面向“互联网+”的风火发电权交易促进风电接纳研究
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摘要
针对目前中国严峻的弃风形势,结合"互联网+"在电力行业不断融合的新趋势,提出面向"互联网+"的分散式超短期风火发电权交易模式。当风电场出力大于电网对它的消纳能力时,为了减少弃风,风电场通过"互联网+"交易平台及时发布交易信息,邀请有能力的火电机组参与发电权交易,利用"互联网+"平台的分散决策系统和云计算技术,快速提供优化决策。由于风电场出力的随机性,风电场实发电量与火电机组签订的交易电量会存在一定偏差,使得风电场无法准确履行交易计划。为此,在风火发电权交易模型中引入风电不平衡费用,量化分析风电场出力偏差引起的不平衡成本。最后,通过算例仿真,验证交易模式的合理性,为解决风电消纳难题提供参考。
Nowadays the wind curtailment situation is increasingly severe in China,and‘Internet +'is integrated into electric power industry step by step. This paper proposes a super short-time decentralized power generation right trading between wind farms and thermal units(PGRTBWT). When power output is more than the power of being absorbed into grid,wind farms will release information to invite thermal units which may participate in power generation right trading in order to reduce wind curtailment by‘Internet +'trading platform. The optimal decisions can be rapidly obtained by ‘Internet +'distributed decision support system and cloud computing. Because of the randomness of wind power,the deviation always exists between real energy and the trading energy,which makes it unable for wind farms to perform the trading plan accurately. Therefore,this paper introduces the wind power unbalanced cost to analyze and calculate deviation cost. Finally,a case simulation shows the trading model is rational. This paper provides a reference for the accommodating of wind power.Internet+accommodation of wind powerdecentralized tradingsuper shorttimepower generation right
Nowadays the wind curtailment situation is increasingly severe in China,and‘Internet +'is integrated into electric power industry step by step. This paper proposes a super short-time decentralized power generation right trading between wind farms and thermal units(PGRTBWT). When power output is more than the power of being absorbed into grid,wind farms will release information to invite thermal units which may participate in power generation right trading in order to reduce wind curtailment by‘Internet +'trading platform. The optimal decisions can be rapidly obtained by ‘Internet +'distributed decision support system and cloud computing. Because of the randomness of wind power,the deviation always exists between real energy and the trading energy,which makes it unable for wind farms to perform the trading plan accurately. Therefore,this paper introduces the wind power unbalanced cost to analyze and calculate deviation cost. Finally,a case simulation shows the trading model is rational. This paper provides a reference for the accommodating of wind power.Internet+accommodation of wind powerdecentralized tradingsuper shorttimepower generation right
引文
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[14]田建芳,毛亚珊,翟桥柱,等.基于风电消纳能力评估的安全约束经济调度方法[J].电网技术,2015,39(9):2398—2403.[14] Tian Jianfang, Mao Yashan, Qu Qiaozhu, et al.Security constrained unit commitment with wind powerbased on evaluation of wind power penetration capacity[J]. Power System Technology,2015,39(9):2398—2403.
[15]李志刚,吴文传,张伯明.消纳大规模风电的鲁棒区间经济调度(一)调度模式与数学模型[J].电力系统自动化,2014,38(20):33—39.[15] Li Zhigang,Wu Wenchuan,Zhang Boming. A robustinterval economic dispatch method accommodating large-scale wind power generation part one dispatch schemeand mathematical model[J]. Automation of ElectricPower Systems,2014,38(20):33—39.
[16]刘文颖,文晶,谢昶,等.考虑风电消纳的电力系统源荷协调多目标优化方法[J].中国电机工程学报,2015,35(5):1079—1088.[16] Liu Wenying,Wen Jing,Xie Chang,et al. Multi-objective optimal method considering wind poweraccommodation based on source-load coordination[J].Proceedings of the CSEE,2015,35(5):1079—1088.
[17]刘德伟,黄越辉,王伟胜,等.考虑调峰和电网输送约束的省级系统风电消纳能力分析[J].电力系统自动化,2011,35(22):77—81.[17] Liu Dewei,Huang Yuefei,Wang Weisheng,et al.Analysis on provincial system available capability ofaccommodating wind power considering peak loaddispatch and transmission constraints[J]. Automation ofElectric Power Systems,2011,35(22):77—81.
