基于多时空尺度协调的多源互补发电场群优化调度
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摘要
为了解决风光发电随机性和不确定性造成的严重弃风、弃光问题,在研究抽水蓄能电站、高载能负荷运行特性和消纳弃风弃光能力的基础上,提出了基于多时空尺度协调的多源互补发电场群优化调度策略。该策略将多源互补发电场群从时间和空间的角度各分三层进行控制,以系统运行成本最小、风光蓄发电利用率最大和系统输出功率波动最小为目标分别建立了日前、滚动、实时3个时间尺度的优化调度模型。通过滚动修正、实时调节来逐级降低风光预测误差及负荷不确定对调度计划的影响,提高调度精度。结合甘肃酒泉具体算例,验证了所提调度策略能够有效提高系统运行经济性,促进风光消纳。
In order to solve the problems of serious wind and solar power curtailment caused by the randomness and uncertainty of wind and solar power generation. Based on the study of pumped storage power station, high load-energy load operation characteristics and the ability to eliminate wind and solar power curtailment, this paper proposes an optimization scheduling method for multi-source complementary power plants group based on multiple temporal and spatial scales coordination. This strategy controls the multi-source complementary power generation group in three layers from the perspective of time and space, respectively. In this strategy, the multi-source complementary power plants group is controlled in three layers from the perspective of time and space, respectively. From three time scales, i.e., day-ahead, rolling and real-time, the optimal scheduling models are established with the goal of the minimum operating cost, the maximum utilization of wind and solar power storage and the minimum fluctuation of output power. Through rolling correction and real-time adjustment, the wind-solar forecasting error and the influence of load uncertainty on the scheduling plan are reduced stepwise to improve the scheduling accuracy. Combining with the specific example of Jiuquan, Gansu, it is verified that the proposed scheduling strategy can improve the economics of system operation effectively and promote the consumption of wind and solar.
In order to solve the problems of serious wind and solar power curtailment caused by the randomness and uncertainty of wind and solar power generation. Based on the study of pumped storage power station, high load-energy load operation characteristics and the ability to eliminate wind and solar power curtailment, this paper proposes an optimization scheduling method for multi-source complementary power plants group based on multiple temporal and spatial scales coordination. This strategy controls the multi-source complementary power generation group in three layers from the perspective of time and space, respectively. In this strategy, the multi-source complementary power plants group is controlled in three layers from the perspective of time and space, respectively. From three time scales, i.e., day-ahead, rolling and real-time, the optimal scheduling models are established with the goal of the minimum operating cost, the maximum utilization of wind and solar power storage and the minimum fluctuation of output power. Through rolling correction and real-time adjustment, the wind-solar forecasting error and the influence of load uncertainty on the scheduling plan are reduced stepwise to improve the scheduling accuracy. Combining with the specific example of Jiuquan, Gansu, it is verified that the proposed scheduling strategy can improve the economics of system operation effectively and promote the consumption of wind and solar.
引文
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[11]吴云亮,孙元章,徐箭,等.基于饱和控制理论的储能装置容量配置方法[J].中国电机工程学报,2011,31(22):32-39.WU Yunliang,SUN Yuanzhang,XU Jian,et al.Determination methodology for energy storage capacity based on saturation control theory[J].Proceedings of the CSEE,2011,31(22):32-39.
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[18]盛四清,张立.基于风光水火多能互补的电力系统经济调度[J].电测与仪表,2017,53(22):66-71.SHENG Siqing,ZHANG Li.An economical scheduling strategy in power system based on integration of wind,photovoltaic,water and thermal power[J].Electrical Measurement and Instrumentation,2017,53(22):66-71.
[19]陈巨龙,赵翔宇.基于增量表达式的滚动发电计划模型与其求解算法研究[J].软件工程师,2014(1):45-49.CHEN Julong,ZHAO Xiangyu.Study of rolling generation scheduling model based on an increment expression and its efficient algorithm[J].Software Engineer,2014(1):45-49.
