高比例风电系统的优化调度方法
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摘要
高比例风电的接入给系统优化调度带来了严峻的挑战。为促进高比例风电的消纳,建立了综合考虑发电成本和弃风成本的鲁棒机组组合模型;同时针对风电的空间集群效应和时间平滑效应,构建了考虑风电空间和时间约束的不确定集;此外为克服模型的求解难度,提出了分层列和约束生成算法,该算法将模型分解为3层优化问题予以求解,即第1层发电成本最小化的机组组合优化层,第2层安全可行性检验层,第3层风电最大化利用层,其中第2层向第1层反馈可行性割集,而第3层向第1层反馈风电消纳的割集,通过协调优化,以确保得到既能够应对的风电随机波动又促进风电充分利用的调度方案。最后结合修改后的IEEE 39节点算例进行了仿真,结果表明:考虑风电时空约束的模型降低了鲁棒优化的保守性,同时模型中加入弃风惩罚成本后提高了调度模型对高比例风电接入的适用性,此外所提算法能够有效地提升鲁棒机组组合的求解效率。
High proportion wind power poses serious challenges to optimal system scheduling. In order to cope with the problem of accommodation of high proportion wind power, a novel robust unit commitment model considering generation cost and wind curtailment cost is proposed. An uncertainty set is introduced to depict wind power fluctuation, and temporal smoothing effect and spatial clustering effect are taken into account to describe the spatial and temporal constraints of wind power. Besides, in order to overcome the difficulty of solving the model, a hierarchical column and constraint generation algorithm is proposed, decomposing the model into a three-layer optimization problem. The first layer is unit commitment optimization with minimum power generation cost, the second layer is feasibility security test, and the third layer is maximum wind power utilization. Among them, the second layer feeds back feasibility cut set to the first layer, and the third layer feeds back wind power accommodation cut set to the first layer, through coordination, to ensure a scheduling scheme able to cope with wind stochastic volatility and promote full use of wind power. Finally, simulation of a modified IEEE 39-bus system is carried out. The simulation results show that, the model considering the spatial and temporal constraints of wind power reduces conservativeness of robust optimization. Meanwhile, the penalty cost of wind curtailment is added into the model to improve applicability of the wind power model and ability of wind power accommodation. The proposed algorithm can effectively improve efficiency of the robust unit commitment.
High proportion wind power poses serious challenges to optimal system scheduling. In order to cope with the problem of accommodation of high proportion wind power, a novel robust unit commitment model considering generation cost and wind curtailment cost is proposed. An uncertainty set is introduced to depict wind power fluctuation, and temporal smoothing effect and spatial clustering effect are taken into account to describe the spatial and temporal constraints of wind power. Besides, in order to overcome the difficulty of solving the model, a hierarchical column and constraint generation algorithm is proposed, decomposing the model into a three-layer optimization problem. The first layer is unit commitment optimization with minimum power generation cost, the second layer is feasibility security test, and the third layer is maximum wind power utilization. Among them, the second layer feeds back feasibility cut set to the first layer, and the third layer feeds back wind power accommodation cut set to the first layer, through coordination, to ensure a scheduling scheme able to cope with wind stochastic volatility and promote full use of wind power. Finally, simulation of a modified IEEE 39-bus system is carried out. The simulation results show that, the model considering the spatial and temporal constraints of wind power reduces conservativeness of robust optimization. Meanwhile, the penalty cost of wind curtailment is added into the model to improve applicability of the wind power model and ability of wind power accommodation. The proposed algorithm can effectively improve efficiency of the robust unit commitment.
引文
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[4]陈皓勇,王锡凡.机组组合问题的优化方法综述[J].电力系统自动化,1999(4):51-56.Chen Haoyong,Wang Xifan.Review on optimization methods for unit commitment[J].Automation of Electric Power Systems,1999(4):51-56(in Chinese).
