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首页> 外文会议>2016 International Conference on Microelectronics, Computing and Communications >Hybrid firefly algorithm based distribution state estimation with regard to renewable energy sources
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Hybrid firefly algorithm based distribution state estimation with regard to renewable energy sources

机译：基于混合萤火虫算法的可再生能源分布状态估计

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Renewable energy, which is a continuous source of energy, can be classified as the sun, running water, biomass, wind, geothermal sources and ocean currents. Several research works projects about 30% of the total generations will be from Renewable Energy Sources (RES) in future and so it's important to analyze different prospects of RES mainly over distribution networks. In this paper, a new Distribution State Estimation (DSE) with RES has been proposed based on a combination of Genetic Algorithm (GA) and Firefly Algorithm (FA). In case of radial distribution network with different RES, State estimation is generally called mixtribution which is basically an optimization technique. This Hybrid Firefly Algorithm (HFA) can estimate RES and load values using Weighted Least Square (WLS) method with some typical situations like reactive power compensator, tap changing transformer modeling, voltage regulator having nonlinear nature of characteristics. For a better understanding and feasibility of the proposed approach, the algorithm is checked over the IEEE 70 bus test system.
机译：可再生能源是一种持续的能源，可以分为太阳，自来水，生物质能，风能，地热能和洋流。将来，有几项研究项目计划约占总发电量的30％来自可再生能源（RES），因此分析主要通过配电网络进行的RES的不同前景非常重要。本文提出了一种基于遗传算法（GA）和萤火虫算法（FA）的带RES的新的配电状态估计（DSE）。在具有不同RES的径向分布网络的情况下，状态估计通常称为混合分配，这基本上是一种优化技术。这种混合萤火虫算法（HFA）可以使用加权最小二乘（WLS）方法估计RES和负载值，并具有一些典型情况，例如无功功率补偿器，抽头变换变压器建模，具有非线性特性的电压调节器。为了更好地理解所提出方法的可行性，该算法在IEEE 70总线测试系统上进行了检查。

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