[20]王功臣,邓长虹,夏沛,等.考虑机组优化选取的含风电电网滚动优化调度方法[J].电力系统自动化,2017,41(11):55-60.WANG Gongchen,DENG Changhong,XIA Pei,et al.Rolling optimization dispatching method of power grid containing wind power with units optimal selection taken into account[J].Automation of Electric Power Systems,2017,41(11):55-60.
[21]王魁,张步涵,闫大威,等.含大规模风电的电力系统多时间尺度滚动协调调度方法研究[J].电网技术,2014,38(9):2434-2440.WANG Kui,ZHANG Buhan,YAN Dawei,et al.Amulti-time scale rolling coordination scheduling method for power grid integrated with large scale wind farm[J].Power System Technology,2014,38(9):2434-2440.
[22]董朕,殷豪,孟安波.基于混合算法优化的短期风功率预测[J].智慧电力,2017,45(11):24-30.DONG Zhen,YIN Hao,MENG Anbo.Short-term wind power forecasting based on kernel extreme learning machine optimized by hybrid algorithm[J].Smart Power,2017,45(11):24-30.
[23]夏鹏,刘文颖,蔡万通,等.基于风电离散化概率序列的机会约束规划优化调度方法[J].电工技术学报,2018,33(21):5069-5079.XIA Peng,LIU Wenying,CAI Wantong,et al.Optimal scheduling method of chance constrained programming based on discrete wind power probability sequences[J].Transactions of China Electrotechnical Society,2018,33(21):5069-5079.
[24]郭鹏,文晶,朱丹丹,等.基于源-荷互动的大规模风电消纳协调控制策略[J].电工技术学报,2017,32(3):1-9.GUO Peng,WEN Jing,ZHU Dandan,et al.The coordination control strategy for large-scale wind power consumption based on source-load interactive[J].Transactions of China Electrotechnical Society,2017,32(3):1-9.
[25]王昭.多能互补系统中电价机制对电加热功率配置及运行的影响分析[J].智慧电力,2018,46(7):23-28.WANG Zhao.Study on the influence of electricity price mechanism on configuration and operation of electric heating power in multiple energy complementary system[J].Smart Power,2018,46(7):23-28.
[26]易文飞,张艺伟,曾博,等.多形态激励型需求侧响应协同平衡可再生能源波动的鲁棒优化配置[J].电工技术学报,2018,33(23):5541-5554.YI Wenfei,ZHANG Yiwei,ZENG Bo,et al.Robust optimization allocation for multi-type incentive-based demand response collaboration to balance renewable energy fluctuations[J].Transactions of China Electrotechnical Society,2018,33(23):5541-5554.
[27]邓佳乐,胡林献,邵世圻,等.电热联合系统多时间尺度滚动调度策略[J].电网技术,2016,40(12):3796-3803.DENG Jiale,HU Linxian,SHAO Shiqi,et al.Multi-time scale rolling scheduling method for combined heat and power system[J].Power System Technology,2016,40(12):3796-3803.
[28]TING T O,RAO M V C,LOO C K.A novel approach for unit commitment problem via an effective hybrid particle swarm optimization[J].IEEE Transactions on Power Systems,2006,21(1):411-418.
[2]刘吉臻.大规模新能源电力安全高效利用基础问题[J].中国电机工程学报,2013,33(16):1-8,25.LIU Jizhen.Basic issues of the utilization of large-scale renewable power with high security and efficiency[J].Proceedings of the CSEE,2013,33(16):1-8,25.
[3]曹宇,汪可友,石文辉,等.风-光-海水抽蓄联合发电系统的调度策略研究[J].电力系统保护与控制,2018,46(2):16-23.CAO Yu,WANG Keyou,SHI Wenhui,et al.Study on dispatching strategies of a wind-solar-seawater pumped storage hybrid power system[J].Power System Protection and Control,2018,46(2):16-23.
[4]李文锋,张健,卜广全,等.抽蓄电站和经多端柔性直流电网接入的大规模新能源间的协调互补优化控制方案[J].电力系统保护与控制,2017,45(23):130-135.LI Wenfeng,ZHANG Jian,BU Guangquan,et al.Acoordinate complementary optimization control scheme between pumped storage station and large-scale new renewable integrated through VSC-MTDC[J].Power System Protection and Control,2017,45(23):130-135.
