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Multi-Time Scale Active and Reactive Power Coordinated Optimal Dispatch in Active Distribution Network Based on Scenario Method

机译:基于情景法的配电网多时间尺度有功无功协调优化调度

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To improve the adaptability for renewable energy sources (RES), a multi-time scale optimal dispatching strategy based on the scenario method is proposed in the active distribution network (ADN). In the day-ahead stage, polynomial normal transformation and Latin hypercube sampling technology are employed to generate scenarios with temporal correlation. By optimizing the operation state of slow-response resources, the expected cost of ADN under all scenarios achieves a minimum. In the intraday stage, based on the updated predicted output of RES, the operation status of the fast-response resources is optimized using the same procedure. In the real-time stage, a rolling finite time-domain optimization strategy is adopted to minimize the deviation between the actual output and the intraday reference. Through the coordination of different time scales, the proposed method can reduce the action numbers of discrete reactive power compensation devices and restrain the fluctuation of bus voltage. A case study on a modified IEEE 33-bus system verified the economy and effectiveness of the proposed method.
机译:为了提高对可再生能源的适应性,提出了一种基于情景法的主动配电网多时间尺度优化调度策略。在日前阶段,采用多项式正态变换和拉丁超立方体采样技术生成具有时间相关性的场景。通过优化慢响应资源的运行状态,ADN在所有场景下的预期成本都达到了最低。在日内阶段,基于更新的RES预测输出,使用相同的程序优化快速响应资源的运行状态。在实时阶段,采用滚动有限时域优化策略,以最小化实际输出和日内参考之间的偏差。该方法通过不同时间尺度的协调,可以减少离散无功补偿装置的动作次数,抑制母线电压的波动。以一个改进的IEEE 33节点系统为例,验证了该方法的经济性和有效性。

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