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Static security based available transfer capability (ATC) computation for real-time power markets

机译:基于静态安全性的实时电力市场的可用传输能力(ATC)计算

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In power system deregulation, the Independent System Operator (ISO) has the responsibility to control the power transactions and avoid overloading of the transmission lines beyond their thermal limits. To achieve this, the ISO has to update in real-time periodically Available Transfer Capability (ATC) index for enabling market participants to reserve the transmission service. In this paper Static Security based ATC has been computed for real-time applications using three artificial intelligent methods viz.: i) Back Propagation Algorithm (BPA); ii) Radial Basis Function (RBF) Neural network; and iii) Adaptive Neuro Fuzzy Inference System (ANFIS). These three different intelligent methods are tested on IEEE 24-bus Reliability Test System (RTS) and 75-bus practical System for the base case and critical line outage cases for different transactions. The results are compared with the conventional full AC Load Flow method for different transactions.
机译:在电力系统解除管制中,独立系统运营商(ISO)负责控制电力交易,并避免传输线超出其热极限的过载。为此,ISO必须实时定期更新可用传输能力(ATC)索引,以使市场参与者能够保留传输服务。在本文中,已经使用三种人工智能方法为实时应用计算了基于静态安全的ATC,即:i)反向传播算法(BPA); ii)径向基函数(RBF)神经网络; iii)自适应神经模糊推理系统(ANFIS)。这三种不同的智能方法在IEEE 24总线可靠性测试系统(RTS)和75总线实用系统上针对不同事务的基本情况和关键线路中断情况进行了测试。将结果与传统的完全交流潮流计算方法进行比较,以进行不同的处理。

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