跟踪风电计划偏差的风储系统联合控制策略
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摘要
风电固有的特性决定了其难以严格按合同要求出力、和传统能源直接竞争,因此,风电场必须提升相关技术以提高与合同计划出力的吻合度。以风电控制性能评价标准为准则,利用离散傅里叶变换(discrete Fourier transform,DFT)对风电场考核时间段内的输出功率偏差进行频谱分析,得出不同时间尺度的补偿功率需求,调用相应特性的储能设备分类调控风储系统的功率输出,满足市场竞争偏差要求;同时制定储能系统间的充放电规则,利用储能间互补平衡,减少能量型储能的深度放电的可能,避免储能系统过充过放。经某风电场典型日的负荷数据仿真验证,所采用的控制策略能较好地跟踪风电计划偏差,控制风电输出精度,有效减少储能系统的动作次数,提高电网对风电的接纳能力。
The inherent characteristics of wind power determine that it is difficult to strictly comply with contractual requirements and compete directly with traditional energy sources. Therefore, wind farms must upgrade related technologies to improve the compatibility with contract plans. This paper takes wind power control performance evaluation standard as criteria, uses discrete Fourier transform(DFT) to perform frequency spectrum analysis on output power deviation in the assessment period of the wind farm, and obtains power compensation requirements for different time scales. The characteristic energy storage equipment classification regulates the power output of the wind storage system and meets market competition deviation requirements. At the same time, it formulates charge-discharge rules among energy storage systems and uses complementary balance between energy storages to reduce possibility of deep discharge of energy-type storage and avoid the energy storage system overcharged or over-discharged. Based on a typical day's load data simulation of a wind farm, it is proved that the adopted control strategy can better track the deviation of the wind power plan, control the output accuracy of wind power, effectively reduce the operation times of the energy storage system, and improve the ability of the grid to accommodate wind power.
The inherent characteristics of wind power determine that it is difficult to strictly comply with contractual requirements and compete directly with traditional energy sources. Therefore, wind farms must upgrade related technologies to improve the compatibility with contract plans. This paper takes wind power control performance evaluation standard as criteria, uses discrete Fourier transform(DFT) to perform frequency spectrum analysis on output power deviation in the assessment period of the wind farm, and obtains power compensation requirements for different time scales. The characteristic energy storage equipment classification regulates the power output of the wind storage system and meets market competition deviation requirements. At the same time, it formulates charge-discharge rules among energy storage systems and uses complementary balance between energy storages to reduce possibility of deep discharge of energy-type storage and avoid the energy storage system overcharged or over-discharged. Based on a typical day's load data simulation of a wind farm, it is proved that the adopted control strategy can better track the deviation of the wind power plan, control the output accuracy of wind power, effectively reduce the operation times of the energy storage system, and improve the ability of the grid to accommodate wind power.
引文
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[15]李滨,吴思缘,阳育德,等.大型风电场的控制性能评价标准及储能控制策略研究[J].中国电机工程学报,2017,37(16):4691-4698.Li Bin,Wu Siyuan,Yang Yude,et al.A research on the control performance standard and energy storage control strategy for large scale wind farms[J].Proceedings of the CSEE,2017,37(16):4691-4698(in Chinese).
[2]施琳,罗毅,施念,等.高渗透率风电-储能孤立电网控制策略[J].中国电机工程学报,2013,33(16):78-85,15.Shi Lin,Luo Yi,Shi Nian,et al.A control strategy of isolated grid with high penetration of wind and energy storage systems[J].Proceedings of the CSEE,2013,33(16):78-85,15(in Chinese).
[3]罗煜,黄梅,鲍谚,等.基于储能SOC优化控制的风储电站实时跟踪发电计划控制策略[J].电工技术学报,2016,31(S1):214-220.Luo Yu,Huang Mei,Bao Yan,et al.Tracking power generation real-time schedule strategy for wind power and battery energy storage combined system based on SOC optimal control of battery energy storage[J].Transactions of China Electrotechnical Society,2016,31(S1):214-220(in Chinese).
[4]戚永志,刘玉田.风光储联合系统输出功率滚动优化与实时控制[J].电工技术学报,2014,29(8):265-273.Qi Yongzhi Liu Yutian.Output power rolling optimization and real-time control in wind-photovoltaic-storage hybrid system[J].Transactions of China Electrotechnical Society,2014,29(8):265-273(in Chinese).
