考虑火电深度调峰的电力系统低碳发电优化研究
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摘要
在低碳电力的背景下,风电接入系统成为节能减排的有效途径,基于此,电力系统加大火电机组调峰深度,增大下调备用空间,将是应对风电出力不确定性的重要举措之一。基于转子的低周疲劳损耗,建立火电机组深度调峰(deep peak regulation, DPR)的寿命损耗成本模型;考虑机组深度调峰引起的碳排放增量和不同碳排放区间下碳交易价格系数的变化,建立阶梯型碳交易成本模型;以总成本最低为目标,建立电力系统低碳优化调度模型。基于算例分析证明所提方法的合理性与有效性。
Under the background of low-carbon power, wind power accessing systems have become an effective way to save energy and reduce emissions. Based on this, the power system increases the peaking depth of the thermal power unit to enlarge the reserve space, which will be one of the important measures to deal with the uncertainty of wind power output. Based on the low cycle fatigue loss of the rotor, the life loss cost model of the deep peak regulation(DPR) of the thermal power unit is established. Considering the change of the carbon transaction price coefficient under different carbon emission intervals, a ladder carbon transaction cost model is established. With the goal of minimizing the overall cost of system power supply,a low-carbon optimal scheduling model for power systems is established. The rationality and effectiveness of the proposed method are proved by numerical results.
Under the background of low-carbon power, wind power accessing systems have become an effective way to save energy and reduce emissions. Based on this, the power system increases the peaking depth of the thermal power unit to enlarge the reserve space, which will be one of the important measures to deal with the uncertainty of wind power output. Based on the low cycle fatigue loss of the rotor, the life loss cost model of the deep peak regulation(DPR) of the thermal power unit is established. Considering the change of the carbon transaction price coefficient under different carbon emission intervals, a ladder carbon transaction cost model is established. With the goal of minimizing the overall cost of system power supply,a low-carbon optimal scheduling model for power systems is established. The rationality and effectiveness of the proposed method are proved by numerical results.
引文
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[16]卢志刚,郭凯,闫桂红,等.考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度[J].电力系统自动化,2017,41(15):58-65.Lu Zhigang,Guo Kai,Yan Guihong,et al.Optimized scheduling of wind power system based on demand response for virtual machines and carbon trading[J].Automation of Electric Power Systems,2017,41(15):58-65(in Chinese).
[17]吕梦璇,娄素华,刘建琴,等.含高比例风电的虚拟电厂多类型备用协调优化[J].中国电机工程学报,2018,38(10):2874-2882.Lyu Mengxuan,Lou Suhua,Liu Jianqin,et al.Multi-type standby coordination optimization of virtual power plants with high proportion of wind power[J].Proceedings of the CSEE,2018,38(10):2874-2882(in Chinese).
[2]邹金,赖旭,汪宁渤.风电随机出力的时间序列模型[J].电网技术,2014,38(9):2416-2421.Zou Jin,Lai Xu,Wang Ningbo.Time series model of wind power random output[J].Power System Technology,2014,38(9):2416-2421(in Chinese).
[3]Shi J,Lee WJ.Weighted parallel algorithm to improve the performance of short-term wind power forecasting[C].Power&Energy Society General Meeting.IEEE,2012:1-6.
[4]赵书强,王扬,徐岩.基于风电预测误差随机性的火储联合相关机会规划调度[J].中国电机工程学报,2014,34(S1):9-16.Zhao Shuqiang,Wang Yang,Xu Yan.Combined storage and scheduling of fire storage based on randomness of wind power forecasting error[J].Proceedings of the CSEE,2014,34(S1):9-16(in Chinese).
[5]林俐,邹兰青,周鹏,等.规模风电并网条件下火电机组深度调峰的多角度经济性分析[J].电力系统自动化,2017,41(7):21-27.Lin Li,Zou Lanqing,Zhou Peng,et al.Multi-angle economic analysis of thermal power plant deep peak shaving under grid wind power grid conditions[J].Automation of Electric Power Systems,2017,41(7):21-27(in Chinese).
