天然气消费结构多目标优化分配模型
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摘要
近年来冬季供暖期天然气消费需求持续旺盛,供需形势较为严峻,天然气紧缺又造成燃气机组(电网重要的调峰电源)的调峰能力无法有效发挥,严重制约了风电消纳能力。如何在冬季天然气供应紧张时期,考虑天然气的各类用途,实现天然气的合理分配,成为值得研究的重要课题。为此,引入粒子群多目标优化理论,充分考虑供给侧风电消纳与需求侧天然气负荷,综合设计了天然气供应收入最大化、供给侧风电消纳量最大化与天然气供应不确定性最小化3个目标函数,结合效用理论构建了考虑供应不确定性和调峰能力约束的天然气消费结构多目标优化分配模型,并以北京市城六区(东城区、西城区、朝阳区、海淀区、丰台区和石景山区)为例进行了模拟优化。研究结果表明:①天然气定价宜同时考虑社会效用和用户效用;②燃气机组调峰所带来的风电消纳效益受机组基本负荷利用小时数、燃气发电用气量以及供热期等因素的影响,从而验证了天然气消费结构的优化效果;③上述城六区应在原有天然气消费结构的基础上,小幅度增加发电、供热用气比例,保持商业及其他用气消费量稳定,大幅度缩减工业及天然气汽车用气量,以尽量满足居民用气量增加的需求。结论认为:北京市城六区优化后的天然气消费结构在满足各方天然气消费需求的同时,增加了总收入,提升了燃气机组调峰消纳风电的能力,证明该多目标优化分配模型能够为区域天然气消费结构优化调整提供理论和技术支撑。
Natural gas is being increasingly applied to power generation, heating and residential life because of its cleanliness, and gasfired units have been an important peak shaving power for national power grids. However, in recent years, the problem of "gas shortage" has severely restricted the peaking capacity of gas-fired units and the wind power accommodation during the heating period. How to take into account all kinds of possible usages of natural gas so as to achieve the rational distribution of natural gas especially when the tight supply of natural gas occurs in winter is worth studying. In view of this, based on the particle swarm multi-objective optimization theory, we fully considered both the wind power accommodation in supply side and the natural gas load in demand side, and set three goals including maximizing the cost of natural gas and the quantity of wind power curtailment, minimizing the uncertainty of natural gas supply. Then, combining with the utility theory, we calculated the social utility and user utility resulting from natural gas consumption, and built a natural gas consumption structure multi-objective optimal allocation model considering supply uncertainty and peaking capacity constraint. Taking Beijing(including Dongcheng, Xicheng, Chaoyang, Haidian, Fengtai and Shijingshan districts) as an example, we conducted an empirical analysis and obtained the optimized gas ratios of different kinds of users including natural gas generation, heating, industrial, commercial, residential, and natural gas vehicles. The following findings were obtained. First, natural gas pricing should consider both social utility and user utility. Second, the optimized natural gas consumption structure would satisfy the demand of various types of users, increase the gross income and improve the wind power accommodation with gas-fired units peak-shaving at the same time.Third, based upon the primary gas consumption structure, the above six districts in Beijing should increase the proportion of gas used for power generation and heating by a small margin with a significant reduction of gas consumption for industry and natural gas vehicles to fully satisfy the increasing demand for gas. In conclusion, the optimized model provides support for the optimization and adjustment of regional natural gas consumption structure.
Natural gas is being increasingly applied to power generation, heating and residential life because of its cleanliness, and gasfired units have been an important peak shaving power for national power grids. However, in recent years, the problem of "gas shortage" has severely restricted the peaking capacity of gas-fired units and the wind power accommodation during the heating period. How to take into account all kinds of possible usages of natural gas so as to achieve the rational distribution of natural gas especially when the tight supply of natural gas occurs in winter is worth studying. In view of this, based on the particle swarm multi-objective optimization theory, we fully considered both the wind power accommodation in supply side and the natural gas load in demand side, and set three goals including maximizing the cost of natural gas and the quantity of wind power curtailment, minimizing the uncertainty of natural gas supply. Then, combining with the utility theory, we calculated the social utility and user utility resulting from natural gas consumption, and built a natural gas consumption structure multi-objective optimal allocation model considering supply uncertainty and peaking capacity constraint. Taking Beijing(including Dongcheng, Xicheng, Chaoyang, Haidian, Fengtai and Shijingshan districts) as an example, we conducted an empirical analysis and obtained the optimized gas ratios of different kinds of users including natural gas generation, heating, industrial, commercial, residential, and natural gas vehicles. The following findings were obtained. First, natural gas pricing should consider both social utility and user utility. Second, the optimized natural gas consumption structure would satisfy the demand of various types of users, increase the gross income and improve the wind power accommodation with gas-fired units peak-shaving at the same time.Third, based upon the primary gas consumption structure, the above six districts in Beijing should increase the proportion of gas used for power generation and heating by a small margin with a significant reduction of gas consumption for industry and natural gas vehicles to fully satisfy the increasing demand for gas. In conclusion, the optimized model provides support for the optimization and adjustment of regional natural gas consumption structure.
