基于鲁棒后悔度的光储微网优化调度

发布时间：2018-03-08 09:05

本文选题：微网　切入点：鲁棒后悔度　出处：《电网技术》2017年01期 　论文类型：期刊论文

【摘要】：提出了一种光储微网系统的鲁棒后悔度优化调度方法,以抑制系统中光伏输出和负荷需求的不确定性扰动。依据不确定参数的预测值及分时电价,动态非均匀划分调度时段以降低求解复杂度。考虑到蓄电池循环寿命在不同充放电深度下的损耗,构建光储微网鲁棒后悔度优化调度模型。由于模型求解属于一类带有非线性的双层优化问题,采用拉格朗日两段松弛和交叉熵混合求解算法获取鲁棒优化调度方案。算例仿真表明,所提求解算法能够实现最大扰动下的经济后悔度最小化,并且动态非均匀调度时段划分能够加快优化模型求解速度。相对于确定性优化调度,鲁棒后悔度优化能够有效减少不确定性因素对模型的影响,从而验证了所提优化调度方法的有效性和可行性。
[Abstract]:In this paper, a robust regret optimal scheduling method for optical storage microgrid system is proposed to suppress the uncertainty disturbance of PV output and load demand in the system, based on the predicted value of uncertain parameters and time-sharing price. Dynamic nonuniform partition of scheduling period is used to reduce the complexity of solution. Considering the loss of battery cycle life at different charge and discharge depths, In this paper, a robust regret scheduling model for optical micronetworks is constructed. The solution of the model belongs to a class of bilevel optimization problems with nonlinearity. The Lagrangian two-stage relaxation and cross-entropy hybrid algorithm are used to obtain the robust optimal scheduling scheme. The simulation results show that the proposed algorithm can minimize the economic regret under the maximum disturbance. And dynamic non-uniform scheduling time division can speed up the optimization model solving speed. Compared with deterministic optimal scheduling, robust regret optimization can effectively reduce the influence of uncertain factors on the model. The effectiveness and feasibility of the proposed optimal scheduling method are verified.
【作者单位】：山东大学控制科学与工程学院;
【基金】：山东省自然科学基金资助项目(ZR2014FM036)
【分类号】：TM73

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