[5]王颖,周刚,韩红卫,等.计及风电最优置信度的机组组合优化方法[J].电网技术,2017,41(3):808-815.Wang Ying,Zhou Gang,Han Hongwei,et al.Unit commitment considering optimal confidence of wind power uncertainty[J].Power System Technology,2017,41(3):808-815(in Chinese).
[6]李本新,韩学山,蒋哲,等.应对风电间歇性的火电机组组合模型与分析[J].电网技术,2017,41(5):1569-1575.Li Benxin,Han Xueshan,Jiang Zhe,et al.Modeling and analysis of unit commitment to accommodate intermittent uncertainty[J].Power System Technology,2017,41(5):1569-1575(in Chinese).
[7]向红吉,戴朝华,明杰,等.考虑低谷时刻负调峰能力及风电预测区间的多目标机组组合优化研究[J].电网技术,2017,41(6):1912-1918.Xiang Hongji,Dai Chaohua,Ming Jie,et al.Research on multi-objective optimization of unit commitment considering negative peak load regulation ability in valley load period and wind power prediction interval[J].Power System Technology,2017,41(6):1912-1918(in Chinese).
[8]汪超群,韦化,吴思缘.计及风电不确定性的随机安全约束机组组合[J].电网技术,2017,41(5):1419-1427.Wang Chaoqun,Wei Hua,Wu Siyuan.Stochastic-security-constrained unit commitment considering uncertainty of wind power[J].Power System Technology,2017,41(5):1419-1427(in Chinese).
[9]Catalao J P S,Mariano S J P S,Mendes V M F,et al.Unit commitment in a competitive and emission constrained environment[J].IEEE Latin America Transactions,2009,7(5):560-568.
[10]王民量,张伯明.考虑多种约束条件的机组组合新算法[J].电力系统自动化,2000,24(12):29-35.Wang Minliang,Zhang Boming.A new algorithm of unit combination considering multiple constraints[J].Automation of Electric Power Systems,2000,24(12):29-35(in Chinese).
[11]Mei S,Zhang D,Wang Y,et al.Robust optimization of static reserve planning with large-scale integration of wind power:a game theoretic approach[J].IEEE Transactions on Sustainable Energy,2014,5(2):535-545.
[12]苏鹏,刘天琪,李兴源.含风电的系统最优旋转备用的确定[J].电网技术,2010,34(12):158-162.Su Peng,Liu Tianqi,Li Xingyuan.Determination of optimal rotating standby system with wind power system[J].Power System Technology,2010,34(12):158-162(in Chinese).
[13]夏澍,顾劲岳,葛晓琳,等.风光联合优化配置的多目标机会约束规划方法[J].电力系统保护与控制,2016,44(6):35-40.Xia Shu,Gu Jinyue,Ge Xiaolin,et al.A multi-objective chance constrained programming of optimal allocation of scenery method[J].Power System Protection and Controll,2016,44(6):35-40(in Chinese).
[14]孙欣,方陈,沈风,等.考虑风电出力不确定性的发用电机组组合方法[J].电工技术学报,2017,32(4):204-211.Sun Xin,Fang Chen,Shen Wind,et al.Considering wind power uncertainty in turbine combination method[J].Transactions of China Electrotechnical Society,2017,32(4):204-211(in Chinese).
[15]黎静华,文劲宇,潘毅,等.面向新能源并网的电力系统鲁棒调度模式[J].电力系统保护与控制,2015,43(22):47-54Li Jinghua,Wen Jinyu,Pan Yi,et al.Facing the new energy grid power system robust scheduling model[J].Power System Protection and Control,2015,43(22):47-54(in Chinese).
[16]陈建华,吴文传,张伯明,等.安全性与经济性协调的鲁棒区间风电调度方法[J].中国电机工程学报,2014,34(7):1033-1040.Chen Jianhua,Wu Wenchuan,Zhang Boming,et al.A robust interval wind power dispatch method in coordination of safety and economy[J].Proceedings of the CSEE,2014,34(7):1033-1040(in Chinese).