引文
[1]Dong Xiucheng,Pi Guanglin,Ma Zhengwei&Dong Cong.The reform of the natural gas industry in the PR of China[J].Renewable and Sustainable Energy Reviews,2017,73(1):582-593.
[2]Wang Ting&Lin Boqiang.China's natural gas consumption peak and factors analysis:A regional perspective[J].Journal of Cleaner Production,2017,142(2):548-564.
[3]邹莉娜,张荣,任庆忠.天然气储备对天然气进口及国内价格的动态影响[J].中国管理科学,2017,25(6):132-142.Zou Lina,Zhang Rong&Ren Qingzhong.The effect of natural gas reserve on the import and price of a gas-importing country[J].Chinese Journal of Management Science,2017,25(6):132-142.
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[5]张书铨,孙竹,刘扬.2017年季节性供气紧张的原因与对策[J].天然气工业,2018,38(7):120-128.Zhang Shuquan,Sun Zhu&Liu Yang.Reasons and countermeasures for the seasonal gas shortage in 2017[J].Natural Gas Industry,2018,38(7):120-128.
[6]王雁凌,田彦鹏,吴梦凯,耿介雯.基于模糊聚类的燃气机组调峰两部制电价模型[J].中国电机工程学报,2017,37(6):1610-1618.Wang Yanling,Tian Yanpeng,Wu Mengkai&Geng Jiewen.Twopart electricity price model for peak load regulation of natural gas power based on fuzzy clustering[J].Proceedings of the CSEE,2017,37(6):1610-1618.
[7]刘文颖,文晶,谢昶,王维洲,梁琛.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.Liu Wenying,Wen Jing,Xie Chang,Wang Weizhou&Liang Chen.Multi-objective optimal method considering wind power accommodation based on source-load coordination[J].Proceedings of the CSEE,2015,35(5):1079-1088.
[8]杨帅,陈磊,徐飞,孙亮,陈群,贺克伦,等.基于能量流的电热综合能源系统弃风消纳优化调度模型[J].电网技术,2018,42(2):417-426.Yang Shuai,Chen Lei,Xu Fei,Sun Liang,Chen Qun,He Kelun,et al.Optimal dispatch model of wind power accommodation in integrated electrical-thermal power system based on power flow model[J].Power System Technology,2018,42(2):417-426.
[9]Li Lanlan,Gong Chengzhu,Tian Shizhong&Jiao Jianling.The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers:Evidence from multi-agent simulation[J].Energy,2016(96):48-58.
[10]胡殿刚,潘正婕,徐昊亮,靳攀润.大规模可再生能源并网条件下天然气机组调峰空间估算[J].电力系统保护与控制,2017,45(3):87-93.Hu Diangang,Pan Zhengjie,Xu Haoliang&Jin Panrun.Peaking capacity estimation of natural gas unit under the condition of large-scale renewable energy connecting with power grid[J].Power System Protection and Control,2017,45(3):87-93.
[11]李光.序数效用理论在薪酬配比方式决策中的应用[J].中国软科学,2010,96(10):186-192.Li Guang.Application of the ordinal utility theory in the decision-making of compensation allocated proportion[J].China Soft Science,2010,96(10):186-192.
[12]Kiran MS.Particle swarm optimization with a new update mechanism[J].Applied Soft Computing,2017,60(7):670-678.
[13]Figueiredo EMN,Ludermir TB&Bastos-Filho CJA.Many-objective particle swarm optimization[J].Information Sciences,2016,374:115-134.
