基于风电消纳能力态势划分的源荷储系统分阶段优化策略
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摘要
仿照电力系统在不同运行条件下有着不同的运行状态,提出解决风电消纳的三态划分法。根据弃风量的多少及其变化趋势,将包含储热、电储能和柔性负荷的热电联产系统划分为正常状态、警戒状态和紧急状态。已知系统运行状态,建立不同状态下的源荷储分阶段优化调度模型,并采用粒子群优化算法对模型进行求解。算例分析表明,正常状态下由于柔性负荷和储热装置的参与,减小了系统的调峰压力,降低了运行成本;警戒状态下电储能设备与风电场建立了一种能量互补关系,实现了平抑风电功率波动的目标,有利于系统的安全稳定运行;紧急状态下储热系统将弃风电能转化为热能,在满足用户热需求的同时,将多余热量储存起来,实现能量的高效利用。
A partition method of three-state for wind power accommodation is proposed,which is modeled based on the operation states of power system under different operation conditions.The combined heat and power system with thermal energy storage,electric energy storage and flexible load are divided into three states that include normal state,alert state and emergency state according to wind power curtailment and its variation trend.A phased optimal scheduling model in different states is established and solved by particle swarm optimization algorithm.In normal state,the participation of flexible load and thermal energy storage is able to reduce the pressure of peak shaving and operation costs of system.In alert state,the energy complementary relationship between electric energy and wind power can be found to achieve the target of alleviating wind power fluctuation,which is helpful for safety and stable operation of the system.In emergency state,the system of thermal energy storage transforms abandoned wind power into heat energy to meet the demand for heat supply of users,stores the excess energy and enhances energy use efficiently.
A partition method of three-state for wind power accommodation is proposed,which is modeled based on the operation states of power system under different operation conditions.The combined heat and power system with thermal energy storage,electric energy storage and flexible load are divided into three states that include normal state,alert state and emergency state according to wind power curtailment and its variation trend.A phased optimal scheduling model in different states is established and solved by particle swarm optimization algorithm.In normal state,the participation of flexible load and thermal energy storage is able to reduce the pressure of peak shaving and operation costs of system.In alert state,the energy complementary relationship between electric energy and wind power can be found to achieve the target of alleviating wind power fluctuation,which is helpful for safety and stable operation of the system.In emergency state,the system of thermal energy storage transforms abandoned wind power into heat energy to meet the demand for heat supply of users,stores the excess energy and enhances energy use efficiently.
引文
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[8]邓佳乐,胡林献,李佳佳.采用二级热网电锅炉调峰的消纳弃风机理及经济性分析[J].电力系统自动化,2016,40(18):41-47.DENG Jiale,HU Linxian,LI Jiajia.Analysis on mechanism of curtailed wind power accommodation and its economic operation based on electric boiler for peak-load regulation at secondary heat supply network[J].Automation of Electric Power Systems,2016,40(18):41-47.
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[12]宋艺航,谭忠富,李欢欢,等.促进风电消纳的发电侧、储能及需求侧联合优化模型[J].电网技术,2014,38(3):610-615.SONG Yihang,TAN Zhongfu,LI Huanhuan,et al.An optimization model combining generation side and energy storage system demand side to promote accommodation of wind power[J].Power System Technology,2014,38(3):610-615.
[13]姚建国,杨胜春,王珂,等.智能电网“源-网-荷”互动运行控制概念及研究框架[J].电力系统自动化,2012,36(21):1-6.YAO Jianguo,YANG Shengchun,WANG Ke,et al.Concept and research framework of smart grid“source-grid-load”interactive operation and control[J].Automation of Electric System,2012,36(21):1-6.
[14]CALLAWAY D S,HISKENS I A.Achieving controllability of electric loads[J].Proceedings of the IEEE,2011,99(1):184-199.
[15]杨经纬,张宁,王毅,等.面向可再生能源消纳的多能源系统:述评与展望[J].电力系统自动化,2018,42(4):11-24.DOI:10.7500/AEPS20171002004.YANG Jingwei,ZHANG Ning,WANG Yi,et al.Multienergy system towards renewable energy accommodation:review and prospect[J].Automation of Electric Power Systems,2018,42(4):11-24.DOI:10.7500/AEPS20171002004.
[16]彭飞翔,李晓晶,孙辉,等.考虑发电集团利益主体协调的风电消纳调度策略[J].电力系统自动化,2018,42(18):98-108.DOI:10.7500/AEPS20170910011.PENG Feixiang,LI Xiaojing,SUN Hui,et al.Dispatch strategy for wind power accommodation considering coordination of power generation group stakeholders[J].Automation of Electric Power Systems,2018,42(18):98-108.DOI:10.7500/AEPS20170910011.
