智能变压器、软开路点和电池储能系统下配电网的能量管理

Abhishek Singh, A. Maulik
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引用次数: 1

摘要

本文提出了一种多目标能量管理方案,以同时降低可再生能源(太阳能和风能)和插电式混合动力汽车负载组成的配电网的预期运行成本,提高电压稳定性,使平均电压偏差最小化。对基于电力电子变换器的软开路点、智能变压器等设备进行协调控制,实现能源管理战略的目标。采用概率方法对可再生能源发电、负荷、插电式混合动力汽车充电功率需求和电网能源价格的不确定性进行建模。采用“Hong’s 2m点估计法”将不确定性纳入最优潮流。对改进后的33总线配电网进行了仿真研究。仿真结果表明,所提出的概率能量管理策略可使期望运行成本降低约1.48%,使电压稳定性提高至少约27.26%,使平均电压偏差降低至少约77.50%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Management of Distribution Network in the Presence of Smart Transformers, Soft Open Points, and Battery Energy Storage System
In this paper, a multi-objective energy management scheme is proposed to simultaneously reduce the expected cost of operation, improve the voltage stability, minimize the average voltage deviation in a distribution network comprising renewable generation sources (solar and wind), and plug-in hybrid electric vehicle loads. Power electronic converter-based devices like soft open point and smart transformer are controlled in a coordinated fashion to realize the objectives of the energy management strategy. A probabilistic approach models the uncertainties of renewable generation, load, charging power requirement of plugin hybrid electric vehicles, and grid energy price. "Hong's 2m point estimate method" is used to incorporate the uncertainties in the optimal power flow. Simulation studies are carried out on a modified thirty-three bus distribution network. Simulation results demonstrate that the proposed probabilistic energy management strategy can reduce the expected cost of operation by ~ 1.48%, improve the voltage stability by at least ~ 27.26%, and reduce the average voltage deviation by at least ~ 77.50%.
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