[14]MikolajkováM,Saxen H&Pettersson F.Linearization of an MINLP model and its application to gas distribution optimization[J].Energy,2018,146:156-168.
[15]Felipe da Silva Alves,Jame Neiva Miranda de Souza,AndréLuiz Hemerly Costa.Multi-objective design optimization of natural gas transmission networks[J].Computers&Chemical Engineering,2016,93:212-220.
[16]Demissie A,Zhu Weihang&Belachew CT.A multi-objective optimization model for gas pipeline operations[J].Computers&Chemical Engineering,2017,100(2):94-103.
[17]黄燕菲,吴长春,陈潜,王莉,左丽丽,赵亚南,等.基于不确定性用气量的输气管网供气可靠度计算方法[J].天然气工业,2018,38(8):126-133.Huang Yanfei,Wu Changchun,Chen Qian,Wang Li,Zuo Lili,Zhao Yanan,et al.A computation model for gas supply reliability analysis in a gas pipeline network based upon the uncertainty of gas consumption[J].Natural Gas Industry,2018,38(8):126-133.
[18]Wang Ting&Lin Boqiang.China's natural gas consumption and subsidies-From a sector perspective[J].Energy Policy,2014(65):541-551.
[19]罗毅,邵周策,张磊,姚良忠.考虑风电不确定性和气网运行约束的鲁棒经济调度和备用配置[J].电工技术学报,2017,32(23):21-32.Luo Yi,Shao Zhouce,Zhang Lei&Yao Liangzhong.Robust economic dispatch and reserve configuration considering wind uncertainty and gas network constraints[J].Transactions of China Electrotechnical Society,2017,32(23):21-32.
[20]杨毅,周志斌,李长俊.天然气用户用气量分配优化模型[J].天然气工业,2009,29(4):115-116.Yang Yi,Zhou Zhibin&Li Changjun.An optimization model of gas consumption amount allocation for natural gas users[J].Natural Gas Industry,2009,29(4):115-116.
[21]BP.BP Statistical review of world energy 2018[R].London:BP,2018.
[22]周凌安,申建建,李继红,张俊,程春田,吴慧军.日启停燃气机组调峰运行方法[J].中国电机工程学报,2017,37(20):5913-5921.Zhou Ling'an,Shen Jianjian,Li Jihong,Zhang Jun,Cheng Chuntian&Wu Huijun.Peak regulation method for daily start-stop gas-fired units[J].Proceedings of the CSEE,2017,37(20):5913-5921.
[23]贾德香,韩净.燃气发电的发展及其对电网调峰和经济性影响研究[J].中国电力,2013,46(7):149-152.Jia Dexiang&Han Jing.Development planning of natural gas power generation and its influence on power system's peak load regulation and economy[J].Electric Power,2013,46(7):149-152.
[24]王智冬,刘连光,刘自发,王帅,由子昂.基于量子粒子群算法的风火打捆容量及直流落点优化配置[J].中国电机工程学报,2014,34(13):2055-2062.Wang Zhidong,Liu Lianguang,Liu Zifa,Wang Shuai&You Zi'ang.Optimal configuration of wind&coal power capacity and DC placement based on quantum PSO algorithm[J].Proceedings of the CSEE,2014,34(13):2055-2062.
[25]张宏宇,印永华,申洪,何剑,赵珊珊.大规模风电接入后的系统调峰充裕性评估[J].中国电机工程学报,2011,31(22):26-31.Zhang Hongyu,Yin Yonghua,Shen Hong,He Jian&Zhao Shanshan.Peak-load regulating adequacy evaluation associated with large-scale wind power integration[J].Proceedings of the CSEE,2011,31(22):26-31.
[2]Wang Ting&Lin Boqiang.China's natural gas consumption peak and factors analysis:A regional perspective[J].Journal of Cleaner Production,2017,142(2):548-564.
[3]邹莉娜,张荣,任庆忠.天然气储备对天然气进口及国内价格的动态影响[J].中国管理科学,2017,25(6):132-142.Zou Lina,Zhang Rong&Ren Qingzhong.The effect of natural gas reserve on the import and price of a gas-importing country[J].Chinese Journal of Management Science,2017,25(6):132-142.
