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Optimal Day-Ahead Scheduling of a Smart Distribution Grid Considering Reactive Power Capability of Distributed Generation

机译:考虑分布式发电无功能力的智能配电网最优提前调度

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In the traditional paradigm, large power plants provide active and reactive power required for the transmission system and the distribution network purchases grid power from it. However, with more and more distributed energy resources (DERs) connected at distribution levels, it is necessary to schedule DERs to meet their demand and participate in the electricity markets at the distribution level in the near future. This paper proposes a comprehensive operational scheduling model to be used in the distribution management system (DMS). The model aims to determine optimal decisions on active elements of the network, distributed generations (DGs), and responsive loads (RLs), seeking to minimize the day-ahead composite economic cost of the distribution network. For more detailed simulation, the composite cost includes the aspects of the operation cost, emission cost, and transmission loss cost of the network. Additionally, the DMS effectively utilizes the reactive power support capabilities of wind and solar power integrated in the distribution, which is usually neglected in previous works. The optimization procedure is formulated as a nonlinear combinatorial problem and solved with a modified differential evolution algorithm. A modified 33-bus distribution network is employed to validate the satisfactory performance of the proposed methodology.
机译:在传统范式中,大型电厂提供传输系统所需的有功和无功功率,而配电网络则从中购买电网功率。但是,随着越来越多的分布式能源在配电级别上连接,有必要安排DER以满足其需求并在不久的将来参与配电级别的电力市场。本文提出了一种用于配送管理系统(DMS)的综合运营调度模型。该模型旨在确定有关网络活动元素,分布式发电(DG)和响应负载(RL)的最佳决策,以力求使配电网络日复一日的综合经济成本降至最低。为了进行更详细的仿真,复合成本包括网络的运营成本,排放成本和传输损耗成本。此外,DMS有效地利用了配电中集成的风电和太阳能的无功功率支持功能,这在以前的工作中通常被忽略。优化过程被公式化为非线性组合问题,并使用改进的差分进化算法求解。修改后的33总线配电网络用于验证所提出方法的令人满意的性能。

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