[5]张川,杨雷,牛童阳,等.平抑风电出力波动储能技术比较及分析[J].电力系统保护与控制,2015,43(7):149-154.ZHANG Chuan,YANG Lei,NIU Tongyang,et al.Comparison and analysis of energy storage technology to balance fluctuation of wind power output[J].Power System Protection and Control,2015,43(7):149-154.
[6]贾文昭,康重庆,李丹,等.基于日前风功率预测的风电消纳能力评估方法[J].电网技术,2012,36(8):69-75.JIA Wenzhao,KANG Chongqing,LI Dan,et al.Evaluation on capability of wind power accommodation based on its day-ahead forecasting[J].Power System Technology,2012,36(8):69-75.
[7]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(增刊1):9-16.ZHAO Shuqiang,WANG Yang,XU Yan.Dependent chance programming dispatching of integrated thermal power generation and energy storage system based on wind power forecasting error[J].Proceedings of the CSEE,2014,34(S1):9-16.
[8]HETZER J,DAVID C,BHATTARAI K.An economic dispatch model incorporating wind power[J].IEEETransactions on Power Energy Conversion,2008,23(2):603-611.
[9]吕翔,刘国静,周莹.含抽水蓄能的风水火联合机组组合研究[J].电力系统保护与控制,2017,45(12):35-43.LüXiang,LIU Guojing,ZHOU Ying.Research on combined unit commitment of wind power-hydro powerthermal power for the power system with pumped hydro storage[J].Power System Protection and Control,2017,45(12):35-43.
[10]李碧辉,申洪,汤涌,等.风光储联合发电系统储能容量对有功功率的影响及评价指标[J].电网技术,2011,35(4):123-128.LI Bihui,SHEN Hong,TANG Yong,et al.Impacts of energy storage capacity configuration of HPWS to active power characteristics and its relevant indices[J].Power System Technology,2011,35(4):123-128.
[11]吴云亮,孙元章,徐箭,等.基于饱和控制理论的储能装置容量配置方法[J].中国电机工程学报,2011,31(22):32-39.WU Yunliang,SUN Yuanzhang,XU Jian,et al.Determination methodology for energy storage capacity based on saturation control theory[J].Proceedings of the CSEE,2011,31(22):32-39.
[12]杨珺,张建成,桂勋.并网风光发电中混合储能系统容量优化配置[J].电网技术,2013,37(5):1209-1216.YANG Jun,ZHANG Jiancheng,GUI Xun.Capacity optimization of hybrid energy storage system in grid-connected wind and PV power generation system[J].Power System Technology,2013,37(5):1209-1216.
[13]LI Jinghua,WANG Sai,YE Liu,et al.A coordinated dispatch method with pumped-storage and battery-storage for compensating the variation of wind power[J].Protection and Control of Modern Power Systems,2018,3(3):21-34.DOI:10.1186/s41601-017-0074-9.
[14]CASTRONUOVO E D,LOPES J A P.On the optimization of the daily operation of a wind-hydro power plant[J].IEEE Transactions on Power Systems,2004,19(3):1599-1606.
[15]刘芳,潘毅,杨军峰,等.风电-火电-抽水蓄能联合优化机组组合模型[J].中国电机工程学报,2015,35(4):766-775.LIU Fang,PAN Yi,YANG Junfeng,et al.Combination model of wind power-thermal power-pumped storage combined optimization[J].Proceedings of the CSEE,2015,35(4):766-775.
[16]黄庶,林舜江,刘明波.含风电场和抽水蓄能电站的多目标安全约束动态优化调度[J].中国电机工程学报,2016,36(1):112-121.HUANG Shu,LIN Shunjiang,LIU Mingbo.Multi-objective security constrained dynamic optimal dispatch with wind farms and pumped storage stations[J].Proceedings of the CSEE,2016,36(1):112-121.