[17]吴迪,程海花,赵晋泉,等.基于平衡成本的风电分段及火电调峰补偿方法[J].电力系统自动化,2019,43(3):116-123.DOI:10.7500/AEPS20180213010.WU Di,CHENG Haihua,ZHAO Jinquan,et al.Balancing cost based wind power segmentation and compensation method of peak regulation for thermal power[J].Automation of Electric Power Systems,2019,43(3):116-123.DOI:10.7500/AEPS20180213010.
[18]严干贵,冯晓东,李军徽,等.用于松弛调峰瓶颈的储能系统容量配置方法[J].中国电机工程学报,2012,32(28):27-35.YAN Gangui,FENG Xiaodong,LI Junhui,et al.Optimization of energy storage system capacity for relaxing peak load regulation bottlenecks[J].Proceedings of the CSEE,2012,32(28):27-35.
[19]洪海生,江全元,严玉婷.实时平抑风电场功率波动的电池储能系统优化控制方法[J].电力系统自动化,2013,37(1):103-109.HONG Haisheng,JIANG Quanyuan,YAN Yuting.An optimization control method of battery energy storage system with wind power fluctuations smoothed in real time[J].Automation of Electric Power Systems,2013,37(1):103-109.
[20]贺益君,陈德钊.适于混合整数非线性规划的混合粒子群优化算法[J].浙江大学学报(工学版),2008,42(5):747-751.HE Yijun,CHEN Dezhao.Hybrid particle swarm optimization algorithm for mixed-integer nonlinear programming[J].Journal of Zhejiang University(Engineering Science),2008,42(5):747-751.
[21]刘钊,康立山,蒋良孝.用粒子群优化改进算法求解混合整数非线性规划问题[J].小型微型计算机系统,2005,26(6):991-994.LIU Zhao,KANG Lishan,JIANG Liangxiao.New PSOalgorithm for MINLP problems[J].Mini-Micro Systems,2005,26(6):991-994.
[22]周玮,彭昱,孙辉,等.含风电场的电力系统动态经济调度[J].中国电机工程学报,2009,29(25):13-18.ZHOU Wei,PENG Yu,SUN Hui,et al.Dynamic economic dispatch in wind power integrated system[J].Proceedings of the CSEE,2009,29(25):13-18.
[2]郭丰慧,胡林献,周升彧.基于二级热网储热式电锅炉调峰的弃风消纳调度模型[J].电力系统自动化,2018,42(19):50-56.DOI:10.7500/AEPS20180130009.GUO Fenghui,HU Linxian,ZHOU Shengyu.Dispatching model of wind power accommodation based on heat storage electric boiler for peak-load regulation in secondary heat supply network[J].Automation of Electric Power Systems,2018,42(19):50-56.DOI:10.7500/AEPS20180130009.
[3]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):3796-3802.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):3796-3802.
[4]王振浩,杨璐,田春光,等.考虑风电消纳的风电-电储能-蓄热式电锅炉联合系统能量优化[J].中国电机工程学报,2017,37(增刊1):137-143.WANG Zhenhao,YANG Lu,TIAN Chunguang,et al.Energy optimization for combined system of wind-electric energy storage-regenerative energy optimization for combined system of wind-electric energy storage-regenerative[J].Proceedings of the CSEE,2017,37(Supplement 1):137-143.
[5]CHEN X,KANG C,O’MALLEY M,et al.Increasing the flexibility of combined heat and power for wind power integration in China:modeling and implications[J].IEEETransactions on Power Systems,2015,30(4):1848-1857.
[6]葛维春.大规模弃风储热供暖协调计算方法[J].发电技术,2018,39(4):291-295.GE Weichun.A coordinated calculation method of abandoned large-scale wind heat storage for heating[J].Power Generation Technology,2018,39(4):291-295.
[7]吕泉,刘永成,刘乐,等.考虑弃风特性的风电供热项目节煤效果与最佳配置方案研究[J].中国电机工程学报,2017,37(16):4699-4711.LQuan,LIU Yongcheng,LIU Le,et al.Research on coalsaving performance and optimal configuration of wind power heating project considering wind power curtailment characteristics[J].Proceedings of the CSEE,2017,37(16):4699-4711.
[8]邓佳乐,胡林献,李佳佳.采用二级热网电锅炉调峰的消纳弃风机理及经济性分析[J].电力系统自动化,2016,40(18):41-47.DENG Jiale,HU Linxian,LI Jiajia.Analysis on mechanism of curtailed wind power accommodation and its economic operation based on electric boiler for peak-load regulation at secondary heat supply network[J].Automation of Electric Power Systems,2016,40(18):41-47.
[9]赵书强,刘大正,谢宇琪,等.基于相关机会目标规划的风光储联合发电系统储能调度策略[J].电力系统自动化,2015,39(14):30-36.ZHAO Shuqiang,LIU Dazheng,XIE Yuqi,et al.Scheduling strategy of energy storage in wind-solar-battery hybrid power system based on dependent-chance goal programming[J].Automation of Electric Power Systems,2015,39(14):30-36.
