含大规模风光电源的配电网储能电池选址定容优化方案

Optimal battery storage allocation in distributed network with large-scale of wind and photovoltaic generation

分布式储能可改善风光等分布式电源大规模并网导致的电网安全和经济运行问题,配电网储能配置关系储能电池工作能力的提升和电网投资成本的降低。提出一种配电网中储能选址定容的双层优化方案:外层以电网成本最低为目标,通过遗传算法优化储能配置,并对遗传算法加以改进,提高计算效率;内层以降低网损、提高削峰填谷收益为目标,利用序列二次规划算法同时计算多时段配网最优潮流,实现储能充放电优化;为保证内外层优化有效配合,利用内层结果对储能容量进行修正,提高储能的利用率;分析风电和光伏额定功率等因素对储能系统配置结果的影响。最后对一个含风光电源的17节点配电网进行测试,验证所提方法的有效性。

The distributed energy storage can improve the gird safe and economical operation caused by large-scale of wind and photovoltaic generation. To make good use of the battery and reduce investment cost,it is important for the gird to be equipped with the optimal allocation of the battery storage. A two-layer optimization algorithm to optimize the sitting and sizing of the storage was proposed in this paper. The outer layer aimed at minimizing the system cost. An enhanced genetic algorithm was employed to optimize the allocation while the computing efficiency was improved. The inner layer was to acquire the optimized battery charging power when targeting at minimizing the power loss and raising the revenue of load shifting. The sequential quadratic programming served to solve the optimal power flow of several hours simultaneously. Meanwhile,the inner layer modified the power and capacity of the storage to guarantee the cooperation of the two layers. The influence of the wind and photovoltaic rated power on the best allocation was analyzed. Finally, a 17-bus distribution network was used to verify the proposed algorithm. The results show that this method can effectively find the allocation of the storage.