[17]胡泽春,丁华杰,孔涛.风电-抽水蓄能联合日运行优化调度模型[J].电力系统自动化,2012,36(2):36-41.HU Zechun,DING Huajie,KONG Tao.A joint daily operational optimization model for wind power and pumped-storage plant[J].Automation of Electric Power Systems,2012,36(2):36-41.
[18]盛四清,张立.基于风光水火多能互补的电力系统经济调度[J].电测与仪表,2017,53(22):66-71.SHENG Siqing,ZHANG Li.An economical scheduling strategy in power system based on integration of wind,photovoltaic,water and thermal power[J].Electrical Measurement and Instrumentation,2017,53(22):66-71.
[19]陈巨龙,赵翔宇.基于增量表达式的滚动发电计划模型与其求解算法研究[J].软件工程师,2014(1):45-49.CHEN Julong,ZHAO Xiangyu.Study of rolling generation scheduling model based on an increment expression and its efficient algorithm[J].Software Engineer,2014(1):45-49.
[20]王功臣,邓长虹,夏沛,等.考虑机组优化选取的含风电电网滚动优化调度方法[J].电力系统自动化,2017,41(11):55-60.WANG Gongchen,DENG Changhong,XIA Pei,et al.Rolling optimization dispatching method of power grid containing wind power with units optimal selection taken into account[J].Automation of Electric Power Systems,2017,41(11):55-60.
[21]王魁,张步涵,闫大威,等.含大规模风电的电力系统多时间尺度滚动协调调度方法研究[J].电网技术,2014,38(9):2434-2440.WANG Kui,ZHANG Buhan,YAN Dawei,et al.Amulti-time scale rolling coordination scheduling method for power grid integrated with large scale wind farm[J].Power System Technology,2014,38(9):2434-2440.
[22]董朕,殷豪,孟安波.基于混合算法优化的短期风功率预测[J].智慧电力,2017,45(11):24-30.DONG Zhen,YIN Hao,MENG Anbo.Short-term wind power forecasting based on kernel extreme learning machine optimized by hybrid algorithm[J].Smart Power,2017,45(11):24-30.
[23]夏鹏,刘文颖,蔡万通,等.基于风电离散化概率序列的机会约束规划优化调度方法[J].电工技术学报,2018,33(21):5069-5079.XIA Peng,LIU Wenying,CAI Wantong,et al.Optimal scheduling method of chance constrained programming based on discrete wind power probability sequences[J].Transactions of China Electrotechnical Society,2018,33(21):5069-5079.
[24]郭鹏,文晶,朱丹丹,等.基于源-荷互动的大规模风电消纳协调控制策略[J].电工技术学报,2017,32(3):1-9.GUO Peng,WEN Jing,ZHU Dandan,et al.The coordination control strategy for large-scale wind power consumption based on source-load interactive[J].Transactions of China Electrotechnical Society,2017,32(3):1-9.
[25]王昭.多能互补系统中电价机制对电加热功率配置及运行的影响分析[J].智慧电力,2018,46(7):23-28.WANG Zhao.Study on the influence of electricity price mechanism on configuration and operation of electric heating power in multiple energy complementary system[J].Smart Power,2018,46(7):23-28.
[26]易文飞,张艺伟,曾博,等.多形态激励型需求侧响应协同平衡可再生能源波动的鲁棒优化配置[J].电工技术学报,2018,33(23):5541-5554.YI Wenfei,ZHANG Yiwei,ZENG Bo,et al.Robust optimization allocation for multi-type incentive-based demand response collaboration to balance renewable energy fluctuations[J].Transactions of China Electrotechnical Society,2018,33(23):5541-5554.
[27]邓佳乐,胡林献,邵世圻,等.电热联合系统多时间尺度滚动调度策略[J].电网技术,2016,40(12):3796-3803.DENG Jiale,HU Linxian,SHAO Shiqi,et al.Multi-time scale rolling scheduling method for combined heat and power system[J].Power System Technology,2016,40(12):3796-3803.
[28]TING T O,RAO M V C,LOO C K.A novel approach for unit commitment problem via an effective hybrid particle swarm optimization[J].IEEE Transactions on Power Systems,2006,21(1):411-418.