摘要
为了提高停电后电力系统负荷恢复效率,具有调控优势且响应速度快的储能参与系统恢复已经成为必然趋势。现有研究中,储能主要是作为可再生能源的辅助电源,平抑可再生能源出力波动;大规模储能也可作为黑启动电源,为待恢复机组提供启动功率。但上述研究都侧重于利用储能的输出功率,而忽略了储能调频能力在提高系统安全性方面的作用,未能更大程度地提高系统的恢复效率。为此,文中提出了考虑电网侧储能调频能力的电力系统负荷恢复策略。以恢复尽可能多的重要负荷为目标,考虑储能的功率特性、频率响应特性和其他安全约束,构建电力系统负荷恢复模糊机会约束模型;进一步通过清晰等价类将其转化为确定性0-1规划问题,并采用人工蜂群算法进行求解;以IEEE 39节点系统为例进行仿真分析,仿真结果表明文中所提策略能够提高负荷恢复效率。
In order to improve the efficiency of power system restoration after a power outage,it has become an inevitable trend that energy storage station which has advantages of fast response and frequency control is employed in system restoration.Currently,energy storage is mainly utilized as an auxiliary power source for renewable energy to smooth out fluctuations of renewable energy.Large-scale energy storage can also be utilized as black start power source to provide starting power for units to be restored.However,the above-mentioned studies have focused on the use of the output power of energy storage,while ignoring the role of energy storage and frequency modulation capabilities in improving system safety,thus failing to improve the recovery efficiency of the system to a greater extent.To this end a power system load restoration strategy that considers the power storage and frequency modulation capability is proposed.With the goal of restoring as many important loads as possible,a fuzzy chance constraint model for power system load restoration is constructed considering the power characteristics,frequency response characteristics and other safety constraints of energy storage.It is further transformed into a deterministic 0-1 programming problem through clear equivalence classes,and the artificial bee colony algorithm is employed to solve it.Taking the IEEE 39 system as an example for simulation analysis,the simulation results show that the strategy proposed in this paper improves the efficiency of load restoration.
作者
谢云云
李虹仪
崔红芬
XIE Yunyun;LI Hongyi;CUI Hongfen(School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China;China Electric Power Research Institute(Nanjing),Nanjing 210003,China)
出处
《电力工程技术》
北大核心
2021年第6期43-51,共9页
Electric Power Engineering Technology
基金
国家自然科学基金资助项目(52177090)。
关键词
负荷恢复
储能
频率调节
模糊机会约束
人工蜂群算法
可再生能源
load restoration
energy storage
frequency regulation
fuzzy chance constrained
artificial bee colony algorithm
renewable energy