[18]王秀丽,李骏,黄镔,等.促进风电消纳的区省两级电力系统调度模型[J].电网技术,2015,39(7):1833—1838.[18] Wang Xiuli,Li Jun,Huang Bin,et al. A two-stageoptimal dispatching model for provincial and regionalpower grids connected with wind farms to promoteaccommodation of wind power[J]. Power SystemTechnology,2015,39(7):1833—1838.
[19]陈颖,周海,王文鹏,等.风电场输出功率超短期预测结果分析与改进[J].电力系统自动化,2011,35(15):30—33.[19] Chen Yi, Zhou Hai, Wang Wenpeng, et al.Improvement of ultra-short-term forecast for wind power[J]. Automation of Electric Power Systems,2011,35(15):30—33.
[20]江岳文,温步瀛.结合风电功率超短期预测值偏差的实时市场调度[J].电力自动化设备,2015,35(3):12—17.[20] Jiang Yuewen,Wen Buying. Real-time market dispatchbased on ultra-short-term forecast error of wind power[J]. ElectricPowerAutomationEquipment,2015,35(3):12—17.
[21]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6):13—18.[21] Li Chanbin, Kang Chongqin, Xia Qing, et al.Generation rights trade and its mechanism[J].Automation of Electric Power Systems,2003,27(6):13—18.
[22]尚金成.基于节能减排的发电权交易理论及应用(一)发电权交易理论[J].电力系统自动化,2009,33(12):46—52.[22] Shang Jincheng. Generation right exchange theory andits applications based on energy-saving and emission-reducing(1)Generation right exchange theory[J].Automation of Electric Power Systems,2009,33(12):46—52.
[23]尚金成,何洋.基于节能减排的发电权交易理论及应用(二)发电权交易分析及应用[J].电力系统自动化,2009,33(13):37—42.[23] Shang Jincheng,He Yang. Generation right exchangetheory and its applications based on energy-saving andemission-reducing(2)Generation right exchangeanalysis and applications[J]. Automation of ElectricPower Systems,2009,33(13):37—42.
[24]周玮,孙辉,顾宏,等.计及风险备用约束的含风电场电力系统动态经济调度[J].中国电机工程学报,2012,32(1):47—55.[24] Zhou Wei, Sun Hui, Gu Hong, et al. Dynamiceconomic dispatch of wind integrated power systemsbased on risk reserve constraints[J]. Proceedings of theCSEE,2012,32(1):47—55.
[25]孙元章,吴俊,李国杰,等.基于风速预测和随机规划的含风电场电力系统动态经济调度[J].中国电机工程学报,2009,29(4):41—47.[25] Sun Yuanzhang,Wu Jun,Li Guojie,et al. Dynamiceconomic dispatch considering wind speed forecastingand stochastic programming[J]. Proceedings of theCSEE,2009,29(4):41—47.
[26]姜建国,田旻,王向前,等.采用扰动加速因子的自适应粒子群优化算法[J].西安电子科技大学学报:自然科学版,2012,39(4):74—80.[26] Jiang Jianguo, Tian Min, Wang Xiangqian, et al.Adaptive particle swarm optimization via disturbingacceleration coefficients[J]. Journal of XidianUniversity:Natural Science,2012,39(4):74—80.
[2]王雁凌,邱小燕,许传龙.以节能降耗为目标的发电权交易阻塞管理模型[J].电网技术,2012,36(6):272—276.[2] Wang Yanling,Qiu Xiaoyan,Xu Chuanlong. Congestionmanagement of generation rights trade based on energyconservation[J]. Power System Technology, 2012,36(6):272—276.
[3]朱怡. 2015年我国驱动全球风电新增达6301万千瓦[EB/OL]. http://www. cpnn. com. cn/zdyw/201602/t20160222_870714. html, 2016-02-22.
[4]张世帅,张学松,王文,等.发电权交易下的节能减排指标设计及应用分析[J].电网技术,2010,34(11):156—161.[4] Zhang Shishuai,Zhang Xuesong,Wang Wen,et al.Design and application analysis of two indices of energy-saving and emission-reducing based on generation righttrading[J]. Power System Technology,2010,34(11):156—161.
