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Power System Stability Control for a Wind Farm Based on Adaptive Dynamic Programming

机译：基于自适应动态规划的风电场电力系统稳定性控制

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摘要

In this paper, a goal representation heuristic dynamic programming (GrHDP) based controller is developed for the doubly-fed induction generator based wind farm to improve the system transient stability under fault conditions. The proposed controller is based on adaptive dynamic programming (ADP) techniques to approximate the optimal control policy according to the interaction between the controller and the power plant. Compared to existing ADP approaches with one action network and one critic network, our GrHDP architecture introduces an additional network, i.e., the reference network, to form an internal goal/reward representation. This better mapping between the system state and the control action significantly improves the control performance. The effectiveness of the proposed approach is validated via two cases. The first case investigates a revised four-machine two-area system with high wind penetration and a static synchronous compensator. The second case is a practical size power system with wind farm in Liaoning Province in China. Detailed simulation analysis and comparative studies with traditional ADP approaches are presented to demonstrate the superior performance of our method.
机译：本文针对基于双馈感应发电机的风电场，开发了一种基于目标表示启发式动态规划（GrHDP）的控制器，以提高故障条件下的系统暂态稳定性。所提出的控制器基于自适应动态规划（ADP）技术，根据控制器和电厂之间的相互作用来近似最佳控制策略。与具有一个动作网络和一个评论者网络的现有ADP方法相比，我们的GrHDP体系结构引入了一个附加网络（即参考网络）以形成内部目标/奖励表示。系统状态和控制动作之间的这种更好的映射显着提高了控制性能。通过两种情况验证了所提方法的有效性。第一个案例研究了经过修订的具有高风速和静态同步补偿器的四机两区域系统。第二种情况是中国辽宁省具有风电场的实际规模的电力系统。提出了详细的仿真分析和与传统ADP方法的比较研究，以证明我们方法的优越性能。

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