敛性能和全局寻优能力。对新英格兰39母线系统进行PMU多目标优化配置仿真及量测冗余性分析的结果表明,该法对PMU配置方案的量测可靠性及其所需PMU数量进行综合评价可方便快捷地得到性价比最优的方案,较之普通的PMU单目标优化配置方法更为合理和灵活。 相似文献
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基于免疫BPSO算法与拓扑可观性的PMU最优配置 总被引:2,自引:0,他引:2
以电力系统状态完全可观测和相量测量单元PMU配置数目最小为优化目标,基于PMU的功能特点和电力网络的拓扑结构信息,形成快速且通用的电网拓扑可观测性判别方法,并设计了一种结合免疫系统信息处理机制的二进制粒子群优化算法对目标函数进行求解,该算法综合了粒子群优化算法简单快速和免疫系统种群多样性的优点,明显改善了进化后期算法的收敛性能和全局寻优能力.最后通过对IEEE14和新英格兰39母线系统进行PMU优化配置仿真及量测冗余性分析,验证了本文方法的有效性和优越性. 相似文献
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This paper addresses two aspects of the optimal Phasor Measurement Unit (PMU) placement problem. Firstly, an ILP (Integer Linear Programing) model for the optimal multistage placement of PMUs is proposed. The approach finds the number of PMUs and its placement in separate stages, while maximizing the system observability at each period of time. The model takes into account: the available budget per stage, the power system expansion along with the multistage PMU placement, redundancy in the PMU placement against the failure of a PMU or its communication links, user defined time constraints for PMU allocation, and the zero-injection effect. Secondly, it is proposed a methodology to identify buses to be observed for dynamic stability monitoring. Two criteria, which are inter-area observability and intra-area observability, have been considered. The methodology identifies coherent groups in large power systems by using a new technique based on graph theory. The technique requires neither full stability studies nor a predefined number of groups. Also, a centrality criterion is used to select a bus for monitoring each coherent area and supervise inter-area oscillations. Then, PMUs are located to ensure complete observability inside each area (intra-area monitoring). Methodology is applied on the 14-bus test system, the 57-bus test system with expansion plans, and the 16-machine 68 bus test system. Results indicate that the optimization model finds the optimal number of PMUs when the PMU placement by stages is required, while the observability at each stage is maximized. Additionally, it is shown that expansion plans and particular requirements of observability can be considered in the model without increasing the number of required PMUs, and the zero-injection effect, which reduces the number of PMUs, can be considered in the model. 相似文献
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基于不可观测深度的分阶段PMU配置算法 总被引:4,自引:1,他引:3
首先介绍了不可观测深度的概念,然后提出混合运用广域测量系统和能量管理系统的数据进行线性状态估计的方法以弥补PMU量测的不足,以此作为在系统不完全可观条件下进行PMU配置的前提。不完全可观系统PMU配置模型能处理如通信条件限制、已配置了部分PMU等约束条件,并能用0-1线性整数规划模型求解。文章最后提出了PMU分阶段配置的方法,并在新英格兰测试系统和浙江电网中进行了验证。结果表明,PMU分阶段优化配置能有效减少初期费用,并且随着系统不可观测深度的降低,线性状态估计的效果更好。 相似文献
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In optimal PMU placement problem, a common assumption is that each PMU installed at a bus can measure the voltage phasor of the installed bus and the current phasors of all lines incident to the bus. However, available PMUs have limited number of channels and cannot measure the current phasors of all their incident lines. The aim of this paper is to recognize the effect of channel capacity of PMUs on their optimal placement for complete power system observability. Initially, the conventional full observability of power networks is formulated. Next, a modified algorithm based on integer linear programming model for the optimal placement of these types of PMUs is presented. The proposed formulation is also extended for assuring complete observability under different contingencies such as single PMU loss and single line outage. Moreover, the problem of combination of PMUs with different number of channels and varying costs in optimal PMU placement is investigated. Since the proposed optimization formulation is regarded to be a multiple-solution one, total measurement redundancy index is evaluated and the solution with the highest redundancy index is selected as the optimal solution. The proposed formulation is applied to several IEEE standard test systems and compared with the existing techniques. 相似文献
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Yoshiaki Matsukawa Masayuki Watanabe Yasunori Mitani Mohammad Lutfi Othman 《Electrical Engineering in Japan》2019,207(2):20-27
The optimal phasor measurement unit (PMU) placement problem in power systems has been considered and investigated by many researchers for accurate and fast state estimation by PMUs. However, the current channel cost of the PMU affects the total placement cost. This paper proposes a novel formulation in the multi‐objective optimal PMU placement, which minimizes the PMU placement cost with the current channel selection and the state estimation error. The current channel selection is represented as a decision variable in the optimization. For trade‐off objective functions, the Pareto approach by nondominated sorting genetic algorithm II (NSGA‐II) is applied in the optimization. The result of the numerical experiment in this paper demonstrates the advantage of considering the appropriate PMU current channel allocation, compared with the conventional method that ignores it, in the modified IEEE New England 39‐bus test system. As a result, the proposed method obtained a better Pareto solution compared with the conventional one because of the consideration for the current channel selection. An advantage of the proposed PMU placement is that it is able to reduce the total PMU placement cost while maintaining the state estimation accuracy. 相似文献