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Parameter Optimization of Droop Controllers for Microgrids in Islanded Mode by the SQP Method with Gradient Sampling

机译:梯度采样的SQP方法对岛状模式下微电网的Droop控制器参数优化

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For enhancing the stability of the microgrid operation, this paper proposes an optimization model considering the small-signal stability constraint. Due to the nonsmooth property of the spectral abscissa function, the droop controller parameters’ optimization is a nonsmooth optimization problem. The Sequential Quadratic Programming with Gradient Sampling (SQP-GS) is implemented to optimize the droop controller parameters for solving the nonsmooth problem. The SQP-GS method can guarantee the solution of the optimization problem globally and efficiently converges to stationary points with probability of one. In the current iteration, the gradient of the nonsmooth function can be evaluated on a set of randomly generated nearby points by computing closed-form sensitivities. A test on the microgrid system shows that the optimality and the efficiency of the SQP-GS are better than those of the heuristic algorithms.
机译:为了提高微电网操作的稳定性,本文提出了考虑小信号稳定约束的优化模型。 由于光谱横坐标功能的非光滑属性,下垂控制器参数的优化是一个非光滑优化问题。 实现了具有梯度采样(SQP-GS)的顺序二次编程以优化下垂控制器参数以解决非光驱问题。 SQP-GS方法可以保证全球优化问题的解决方案,并有效地收敛于具有概率的静止点。 在当前迭代中,可以通过计算闭合形式灵敏度对一组随机产生的附近点进行评估非光滑函数的梯度。 对微电网系统的测试表明,SQP-GS的最优性和效率优于启发式算法。

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