[6]张程飞,袁越,张新松,等.考虑碳排放配额影响的含风电系统日前调度计划模型[J].电网技术,2014,38(8):2114-2120.Zhang Chengfei,Yuan Yue,Zhang Xinsong,et al.Model of daylight dispatching plan for wind power system considering carbon emission quota[J].Power System Technology,2014,38(8):2114-2120(in Chinese).
[7]卢志刚,隋玉珊,冯涛,等.考虑储热装置与碳捕集设备的风电消纳低碳经济调度[J].电工技术学报,2016,31(17):41-51.Lu Zhigang,Sui Yushan,Feng Tao,et al.Wind power consumption and low carbon economic dispatching considering heat storage device and carbon capture equipment[J].Transactions of China Electrotechnical Society,2016,31(17):41-51(in Chinese).
[8]秦婷,刘怀东,王锦桥,等.基于碳交易的电-热-气综合能源系统低碳经济调度[J].电力系统自动化,2018,42(14):8-13+22.Qin Ting,Liu Huaidong,Wang Jinqiao,et al.Low carbon economic dispatch of electric-heat-gas integrated energy system based on carbon trading[J].Automation of Electric Power System,2018,42(14):8-13+22(in Chinese).
[9]张保衡.大容量火电机组寿命管理与调峰运行[M].水利电力出版社,1988.Zhang Baoheng.Life management and peaking operation of large capacity thermal power units[M].Water Resources and Electric Power Press,1988(in Chinese).
[10]娄素华,胡斌,吴耀武,等.碳交易环境下含大规模光伏电源的电力系统优化调度[J].电力系统自动化,2014,38(17):91-97.Lou Suhua,Hu Bin,Wu Yaowu,et al.Power system optimization scheduling with large scale photovoltaic power supply in carbon trading environment[J].Automation of Electric Power Systems,2014,38(17):91-97(in Chinese).
[11]全国碳交易市场的配额分配方案(讨论稿)[E B/O L].[2017-06-02].http://www.cnenergynews.cn/hb/tpf/201706/t20170602_444547.html.
[12]丁华杰,宋永华,胡泽春,等.基于风电场功率特性的日前风电预测误差概率分布研究[J].中国电机工程学报,2013,33(34):136-144.Ding Huajie,Song Yonghua,Hu Zechun,et al.Study on probability distribution of forecasting errors of wind power forecast based on wind farm power characteristics[J].Proceedings of the CSEE,2013,33(34):136-144(in Chinese).
[13]Zhang N,Kang C,Xia Q,et al.A convex model of risk-based unit commitment for day-ahead market clearing considering wind power uncertainty[J].IEEE Transactions on Power Systems,2015,30(3):1582-1592.
[14]Wang G,You D,Lou S,et al.Economic valuation of low-load operation with auxiliary firing of coal-fired units[J].Energies,2017,10,1037.
[15]李一铭,李文沅,颜伟,等.基于机会约束规划模型降低机组寿命损耗的日调度计划[J].电网技术,2014,38(7):1885-1890.Li Yiming,Li Wenyuan,Yan Wei,et al.Daily dispatching plan for reducing unit life loss based on chance constrained programming model[J].Power System Technology,2014,38(7):1885-1890(in Chinese).
[16]卢志刚,郭凯,闫桂红,等.考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度[J].电力系统自动化,2017,41(15):58-65.Lu Zhigang,Guo Kai,Yan Guihong,et al.Optimized scheduling of wind power system based on demand response for virtual machines and carbon trading[J].Automation of Electric Power Systems,2017,41(15):58-65(in Chinese).
[17]吕梦璇,娄素华,刘建琴,等.含高比例风电的虚拟电厂多类型备用协调优化[J].中国电机工程学报,2018,38(10):2874-2882.Lyu Mengxuan,Lou Suhua,Liu Jianqin,et al.Multi-type standby coordination optimization of virtual power plants with high proportion of wind power[J].Proceedings of the CSEE,2018,38(10):2874-2882(in Chinese).