[17]王鲁浩,李歧强,丁然,等.可再生能源微网鲁棒多目标优化调度[J].电工技术学报,2017,32(5):184-192.Wang Luhao,Li Qiqiang,Ding Ran,et al.Robust multi-objective optimal scheduling of renewable energy micronetworks[J].Transactions of China Electrotechnical Society,2017,32(5):184-192(in Chinese).
[18]álvaro Lorca,Sun X A,Litvinov E,et al.Multistage adaptive robust optimization for the unit commitment problem[J].Operations Research,2014(64):32-51.
[19]艾小猛,韩杏宁,文劲宇,等.考虑风电爬坡事件的鲁棒机组组合[J].电工技术学报,2015,30(24):188-195.Ai Xiaomeng,Han Xingning,Wen Jinyu,et al.Considering wind power ramp events robust unit[J].Transactions of China Electrotechnical Society,2015,30(24):188-195(in Chinese).
[20]高红均,刘俊勇,刘继春,等.基于坏场景集的含风电机组组合模型[J].电力系统保护与控制,2013,41(10):27-32.High Hongjun,Liu Junyong,Liu Jichun,et al.With wind turbine combined model[J].Power System Protection and Control,2013,41(10):27-32(in Chinese).
[21]Xiong P,Jirutitijaroen P,Singh C.A Distributionally robust optimization model for unit commitment considering uncertain wind power generation[J].IEEE Transactions on Power Systems,2017,PP(99):1-11
[22]Guan Y,Wang J.Uncertainty sets for robust unit commitment[J].IEEE Transactions on Power Systems,2014,29(3):1439-1440.
[23]范刘洋,汪可友,吴巍,等.多时间尺度的电力系统鲁棒调度研究[J].电网技术,2017,41(5):1576-1582.Fan Liuyang,Wang Keyou,Wu Wei,et al.Study on power system robust scheduling multi time scale[J].Power System Technology,2017,41(5):1576-1582(in Chinese).
[24]Bertsimas D,Litvinov E,Sun X A,et al.Adaptive robust optimization for the security constrained unit commitment problem[J].IEEETransactions on Power Systems,2013,28(1):52-63.
[25]孙东磊,韩学山,杨金洪.计及电压调节效应的电力系统机组组合[J].电工技术学报,2016,31(5):107-117.Sun Donglei,Han Xueshan,Yang Jinhong.Considering voltage regulation effect of unit commitment in power systems[J].Transactions of China Electrotechnical Society,2016,31(5):107-117(in Chinese).
[26]Zhao L,Zeng B.Robust unit commitment problem with demand response and wind energy[C]//Power and Energy Society General Meeting.San Diego,CA,USA,2010:1-8.
[27]An Y,Zeng B.Exploring the modeling capacity of two-stage robust optimization:variants of robust unit commitment model[J].IEEETransactions on Power Systems,2014,30(1):109-122.
[28]Ongsakul W,Petcharaks N.Unit commitment by enhanced adaptive Lagrangian relaxation[J].IEEE Transactions on Power Systems,2004,19(1):620-628.
[29]谢毓广,江晓东.储能系统对含风电的机组组合问题影响分析[J].电力系统自动化,2011,35(5):19-24.Xie Yuguang,Jiang Xiaodong.Analysis of the influence of energy storage system on the problem of unit combination with wind power[J].Automation of Electric Power Systems,2011,35(5):19-24(in Chinese).
[30]Doquet M.Use of a stochastic process to sample wind power curves in planning studies[C]//Power Tech,2007 IEEE Lausanne.Lausanne,Switzerland,2008:663-670.
[2]国家发展改革委.能源生产和消费革命战略[EB/OL].[2016-12-29].http://www.ndrc.gov.cn/zcfb/zcfbtz/201704/W020170425509386101355.pdf.
[3]Constantinescu E M,Zavala V M,Rocklin M,et al.A computational framework for uncertainty quantification and stochastic optimization in unit commitment with wind power generation[J].IEEETransactions on Power Systems,2011,26(1):431-441.
