风电场复合储能系统容量配置的优化设计  

Optimal Design of Hybrid Energy Storage System Capacity for Wind Farms

作　　者：张坤[1] 毛承雄[1] 谢俊文[1] 陆继明[1] 王丹[1] 曾杰[2] 陈迅[2] 

机构地区：[1]强电磁工程与新技术国家重点实验室(华中科技大学),湖北省武汉市430074 [2]广东电网公司电力科学研究院,广东省广州市510080

出　　处：《中国电机工程学报》2012年第25期79-87,13,共9页Proceedings of the CSEE

基　　金：国家重点基础研究发展计划(2009CB219702);国家自然科学基金重点项目(50837003)~~

摘　　要：依据风电场复合储能系统的功能和工作特性,提出了一种复合储能系统(hybrid energy storage system,HESS)容量的优化配置方法,使其在满足平滑风电功率波动等技术性能的同时,还能满足系统的经济性要求。首先,提出了一种能够定量反映功率曲线平滑度的判据标准。其次,建立了复合储能系统特性参数–风电功率平滑度的短期神经网络模型,并在此基础上综合考虑了复合储能系统的技术性能和经济性能,建立了反映复合储能系统特性参数–风电功率平滑度、复合储能系统成本特性的长期数学模型。最后,通过遗传算法对该模型的目标函数进行寻优,从而得到复合储能系统最佳的特性参数组合。算例分析表明所提出的方法是合理、有效的。According to the function and operating characteristics of hybrid energy storage system （HESS） for wind farm, an optimal design method of HESS capacity was proposed so that HESS can meet the technical requirements, such as smoothing out the wind power fluctuations and the economic requirement. In this paper, a quantitative criterion was proposed to identify the level of smoothing （LOS） of power curve firstly. Secondly, a short-term neural network model was established to reflect the relationship between characteristic parameters of HESS and LOS of output power transmitted to the grid. And then taken the technical and economic demand into the comprehensive consideration, a long-term mathematical model was established to reflect the relationship between characteristic parameters of HESS, LOS of output power transmitted to the grid and economic cost of HESS. Finally, genetic algorithm （GA） was used to determine optimal characteristic parameters of HESS by optimizing the objective function, which was derived from the built model. An example shows the rationality and effectiveness of the proposed method.

关 键 词：风力发电 复合储能系统 储能容量 平滑时间常 数 神经网络 遗传算法 

分 类 号：TM71[电气工程—电力系统及自动化]