含先进绝热压缩空气储能电站的电力系统实时调度模型
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摘要
先进绝热压缩空气储能(AA-CAES)具有规模大、成本低、无需燃料、效率高等优点,是压缩空气储能(CAES)技术领域的主流发展趋势之一。本文将AA-CAES电站作为重要的调度资源,与常规机组、风电共同参与电力系统实时调度。首先,基于AA-CAES电站的热力学特性,建立能够反映AA-CAES电站变工况条件下运行特性的储能电站运行约束模型。然后,考虑AACAES电站在自动发电控制(AGC)阶段的功率调节不确定性,建立AA-CAES电站AGC约束模型。在此基础上,提出含AA-CAES电站的电力系统实时调度模型,该模型考虑了系统AGC容量需求约束、AGC调节速率需求约束和AGC调节任务量需求约束。最后,基于修改版IEEE30节点系统进行算例仿真,仿真结果证明了调度模型的有效性。
Advanced adiabatic compressed air energy storage(AA-CAES) has the merits of large-scale,low-costs,no fossil fuel,and high efficiency,etc.It is one of the mainstream development trends of the compressed air energy storage(CAES) technology.This paper took the AA-CAES as an important scheduling resource,to participate in power system real-time dispatch together with thermal power generators and a wind power plant.Firstly,based on the thermodynamic characteristics of the AA-CAES plant,the operation constraints of AA-CAES,which can reflect the AA-CAES operation characteristics under off-design conditions,were established.After that,the automatic generation control(AGC) constraints of the AA-CAES plant were established considering the power regulation uncertainty in the AGC stage.As a result,the real-time dispatch model for the power system with AA-CAES was established.In the model,the system AGC capacity demand,the AGC regulation rate demand and the AGC regulation task demand were considered.Finally,the simulation test was applied on the modified IEEE 30-bus system,which verified the dispatch model.
Advanced adiabatic compressed air energy storage(AA-CAES) has the merits of large-scale,low-costs,no fossil fuel,and high efficiency,etc.It is one of the mainstream development trends of the compressed air energy storage(CAES) technology.This paper took the AA-CAES as an important scheduling resource,to participate in power system real-time dispatch together with thermal power generators and a wind power plant.Firstly,based on the thermodynamic characteristics of the AA-CAES plant,the operation constraints of AA-CAES,which can reflect the AA-CAES operation characteristics under off-design conditions,were established.After that,the automatic generation control(AGC) constraints of the AA-CAES plant were established considering the power regulation uncertainty in the AGC stage.As a result,the real-time dispatch model for the power system with AA-CAES was established.In the model,the system AGC capacity demand,the AGC regulation rate demand and the AGC regulation task demand were considered.Finally,the simulation test was applied on the modified IEEE 30-bus system,which verified the dispatch model.
引文
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[14]Li Rui,Chen Laijun,Yuan Tiejiang,et al.Optimal dispatch of zero-carbon-emission micro energy internet integrated with non-supplementary fired compressed air energy storage system[J].Journal of Modern Power Systems&Clean Energy,2016,4(4):566-580.
[15]于丹文,杨明,韩学山,等.计及风电概率分布特征的鲁棒实时调度方法[J].中国电机工程学报,2017,37(3):727-737.Yu Danwen,Yang Ming,Han Xueshan,et al.Robust real-time dispatch considering probabilistic distribution of wind generation[J].Proceedings of the CSEE,2017,37(3):727-737.
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[18]薛小代,陈晓弢,梅生伟,等.采用熔融盐蓄热的非补燃压缩空气储能发电系统性能[J].电工技术学报,2016,31(14):11-20.Xue Xiaodai,Chen Xiaotao,Mei Shengwei,et al.Performance of non-supplementary fired compressed air energy storage with molten salt heat storage[J].Transactions of China Electrotechnical Society,2016,31(14):11-20.
[19]Crotogino F,Mohmeyer K U,Scharf R.Huntorf CAES:More than 20 years of successful operation[C]//Proceedings of Solution Mining Research Institude Meeting,Orlando,USA,2001:1-6.
[20]陈大宇,张粒子,马历.储能参与的AGC市场出清优化建模新方法[J].电力系统自动化,2014,38(13):79-84.Chen Dayu,Zhang Lizi,Ma Li.A new optimization method for AGC market clearing considering energy storage systems[J].Automation of Electric Power Systems,2014,38(13):79-84.