[10]YUAN Y,LI Q,WANG W.Optimal operation strategy of energy storage unit in wind power integration based on stochastic programming[J].IET Renewable Power Generation,2011,5(2):194-201.
[11]孙建军,张世泽,曾梦迪,等.考虑分时电价的主动配电网柔性负荷多目标优化控制[J].电工技术学报,2018,33(2):401-412.SUN Jianjun,ZHANG Shize,ZENG Mengdi,et al.Multiobjective optimal control for flexible load in active distribution network considering time-of-use tariff[J].Transactions of China Electrotechnical Society,2018,33(2):401-412.
[12]宋艺航,谭忠富,李欢欢,等.促进风电消纳的发电侧、储能及需求侧联合优化模型[J].电网技术,2014,38(3):610-615.SONG Yihang,TAN Zhongfu,LI Huanhuan,et al.An optimization model combining generation side and energy storage system demand side to promote accommodation of wind power[J].Power System Technology,2014,38(3):610-615.
[13]姚建国,杨胜春,王珂,等.智能电网“源-网-荷”互动运行控制概念及研究框架[J].电力系统自动化,2012,36(21):1-6.YAO Jianguo,YANG Shengchun,WANG Ke,et al.Concept and research framework of smart grid“source-grid-load”interactive operation and control[J].Automation of Electric System,2012,36(21):1-6.
[14]CALLAWAY D S,HISKENS I A.Achieving controllability of electric loads[J].Proceedings of the IEEE,2011,99(1):184-199.
[15]杨经纬,张宁,王毅,等.面向可再生能源消纳的多能源系统:述评与展望[J].电力系统自动化,2018,42(4):11-24.DOI:10.7500/AEPS20171002004.YANG Jingwei,ZHANG Ning,WANG Yi,et al.Multienergy system towards renewable energy accommodation:review and prospect[J].Automation of Electric Power Systems,2018,42(4):11-24.DOI:10.7500/AEPS20171002004.
[16]彭飞翔,李晓晶,孙辉,等.考虑发电集团利益主体协调的风电消纳调度策略[J].电力系统自动化,2018,42(18):98-108.DOI:10.7500/AEPS20170910011.PENG Feixiang,LI Xiaojing,SUN Hui,et al.Dispatch strategy for wind power accommodation considering coordination of power generation group stakeholders[J].Automation of Electric Power Systems,2018,42(18):98-108.DOI:10.7500/AEPS20170910011.
[17]吴迪,程海花,赵晋泉,等.基于平衡成本的风电分段及火电调峰补偿方法[J].电力系统自动化,2019,43(3):116-123.DOI:10.7500/AEPS20180213010.WU Di,CHENG Haihua,ZHAO Jinquan,et al.Balancing cost based wind power segmentation and compensation method of peak regulation for thermal power[J].Automation of Electric Power Systems,2019,43(3):116-123.DOI:10.7500/AEPS20180213010.
[18]严干贵,冯晓东,李军徽,等.用于松弛调峰瓶颈的储能系统容量配置方法[J].中国电机工程学报,2012,32(28):27-35.YAN Gangui,FENG Xiaodong,LI Junhui,et al.Optimization of energy storage system capacity for relaxing peak load regulation bottlenecks[J].Proceedings of the CSEE,2012,32(28):27-35.
[19]洪海生,江全元,严玉婷.实时平抑风电场功率波动的电池储能系统优化控制方法[J].电力系统自动化,2013,37(1):103-109.HONG Haisheng,JIANG Quanyuan,YAN Yuting.An optimization control method of battery energy storage system with wind power fluctuations smoothed in real time[J].Automation of Electric Power Systems,2013,37(1):103-109.
[20]贺益君,陈德钊.适于混合整数非线性规划的混合粒子群优化算法[J].浙江大学学报(工学版),2008,42(5):747-751.HE Yijun,CHEN Dezhao.Hybrid particle swarm optimization algorithm for mixed-integer nonlinear programming[J].Journal of Zhejiang University(Engineering Science),2008,42(5):747-751.
[21]刘钊,康立山,蒋良孝.用粒子群优化改进算法求解混合整数非线性规划问题[J].小型微型计算机系统,2005,26(6):991-994.LIU Zhao,KANG Lishan,JIANG Liangxiao.New PSOalgorithm for MINLP problems[J].Mini-Micro Systems,2005,26(6):991-994.
[22]周玮,彭昱,孙辉,等.含风电场的电力系统动态经济调度[J].中国电机工程学报,2009,29(25):13-18.ZHOU Wei,PENG Yu,SUN Hui,et al.Dynamic economic dispatch in wind power integrated system[J].Proceedings of the CSEE,2009,29(25):13-18.