电池源太阳能光伏电站(B-SSPV)在配电网中的规模和布局

Abid Ali, N. M. Nor, T. Ibrahim, M. Romlie, Kishore Bingi
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摘要

本章提出了一种混合整数优化方法,使用遗传算法(MIOGA)来确定电池源太阳能光伏电站(B-SSPV)的最佳尺寸和位置,以减少配电网中的总能量损失。以总能量损失指数(TELI)为主要目标函数,同时计算了B-SSPV电站的母线电压偏差和光伏穿透量。为了处理太阳辐照度的随机行为,用β概率密度函数(beta - pdf)模拟了15年的天气数据。将该算法应用于ieee33总线和ieee69总线测试配电网,并对不同时变电压相关负荷模型进行了优化。从结果可以得知,与仅光伏发电相比,B-SSPV电站在配电网中的整合导致配电网的渗透率更高。所提出的算法在确定光伏电站和电池储能的大小以及电池储能的充放电方面非常有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sizing and Placement of Battery-Sourced Solar Photovoltaic (B-SSPV) Plants in Distribution Networks
This chapter proposes a mixed-integer optimization using genetic algorithm (MIOGA) for determining the optimum sizes and placements of battery-sourced solar photovoltaic (B-SSPV) plants to reduce the total energy losses in distribution networks. Total energy loss index (TELI) is formulated as the main objective function and meanwhile bus voltage deviations and PV penetrations of B-SSPV plants are calculated. To deal the stochastic behavior of solar irradiance, 15 years of weather data is modeled by using beta probability density function (Beta-PDF). The proposed algorithm is applied on IEEE 33 bus and IEEE 69 bus test distribution networks and optimum results are acquired for different time varying voltage dependent load models. From the results, it is known that, compared to PV only, the integration of B-SSPV plants in the distribution networks resulted in higher penetration levels in distribution networks. The proposed algorithm was very effective in terms of determining the sizes of the PV plant and the battery storage, and for the charging and discharging of the battery storage.
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