[21]段翩,朱建全,刘明波.基于双层模糊机会约束规划的虚拟电厂优化调度[J].电工技术学报,2016,31(9):58-67.Duan Pian,Zhu Jianquan,Liu Mingbo.Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J].Transactions of China Electrotechnical Society,2016,31(9):58-67.
[22]罗超,杨军,孙元章,等.考虑备用容量优化分配的含风电电力系统动态经济调度[J].中国电机工程学报,2014,34(34):6109-6118.Luo Chao,Yang Jun,Sun Yuanzhang,et al.Dynamic economic dispatch of wind integrated power system considering optimal scheduling of reserve capacity[J].Proceedings of the CESS,2014,34(34):6109-6118.
[23]Li Zhigang,Wu Wenchuan,Zhang Boming,et al.Adjustable robust real-time power dispatch with largescale wind power integration[J].IEEE Transactions on Sustainable Energy,2015,6(2):357-368.
[24]翟鹤峰,杨明,王栋,等.计及注入转移分布因子估计误差的鲁棒实时调度[J].电工技术学报,2017,32(14):217-228.Zhai Hefeng,Yang Ming,Wang Dong,et al.Robust real-time dispatch considering the injection shift factor estimation errors[J].Transactions of China Electrotechnical Society,2017,32(14):217-228.
[25]宋卓然,赵琳,张子信,等.热电联产与风电机组联合运行滚动优化调度模型[J].电力系统保护与控制,2016,44(24):110-116.Song Zhuoran,Zhao Lin,Zhang Zixin,et al.Rolling optimal model for multiple heating source and wind turbine unit[J].Power System Protection and Control,2016,44(24):110-116.
[26]赵冬梅,殷加玞.考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J].电工技术学报,2018,33(5):1076-1085.Zhao Dongmei,Yin Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering source-side and load-side uncertainty[J].Transactions of China Electrotechnical Society,2018,33(5):1076-1085.
[2]许汉平,李姚旺,苗世洪,等.考虑可再生能源消纳效益的电力系统“源-荷-储”协调互动优化调度策略[J].电力系统保护与控制,2017,45(17):18-25.Xu Hanping,Li Yaowang,Miao Shihong,et al.Optimization dispatch strategy considering renewable energy consumptive benefits based on“source-loadenergy storage”coordination in power system[J].Power System Protection and Control,2017,45(17):18-25.
[3]Chen Laijun,Zheng Tianwen,Mei Shengwei,et al.Review and prospect of compressed air energy storage system[J].Journal of Modern Power Systems&Clean Energy,2016,4(4):529-541.
[4]Jakiel C,Zunft S,Nowi A.Adiabatic compressed air energy storage plants for efficient peak load power supply from wind energy:the European project AA-CAES[J].International Journal of Energy Technology&Policy,2007,5(3):296-306.
[5]Luo Xing,Wang Jihong,Krupke C,et al.Modelling study,efficiency analysis and optimisation of largescale adiabatic compressed air energy storage systems with low-temperature thermal storage[J].Applied Energy,2016,162:589-600.
[6]严毅,张承慧,李珂,等.含压缩空气的微网复合储能系统主动控制策略[J].电工技术学报,2017,32(20):231-240.Yan Yi,Zhang Chenhui,Li Ke,et al.An active control strategy for composited energy storage with compressed air energy storage in micro-grid[J].Transactions of China Electrotechnical Society,2017,32(20):231-240.
[7]Wang Jidai,Lu Kunpeng,Ma Lan,et al.Overview of compressed air energy storage and technology development[J].Energies,2017,991(10):1-22.
[8]Daneshi H,Srivastava A K.Security-constrained unit commitment with wind generation and compressed air energy storage[J].IET Generation Transmission&Distribution,2012,6(2):167-175.
[9]Abbaspour M,Satkin M,Mohammadi-Ivatloo B,et al.Optimal operation scheduling of wind power integrated with compressed air energy storage(CAES)[J].Renewable Energy,2013,51(51):53-59.
[10]Ghalelou A,Fakhri A,Nojavan S,et al.A stochastic self-scheduling program for compressed air energy storage(CAES)of renewable energy sources(RESs)based on a demand response mechanism[J].Energy Conversion&Management,2016,120:388-396.
[11]Shafiee S,Zareipour H,Knight A.Considering thermodynamic characteristics of a CAES facility in self-scheduling in energy and reserve markets[J].IEEETransactions on Smart Grid,2018,9(4):3476-3485.