[5]黄杨,胡伟,闵勇,等.考虑日前计划的风储联合系统多目标协调调度[J].中国电机工程学报,2014,34(28):4743-4751.Huang Yang,Hu Wei,Min Yong,et al.Multi-objective coordinative dispatch for wind-storage combined systems considering day-ahead generation schedules[J].Proceedings of the CSEE,2014,34(28):4743-4751(in Chinese).
[6]柴炜,李征,蔡旭,等.基于使用寿命模型的大容量电池储能系统变步长优化控制方法[J].电工技术学报,2016,31(14):58-66.Chai Wei,Li Zheng,Cai Xu,et al.Variable step-size control method of large capacity battery energy storage system based on the life model[J].Transactions of China Electrotechnical Society,2016,31(14):58-66(in Chinese).
[7]桑丙玉,陶以彬,郑高,等.超级电容-蓄电池混合储能拓扑结构和控制策略研究[J].电力系统保护与控制,2014,42(2):1-6.Sang Bingyu,Tao Yibin,Zheng Gao,et al.Research on topology and control strategy of the super-capacitor and battery hybrid energy storage[J].Power System Protection and Control,2014,42(2):1-6(in Chinese).
[8]吴冠男,张明理,徐建源,等.考虑抗扰性能的风电混合储能系统协调控制策略研究[J].电力系统保护与控制,2017,45(22):164-169.Wu Guannan,Zhang Mingli,Xu Jianyuan,et al,Study on coordination control of wind power hybrid energy storage system in consideration of anti-disturbance performance[J].Power System Protection and Control,2017,45(22):164-169(in Chinese).
[9]孙承晨,袁越,CHOI San Shing,等.用于能量调度的风-储混合系统运行策略及容量优化[J].电网技术,2015,39(8):2107-2114.Sun Chengchen,Yuan Yue,Choi San Shing,et al.Capacity optimization and operational strategy of the wind-energy storage hybrid systems for energy dispatching[J].Power System Technology,2015,39(8):2107-2114(in Chinese).
[10]田崇翼,李珂,严毅,等.基于经验模式分解的风电场多时间尺度复合储能控制策略[J].电网技术,2015,39(8):2167-2172.Tian Chongyi,Li Ke,Yan Yi,et al.A multi-time scale control strategy of hybrid energy storage system in wind farm based on empirical mode decomposition[J].Power System Technology,2015,39(8):2167-2172(in Chinese).
[11]史林军,周佳佳,温荣超,等.基于经验模态分解与小波分析相结合的风电功率平滑控制[J].电力系统保护与控制,2016,44(24):9-16.Shi Linjun,Zhou Jiajia,Wen Rongchao,et al.Power smoothing control of wind power based on combination of empirical mode decomposition and wavelet analysis[J].Power System Protection and Control,2016,44(24):9-16(in Chinese).
[12]王晛,黄蒙涛,张少华.考虑风电投标偏差惩罚的电力市场均衡分析[J].电网技术,2016,40(2):602-607.Wang Xian,Huang Mengtao,Zhang Shaohua.Equilibrium analysis of electricity market considering penalties for wind power’s bidding deviation[J].Power System Technology,2016,40(2):602-607(in Chinese).
[13]高飞,杨凯,惠东,等.储能用磷酸铁锂电池循环寿命的能量分析[J].中国电机工程学报,2013,33(5):41-45,8.Gao Fei,Yang Kai,Hui Dong,et al.Cycle-life energy analysis of LiFePO4 batteries for energy storage[J].Proceedings of the CSEE,2013,33(5):41-45,8(in Chinese).
[14]李滨,陈姝,韦化.风电场储能容量优化的频谱分析方法[J].中国电机工程学报,2015,35(9):2128-2134.Li Bin,Chen Shu,Wei Hua.Optimization of energy storage capacity based on spectral analysis for wind farm[J].Proceedings of the CSEE,2015,35(9):2128-2134(in Chinese).
[15]李滨,吴思缘,阳育德,等.大型风电场的控制性能评价标准及储能控制策略研究[J].中国电机工程学报,2017,37(16):4691-4698.Li Bin,Wu Siyuan,Yang Yude,et al.A research on the control performance standard and energy storage control strategy for large scale wind farms[J].Proceedings of the CSEE,2017,37(16):4691-4698(in Chinese).