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Multiple Solutions of Optimal PMU Placement Using Exponential Binary PSO Algorithm for Smart Grid Applications

机译:指数二进制PSO算法在智能电网应用中最优PMU布置的多种解决方案

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For smart grid execution, one of the most important requirements is fast, precise, and efficient synchronized measurements, which are possible by phasor measurement unit (PMU). To achieve fully observable network with the least number of PMUs, optimal placement of PMU (OPP) is crucial. In trying to achieve OPP, priority may be given at critical buses, generator buses, or buses that are meant for future extension. Also, different applications will have to be kept in view while prioritizing PMU placement. Hence, OPP with multiple solutions (MSs) can offer better flexibility for different placement strategies as it can meet the best solution based on the requirements. To provide MSs, an effective exponential binary particle swarm optimization (EBPSO) algorithm is developed. In this algorithm, a nonlinear inertia-weight-coefficient is used to improve the searching capability. To incorporate previous position of particle, two innovative mathematical equations that can update particle's position are formulated. For quick and reliable convergence, two useful filtration techniques that can facilitate MSs are applied. Single mutation operator is conditionally applied to avoid stagnation. The EBPSO algorithm is so developed that it can provide MSs for various practical contingencies, such as single PMU outage and single line outage for different systems.
机译:对于智能电网执行,最重要的要求之一是快速,精确和高效的同步测量,这可以通过相量测量单元(PMU)实现。为了以最少的PMU数量实现完全可观察的网络,PMU(OPP)的最佳放置至关重要。在尝试实现OPP时,可以优先考虑关键总线,发电机总线或打算用于将来扩展的总线。同样,在优先安排PMU放置时,必须保留不同的应用程序。因此,具有多种解决方案(MS)的OPP可以根据要求满足最佳解决方案,因此可以为不同的放置策略提供更好的灵活性。为了提供MS,开发了一种有效的指数二进制粒子群优化(EBPSO)算法。在该算法中,使用非线性惯性权重系数来提高搜索能力。为了合并粒子的先前位置,制定了两个可以更新粒子位置的创新数学方程式。为了快速可靠地收敛,应用了两种有助于MS的有用过滤技术。有条件地应用单个变异算子来避免停滞。 EBPSO算法如此发达,可以为各种实际情况提供MS,例如针对不同系统的单PMU中断和单线中断。

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