[4]陈皓勇,王锡凡.机组组合问题的优化方法综述[J].电力系统自动化,1999(4):51-56.Chen Haoyong,Wang Xifan.Review on optimization methods for unit commitment[J].Automation of Electric Power Systems,1999(4):51-56(in Chinese).
[5]王颖,周刚,韩红卫,等.计及风电最优置信度的机组组合优化方法[J].电网技术,2017,41(3):808-815.Wang Ying,Zhou Gang,Han Hongwei,et al.Unit commitment considering optimal confidence of wind power uncertainty[J].Power System Technology,2017,41(3):808-815(in Chinese).
[6]李本新,韩学山,蒋哲,等.应对风电间歇性的火电机组组合模型与分析[J].电网技术,2017,41(5):1569-1575.Li Benxin,Han Xueshan,Jiang Zhe,et al.Modeling and analysis of unit commitment to accommodate intermittent uncertainty[J].Power System Technology,2017,41(5):1569-1575(in Chinese).
[7]向红吉,戴朝华,明杰,等.考虑低谷时刻负调峰能力及风电预测区间的多目标机组组合优化研究[J].电网技术,2017,41(6):1912-1918.Xiang Hongji,Dai Chaohua,Ming Jie,et al.Research on multi-objective optimization of unit commitment considering negative peak load regulation ability in valley load period and wind power prediction interval[J].Power System Technology,2017,41(6):1912-1918(in Chinese).
[8]汪超群,韦化,吴思缘.计及风电不确定性的随机安全约束机组组合[J].电网技术,2017,41(5):1419-1427.Wang Chaoqun,Wei Hua,Wu Siyuan.Stochastic-security-constrained unit commitment considering uncertainty of wind power[J].Power System Technology,2017,41(5):1419-1427(in Chinese).
[9]Catalao J P S,Mariano S J P S,Mendes V M F,et al.Unit commitment in a competitive and emission constrained environment[J].IEEE Latin America Transactions,2009,7(5):560-568.
[10]王民量,张伯明.考虑多种约束条件的机组组合新算法[J].电力系统自动化,2000,24(12):29-35.Wang Minliang,Zhang Boming.A new algorithm of unit combination considering multiple constraints[J].Automation of Electric Power Systems,2000,24(12):29-35(in Chinese).
[11]Mei S,Zhang D,Wang Y,et al.Robust optimization of static reserve planning with large-scale integration of wind power:a game theoretic approach[J].IEEE Transactions on Sustainable Energy,2014,5(2):535-545.
[12]苏鹏,刘天琪,李兴源.含风电的系统最优旋转备用的确定[J].电网技术,2010,34(12):158-162.Su Peng,Liu Tianqi,Li Xingyuan.Determination of optimal rotating standby system with wind power system[J].Power System Technology,2010,34(12):158-162(in Chinese).
[13]夏澍,顾劲岳,葛晓琳,等.风光联合优化配置的多目标机会约束规划方法[J].电力系统保护与控制,2016,44(6):35-40.Xia Shu,Gu Jinyue,Ge Xiaolin,et al.A multi-objective chance constrained programming of optimal allocation of scenery method[J].Power System Protection and Controll,2016,44(6):35-40(in Chinese).
[14]孙欣,方陈,沈风,等.考虑风电出力不确定性的发用电机组组合方法[J].电工技术学报,2017,32(4):204-211.Sun Xin,Fang Chen,Shen Wind,et al.Considering wind power uncertainty in turbine combination method[J].Transactions of China Electrotechnical Society,2017,32(4):204-211(in Chinese).
[15]黎静华,文劲宇,潘毅,等.面向新能源并网的电力系统鲁棒调度模式[J].电力系统保护与控制,2015,43(22):47-54Li Jinghua,Wen Jinyu,Pan Yi,et al.Facing the new energy grid power system robust scheduling model[J].Power System Protection and Control,2015,43(22):47-54(in Chinese).
