摘要
在风力发电补贴越来越低,未来更可能取消补贴且电力市场辅助服务越来越完善的情况下,提出了一种以风电场AGC辅助服务性能与整体收益为目标的混合储能系统配置方法。首先,基于华北地区的两个细则,分析了AGC辅助服务的考核指标。然后,采用充放电次数限制少、充放电功率高的全钒液电池与成本低廉、容量较大的铅酸电池组成的混合储能系统,提出基于AGC服务性能指标和发电量有效上网率的响应效能指标,更好的反映加入储能系统的效果,并制定了储能系统充放电响应及SOC状态强制回归策略。基于计算效率高、全局收敛性能好的混沌蚁群算法,通过建立储能系统的成本子模型、风电场AGC服务收益及增加有效上网电量收益子模型,构建了以日收益最大为目标的优化配置模型。最后,通过计算某风电场储能系统的最优经济配置,分析了加入储能前后的响应效能与收益。结果表明:最优经济配置方法合理有效,加入储能系统后提升风电场约30%的综合性能收益。研究成果对未来风电场合理配置混合储能系统具有较大参考价值。
An AGC auxiliary service performance and overall benefit of wind farm-targeted allocation method for the hybrid energy storage system is proposed herein under the condition that the subsidies of wind power are getting lower and lower, and more likely to be abolished in the future, while the auxiliary services power market are more and more perfect. At first, the appraisal indicators for AGC auxiliary service are analyzed in accordance with two rules for the region of the North China. Afterwards, the AGC service performance index and the rate of power generation to effectively access grid-based response performance indexes are put forward, so as to better reflect the effect of adding energy storage system, and then the charge-discharge response and SOC state mandatory regression strategy of the energy storage system are made. A maximum daily benefit-targeted optimal allocation model is established through building up the cost model of the energy storage system, AGC service revenue and increasing the effective revenue. At last, the response performance and benefit before and after adding the energy storage are analyzed through the optimal economic allocation of the energy storage system for a wind farm. The result shows that the optimal economic allocation method is reasonable and effective;from which the comprehensive performance benefit of the wind farm is increased by about 30% after adding the energy storage system. The study result has a larger referential value for the reasonable allocation of wind farm energy storage system in the days to come.
作者
曾鉴
袁川
朱觅
杨新婷
刘友波
ZENG Jian;YUAN Chuan;ZHU Mi;YANG Xinting;LIU Youbo(Economic and Technological Research Institute,State Grid Sichuan Electric Power Company,Chengdu 610041,Sichuan,China;States Grid Sichuan Electric Power Company,Chengdu 610041,Sichuan,China;College of Electrical Engineering and Information Technology,Sichuan University,Chengdu 610065,Sichuan,China)
出处
《水利水电技术》
北大核心
2019年第3期194-200,共7页
Water Resources and Hydropower Engineering
基金
国家电网公司科技项目(SGSCJY00GHJS1800021)
关键词
风电场
AGC服务
储能系统
混合优化
混沌蚁群算法
经济性
响应效能
可再生清洁能源
wind farm
AGC service
energy storage system
hybrid optimization
chaotic ant colony algorithm
economy
response efficiency
renewable clean energy