[5]迟远英,王彦亮,牛东晓,等.碳排放交易下的发电权置换优化模型[J].电网技术,2010,(6):78—81.[5] Chi Yuanying,Wang Yanliang,Liu Dongxiao,et al. Anoptimization model of generation right exchanging undercarbon emission trading[J]. Power System Technology,2010,(6):78—81.
[6]傅鸿浩,蔡国田,赵黛青.计及环境成本的跨省输电发电权交易及敏感性分析[J].电力自动化设备,2014,34(9):101—105.[6] Fu Honghao,Cai Guotian,Zhao Daiqing. Generationright trade of trans-province power transmissionconsidering environmental cost and sensitivity analysis[J]. ElectricPowerAutomationEquipment,2014,34(9):101—105.
[7]李丰,张粒子.大规模风电跨省消纳与交易机制的研究[J].电力自动化设备,2013,33(8):119—124.[7] Li Feng,Zhang Lizi. Accommodation and transactionmechanism of trans provincial large-scale wind power[J]. Electric Power Automation Equipment,2013,33(8):119—124.
[8]吴杨,刘俊勇,高红均,等.基于风险决策的风火发电权交易研究[J].电网技术,2016,40(3):1—7.[8] Wu Yang,Liu Junyong,Gao Hongjun,et al. Study ontransaction risk decision based on wind power[J]. PowerSystem Technology,2016,40(3):1—7.
[9]杜壮.国家发改委正在牵头制定“互联网+”行动计划——让真正创新的企业能获利[J].中国战略新兴产业,2015,(9):37—39.[9] Du Zhuang. State development and reform commission isleading making ‘Internet+’ action plan—Let realinnovation of enterprise make profit[J]. China StrategicEmerging Industry,2015,(9):37—39.
[10]白杨,谢乐,夏清,等.中国推进售电侧市场化的制度设计与建议[J].电力系统自动化,2015,(14):1—7.[10] Bai Yang,Xie Le,Xia Qing,et al. Institutional designof Chinese retail electricity market reform and relatedsuggestions[J]. Automation of Electric Power Systems,2015,39(14):1—7.
[11]陈启鑫,刘敦楠,林今,等.能源互联网的商业模式与市场机制(一)[J].电网技术,2015,39(11):3050—3056.[11] Chen Qixin,Liu Dunnan,Lin Jin,et al. Businessmodels and market mechanisms of energy internet(1)[J]. Power System Technology,2015,39(11):3050—3056.
[12]刘敦楠,曾明,黄仁乐,等.能源互联网的商业模式与市场机制(二)[J].电网技术,2015,39(11):3057—3063.[12] Liu Dunnan,Zeng Ming,Huang Renle,et al. Businessmodels and market mechanisms of energy internet(2)[J]. Power System Technology,2015,39(11):3057—3063.
[13]袁铁江,彭超锋,梅生伟,等.基于提高消纳能力的风电平衡区域电网划分方法[J].电网技术,2015,39(8):2129—2134.[13] Yuan Tiejiang,Peng Chaofeng,Mei Shengwei,et al. Apartitioning method to enhance accommodationcapability of power network with balanced region of windpower[J]. Power System Technology,2015,39(8):2129—2134.
[14]田建芳,毛亚珊,翟桥柱,等.基于风电消纳能力评估的安全约束经济调度方法[J].电网技术,2015,39(9):2398—2403.[14] Tian Jianfang, Mao Yashan, Qu Qiaozhu, et al.Security constrained unit commitment with wind powerbased on evaluation of wind power penetration capacity[J]. Power System Technology,2015,39(9):2398—2403.
[15]李志刚,吴文传,张伯明.消纳大规模风电的鲁棒区间经济调度(一)调度模式与数学模型[J].电力系统自动化,2014,38(20):33—39.[15] Li Zhigang,Wu Wenchuan,Zhang Boming. A robustinterval economic dispatch method accommodating large-scale wind power generation part one dispatch schemeand mathematical model[J]. Automation of ElectricPower Systems,2014,38(20):33—39.
