考虑概率分布约束的含高渗透率风电电力系统储能鲁棒优化方法

Distributional Robust Joint Chance Constrained Optimal Capacity Installment of Energy Storage in Power System With High Penetration of Wind Power

提出一种考虑风电功率预测误差概率分布不确定性的储能容量优化配置方法。该方法可保证在风电功率任意可能分布下,通过调度可调发电机组及配置储能以保证系统安全运行,同时最小化储能配置成本。首先鉴于历史数据的不完备性,将根据历史数据获得的风电二阶矩信息描述为波动区间,然后采用概率分布鲁棒联合机会约束模型描述含风场系统储能最优配置问题,进而采用拉格朗日对偶消去优化模型中的随机变量,将鲁棒机会约束模型转化为确定性的线性矩阵不等式问题,最后采用凸优化算法求解,并分析风电预测误差精度、机会约束置信度、风电功率波动性对储能配置容量的影响。采用修改的Garver 6节点算例验证了该方法的可行性和有效性。

This paper extends method estimating optimal installment of energy storage system（ESS） considering distributional uncertainties of wind power forecast errors（WPFEs）. Firstly, according to historical data of wind power, the second-order WPFE moment is formulated as fluctuation interval providing data incompleteness. Then distributional robust joint chance constrained（DRJCC） approach is used to describe optimal ESS installment model with large penetration of wind power. S-lemma and Schur complement are adopted to eliminate uncertainties in the proposed model so as to reformulate a deterministic linear matrix inequality. Finally, a new method involving convex optimization is applied to solve the problem. WPFE fluctuation interval, confidence level of DRJCC and covariance of WPFE are taken into consideration to evaluate their influences on results of ESS optimal installment, focusing on jointly optimization of ESS and units reserve. With revised Garver six bus system, feasibility and effectiveness of the proposed model is validated. Results indicate that the proposed method can ensure safe operation of power system under the worst-case WPFE distribution and minimize cost of installing ESSs through jointly dispatching scheduled output of dispatchable generating units and installed ESS capacity.