[16]陈建华,吴文传,张伯明,等.安全性与经济性协调的鲁棒区间风电调度方法[J].中国电机工程学报,2014,34(7):1033-1040.Chen Jianhua,Wu Wenchuan,Zhang Boming,et al.A robust interval wind power dispatch method in coordination of safety and economy[J].Proceedings of the CSEE,2014,34(7):1033-1040(in Chinese).
[17]王鲁浩,李歧强,丁然,等.可再生能源微网鲁棒多目标优化调度[J].电工技术学报,2017,32(5):184-192.Wang Luhao,Li Qiqiang,Ding Ran,et al.Robust multi-objective optimal scheduling of renewable energy micronetworks[J].Transactions of China Electrotechnical Society,2017,32(5):184-192(in Chinese).
[18]álvaro Lorca,Sun X A,Litvinov E,et al.Multistage adaptive robust optimization for the unit commitment problem[J].Operations Research,2014(64):32-51.
[19]艾小猛,韩杏宁,文劲宇,等.考虑风电爬坡事件的鲁棒机组组合[J].电工技术学报,2015,30(24):188-195.Ai Xiaomeng,Han Xingning,Wen Jinyu,et al.Considering wind power ramp events robust unit[J].Transactions of China Electrotechnical Society,2015,30(24):188-195(in Chinese).
[20]高红均,刘俊勇,刘继春,等.基于坏场景集的含风电机组组合模型[J].电力系统保护与控制,2013,41(10):27-32.High Hongjun,Liu Junyong,Liu Jichun,et al.With wind turbine combined model[J].Power System Protection and Control,2013,41(10):27-32(in Chinese).
[21]Xiong P,Jirutitijaroen P,Singh C.A Distributionally robust optimization model for unit commitment considering uncertain wind power generation[J].IEEE Transactions on Power Systems,2017,PP(99):1-11
[22]Guan Y,Wang J.Uncertainty sets for robust unit commitment[J].IEEE Transactions on Power Systems,2014,29(3):1439-1440.
[23]范刘洋,汪可友,吴巍,等.多时间尺度的电力系统鲁棒调度研究[J].电网技术,2017,41(5):1576-1582.Fan Liuyang,Wang Keyou,Wu Wei,et al.Study on power system robust scheduling multi time scale[J].Power System Technology,2017,41(5):1576-1582(in Chinese).
[24]Bertsimas D,Litvinov E,Sun X A,et al.Adaptive robust optimization for the security constrained unit commitment problem[J].IEEETransactions on Power Systems,2013,28(1):52-63.
[25]孙东磊,韩学山,杨金洪.计及电压调节效应的电力系统机组组合[J].电工技术学报,2016,31(5):107-117.Sun Donglei,Han Xueshan,Yang Jinhong.Considering voltage regulation effect of unit commitment in power systems[J].Transactions of China Electrotechnical Society,2016,31(5):107-117(in Chinese).
[26]Zhao L,Zeng B.Robust unit commitment problem with demand response and wind energy[C]//Power and Energy Society General Meeting.San Diego,CA,USA,2010:1-8.
[27]An Y,Zeng B.Exploring the modeling capacity of two-stage robust optimization:variants of robust unit commitment model[J].IEEETransactions on Power Systems,2014,30(1):109-122.
[28]Ongsakul W,Petcharaks N.Unit commitment by enhanced adaptive Lagrangian relaxation[J].IEEE Transactions on Power Systems,2004,19(1):620-628.
[29]谢毓广,江晓东.储能系统对含风电的机组组合问题影响分析[J].电力系统自动化,2011,35(5):19-24.Xie Yuguang,Jiang Xiaodong.Analysis of the influence of energy storage system on the problem of unit combination with wind power[J].Automation of Electric Power Systems,2011,35(5):19-24(in Chinese).
[30]Doquet M.Use of a stochastic process to sample wind power curves in planning studies[C]//Power Tech,2007 IEEE Lausanne.Lausanne,Switzerland,2008:663-670.
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