元启发式算法在稳态减载离散模型中的应用

B. Rad, M. Abedi
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引用次数: 5

摘要

紧急情况下的最优减载是电力系统规划、安全和运行中的重要问题之一。为了防止电压崩溃和线路过载等可能导致级联停电和停电的现象,必须进行减载。本文提出了一种新的最优减载方法。该方法的一个重要规范是确定每条总线的负载减少量。在本研究中,主要研究基于偶然性排序的单线临界停机和发电机停机。将最优减载问题表述为一个受运行和安全约束的非线性优化问题,目标函数为服务中断成本。最后,采用遗传算法和粒子群算法求解减载问题,其中权重因子采用层次分析法确定。该方法在ieee30总线系统上进行了测试,并给出了测试结果。
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Application of meta-heuristics algorithms in discrete model of steady-state load-shedding
Optimal load-shedding during contingency situations is one of the most important issues in planning, security, and operation of power systems. Load-shedding is necessary to prevent phenomena such as voltage collapse and line over load which may lead to cascade outages and then black-out. In this paper, a new optimal load-shedding approach is presented. One of the important specifications of this method is that amount of load shed from each bus is determined. In this research, studies consist of critical single line and generator outage based on contingency ranking. The optimal load-shedding is formulated as a nonlinear optimization problem subject to operation and security constraints, where objective function is the service interruption cost. Finally, the load-shedding problem is also solved by genetic and particle swarm optimization algorithms, in which weighting factors are determined using AHP method. The proposed method is tested on the IEEE 30 bus system, and the results are presented.
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