[16]刘文颖,文晶,谢昶,等.考虑风电消纳的电力系统源荷协调多目标优化方法[J].中国电机工程学报,2015,35(5):1079—1088.[16] Liu Wenying,Wen Jing,Xie Chang,et al. Multi-objective optimal method considering wind poweraccommodation based on source-load coordination[J].Proceedings of the CSEE,2015,35(5):1079—1088.
[17]刘德伟,黄越辉,王伟胜,等.考虑调峰和电网输送约束的省级系统风电消纳能力分析[J].电力系统自动化,2011,35(22):77—81.[17] Liu Dewei,Huang Yuefei,Wang Weisheng,et al.Analysis on provincial system available capability ofaccommodating wind power considering peak loaddispatch and transmission constraints[J]. Automation ofElectric Power Systems,2011,35(22):77—81.
[18]王秀丽,李骏,黄镔,等.促进风电消纳的区省两级电力系统调度模型[J].电网技术,2015,39(7):1833—1838.[18] Wang Xiuli,Li Jun,Huang Bin,et al. A two-stageoptimal dispatching model for provincial and regionalpower grids connected with wind farms to promoteaccommodation of wind power[J]. Power SystemTechnology,2015,39(7):1833—1838.
[19]陈颖,周海,王文鹏,等.风电场输出功率超短期预测结果分析与改进[J].电力系统自动化,2011,35(15):30—33.[19] Chen Yi, Zhou Hai, Wang Wenpeng, et al.Improvement of ultra-short-term forecast for wind power[J]. Automation of Electric Power Systems,2011,35(15):30—33.
[20]江岳文,温步瀛.结合风电功率超短期预测值偏差的实时市场调度[J].电力自动化设备,2015,35(3):12—17.[20] Jiang Yuewen,Wen Buying. Real-time market dispatchbased on ultra-short-term forecast error of wind power[J]. ElectricPowerAutomationEquipment,2015,35(3):12—17.
[21]黎灿兵,康重庆,夏清,等.发电权交易及其机理分析[J].电力系统自动化,2003,27(6):13—18.[21] Li Chanbin, Kang Chongqin, Xia Qing, et al.Generation rights trade and its mechanism[J].Automation of Electric Power Systems,2003,27(6):13—18.
[22]尚金成.基于节能减排的发电权交易理论及应用(一)发电权交易理论[J].电力系统自动化,2009,33(12):46—52.[22] Shang Jincheng. Generation right exchange theory andits applications based on energy-saving and emission-reducing(1)Generation right exchange theory[J].Automation of Electric Power Systems,2009,33(12):46—52.
[23]尚金成,何洋.基于节能减排的发电权交易理论及应用(二)发电权交易分析及应用[J].电力系统自动化,2009,33(13):37—42.[23] Shang Jincheng,He Yang. Generation right exchangetheory and its applications based on energy-saving andemission-reducing(2)Generation right exchangeanalysis and applications[J]. Automation of ElectricPower Systems,2009,33(13):37—42.
[24]周玮,孙辉,顾宏,等.计及风险备用约束的含风电场电力系统动态经济调度[J].中国电机工程学报,2012,32(1):47—55.[24] Zhou Wei, Sun Hui, Gu Hong, et al. Dynamiceconomic dispatch of wind integrated power systemsbased on risk reserve constraints[J]. Proceedings of theCSEE,2012,32(1):47—55.
[25]孙元章,吴俊,李国杰,等.基于风速预测和随机规划的含风电场电力系统动态经济调度[J].中国电机工程学报,2009,29(4):41—47.[25] Sun Yuanzhang,Wu Jun,Li Guojie,et al. Dynamiceconomic dispatch considering wind speed forecastingand stochastic programming[J]. Proceedings of theCSEE,2009,29(4):41—47.
[26]姜建国,田旻,王向前,等.采用扰动加速因子的自适应粒子群优化算法[J].西安电子科技大学学报:自然科学版,2012,39(4):74—80.[26] Jiang Jianguo, Tian Min, Wang Xiangqian, et al.Adaptive particle swarm optimization via disturbingacceleration coefficients[J]. Journal of XidianUniversity:Natural Science,2012,39(4):74—80.