[12]Easan Drury,Paul Denholm,Ramteen Sioshansi.The value of compressed air energy storage in energy and reserve markets[J].Energy,2011,36(8):4959-4973.
[13]Li Yaowang,Miao Shihong,Luo Xing,et al.Optimization model for the power system scheduling with wind generation and compressed air energy storage combination[C]//IEEE International Conference on Automation and Computing,Colchester,UK,2016:300-305.
[14]Li Rui,Chen Laijun,Yuan Tiejiang,et al.Optimal dispatch of zero-carbon-emission micro energy internet integrated with non-supplementary fired compressed air energy storage system[J].Journal of Modern Power Systems&Clean Energy,2016,4(4):566-580.
[15]于丹文,杨明,韩学山,等.计及风电概率分布特征的鲁棒实时调度方法[J].中国电机工程学报,2017,37(3):727-737.Yu Danwen,Yang Ming,Han Xueshan,et al.Robust real-time dispatch considering probabilistic distribution of wind generation[J].Proceedings of the CSEE,2017,37(3):727-737.
[16]Beaudin M,Zareipour H,Schellenberglabe A,et al.Energy storage for mitigating the variability of renewable electricity sources:an updated review[J].Energy for Sustainable Development,2010,14(4):302-314.
[17]张远.风电与先进绝热压缩空气储能技术的系统集成与仿真研究[D].北京:中国科学院研究生院(工程热物理研究所),2014.
[18]薛小代,陈晓弢,梅生伟,等.采用熔融盐蓄热的非补燃压缩空气储能发电系统性能[J].电工技术学报,2016,31(14):11-20.Xue Xiaodai,Chen Xiaotao,Mei Shengwei,et al.Performance of non-supplementary fired compressed air energy storage with molten salt heat storage[J].Transactions of China Electrotechnical Society,2016,31(14):11-20.
[19]Crotogino F,Mohmeyer K U,Scharf R.Huntorf CAES:More than 20 years of successful operation[C]//Proceedings of Solution Mining Research Institude Meeting,Orlando,USA,2001:1-6.
[20]陈大宇,张粒子,马历.储能参与的AGC市场出清优化建模新方法[J].电力系统自动化,2014,38(13):79-84.Chen Dayu,Zhang Lizi,Ma Li.A new optimization method for AGC market clearing considering energy storage systems[J].Automation of Electric Power Systems,2014,38(13):79-84.
[21]段翩,朱建全,刘明波.基于双层模糊机会约束规划的虚拟电厂优化调度[J].电工技术学报,2016,31(9):58-67.Duan Pian,Zhu Jianquan,Liu Mingbo.Optimal dispatch of virtual power plant based on bi-level fuzzy chance constrained programming[J].Transactions of China Electrotechnical Society,2016,31(9):58-67.
[22]罗超,杨军,孙元章,等.考虑备用容量优化分配的含风电电力系统动态经济调度[J].中国电机工程学报,2014,34(34):6109-6118.Luo Chao,Yang Jun,Sun Yuanzhang,et al.Dynamic economic dispatch of wind integrated power system considering optimal scheduling of reserve capacity[J].Proceedings of the CESS,2014,34(34):6109-6118.
[23]Li Zhigang,Wu Wenchuan,Zhang Boming,et al.Adjustable robust real-time power dispatch with largescale wind power integration[J].IEEE Transactions on Sustainable Energy,2015,6(2):357-368.
[24]翟鹤峰,杨明,王栋,等.计及注入转移分布因子估计误差的鲁棒实时调度[J].电工技术学报,2017,32(14):217-228.Zhai Hefeng,Yang Ming,Wang Dong,et al.Robust real-time dispatch considering the injection shift factor estimation errors[J].Transactions of China Electrotechnical Society,2017,32(14):217-228.
[25]宋卓然,赵琳,张子信,等.热电联产与风电机组联合运行滚动优化调度模型[J].电力系统保护与控制,2016,44(24):110-116.Song Zhuoran,Zhao Lin,Zhang Zixin,et al.Rolling optimal model for multiple heating source and wind turbine unit[J].Power System Protection and Control,2016,44(24):110-116.
[26]赵冬梅,殷加玞.考虑源荷双侧不确定性的模糊随机机会约束优先目标规划调度模型[J].电工技术学报,2018,33(5):1076-1085.Zhao Dongmei,Yin Jiafu.Fuzzy random chance constrained preemptive goal programming scheduling model considering source-side and load-side uncertainty[J].Transactions of China Electrotechnical Society,2018,33(5):1076-1085.