Transient Stable Corrective Control Using Neural Lyapunov Learning
Transient Stable Corrective Control Using Neural Lyapunov Learning
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DOI：
10.1109/tpwrs.2022.3204459
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发表时间：
2023-07
影响因子：
6.6
通讯作者：
Federica Bellizio;J. Cremer;G. Strbac
中科院分区：
文献类型：
--
作者：
Federica Bellizio;J. Cremer;G. Strbac
本文提出了一种实时计算动态安全校正控制措施的方法，并量化了校正控制的经济价值。降低惯性需要实时的快速控制方法，以在设备故障时纠正系统操作并保持系统安全性。然而，在这种紧急故障措施之外使用纠正控制并没有充分利用它们。这项工作的主要贡献是最佳使用纠正控制应用程序结合预防策略，以提高网络利用率，降低正常运营成本，同时保持足够的安全水平。所提出的方法学习神经网络的安全证书和模型预测的安全动态故障后状态的代数约束在AC最优潮流（OPF）决定接近实时的最优校正控制。在ACOPF中考虑这些安全约束可以同时平衡系统暂态稳定性与预防和纠正控制的成本。这种方法优于次优方法，旨在顺序找到平衡。案例研究是基于IEEE 9总线系统与集成的电动汽车和风力发电的份额高达40%和IEEE 39总线和118总线系统。该方法在稳定性、经济性和碳排放方面优于基线控制方法。一种基线方法是预防性弃风，与此相比，所提出的方法将IEEE 9总线的运营成本降低了60%，将不稳定运营减少了50%，并将碳排放量减少了60%。在IEEE 39节点和118节点系统中，该方法适用于更大的系统。
This paper proposes a method to compute corrective control actions for dynamic security in real-time and quantifies the economic value of corrective control. Lowered inertia requires fast control methods in real-time to correct system operation and maintain system security when equipment fails. However, using corrective control beyond such emergency failure measures does not make fully use of them. The key contribution of this work is the optimal use of corrective control applications in combination with preventive strategies to enhance the network utilisation, reduce the normal operating costs while maintaining adequate security levels. The proposed approach learns a neural network for safety certificates and models the predicted safe dynamic post-fault state as algebraic constraints in an AC optimal power flow (OPF) deciding close to real-time on the optimal corrective control. Considering these safety constraints within the ACOPF can balance simultaneously the system transient stability with the costs for preventive and corrective control. This proposed approach outperforms sub-optimal approaches aiming at sequentially finding the balance. Case studies were based on the IEEE 9-bus system with integrated electrical vehicles and shares of wind power up-to 40% and on the IEEE 39-bus and 118-bus systems. The proposed approach outperforms baseline control approaches in stability, economics, and carbon emissions. One baseline approach was preventive wind curtailment, against which the proposed approach reduced operating costs by up-to 60%, decreased unstable operations by 50% and reduced carbon emissions by 60% in the IEEE 9-bus. In the IEEE 39-bus and 118-bus systems, the approach was promising for larger systems.