[4]魏欢,田静,李波,高永刚,王影,朱丽丽.中国天然气储气调峰方式研究[J].天然气工业,2016,36(8):145-150.Wei Huan,Tian Jing,Li Bo,Gao Yonggang,Wang Ying&Zhu Lili.Research on natural gas storage and peak-shaving models in China[J].Natural Gas Industry,2016,36(8):145-150.
[5]张书铨,孙竹,刘扬.2017年季节性供气紧张的原因与对策[J].天然气工业,2018,38(7):120-128.Zhang Shuquan,Sun Zhu&Liu Yang.Reasons and countermeasures for the seasonal gas shortage in 2017[J].Natural Gas Industry,2018,38(7):120-128.
[6]王雁凌,田彦鹏,吴梦凯,耿介雯.基于模糊聚类的燃气机组调峰两部制电价模型[J].中国电机工程学报,2017,37(6):1610-1618.Wang Yanling,Tian Yanpeng,Wu Mengkai&Geng Jiewen.Twopart electricity price model for peak load regulation of natural gas power based on fuzzy clustering[J].Proceedings of the CSEE,2017,37(6):1610-1618.
[7]刘文颖,文晶,谢昶,王维洲,梁琛.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.Liu Wenying,Wen Jing,Xie Chang,Wang Weizhou&Liang Chen.Multi-objective optimal method considering wind power accommodation based on source-load coordination[J].Proceedings of the CSEE,2015,35(5):1079-1088.
[8]杨帅,陈磊,徐飞,孙亮,陈群,贺克伦,等.基于能量流的电热综合能源系统弃风消纳优化调度模型[J].电网技术,2018,42(2):417-426.Yang Shuai,Chen Lei,Xu Fei,Sun Liang,Chen Qun,He Kelun,et al.Optimal dispatch model of wind power accommodation in integrated electrical-thermal power system based on power flow model[J].Power System Technology,2018,42(2):417-426.
[9]Li Lanlan,Gong Chengzhu,Tian Shizhong&Jiao Jianling.The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers:Evidence from multi-agent simulation[J].Energy,2016(96):48-58.
[10]胡殿刚,潘正婕,徐昊亮,靳攀润.大规模可再生能源并网条件下天然气机组调峰空间估算[J].电力系统保护与控制,2017,45(3):87-93.Hu Diangang,Pan Zhengjie,Xu Haoliang&Jin Panrun.Peaking capacity estimation of natural gas unit under the condition of large-scale renewable energy connecting with power grid[J].Power System Protection and Control,2017,45(3):87-93.
[11]李光.序数效用理论在薪酬配比方式决策中的应用[J].中国软科学,2010,96(10):186-192.Li Guang.Application of the ordinal utility theory in the decision-making of compensation allocated proportion[J].China Soft Science,2010,96(10):186-192.
[12]Kiran MS.Particle swarm optimization with a new update mechanism[J].Applied Soft Computing,2017,60(7):670-678.
[13]Figueiredo EMN,Ludermir TB&Bastos-Filho CJA.Many-objective particle swarm optimization[J].Information Sciences,2016,374:115-134.
[14]MikolajkováM,Saxen H&Pettersson F.Linearization of an MINLP model and its application to gas distribution optimization[J].Energy,2018,146:156-168.
[15]Felipe da Silva Alves,Jame Neiva Miranda de Souza,AndréLuiz Hemerly Costa.Multi-objective design optimization of natural gas transmission networks[J].Computers&Chemical Engineering,2016,93:212-220.
[16]Demissie A,Zhu Weihang&Belachew CT.A multi-objective optimization model for gas pipeline operations[J].Computers&Chemical Engineering,2017,100(2):94-103.
[17]黄燕菲,吴长春,陈潜,王莉,左丽丽,赵亚南,等.基于不确定性用气量的输气管网供气可靠度计算方法[J].天然气工业,2018,38(8):126-133.Huang Yanfei,Wu Changchun,Chen Qian,Wang Li,Zuo Lili,Zhao Yanan,et al.A computation model for gas supply reliability analysis in a gas pipeline network based upon the uncertainty of gas consumption[J].Natural Gas Industry,2018,38(8):126-133.
[18]Wang Ting&Lin Boqiang.China's natural gas consumption and subsidies-From a sector perspective[J].Energy Policy,2014(65):541-551.
[19]罗毅,邵周策,张磊,姚良忠.考虑风电不确定性和气网运行约束的鲁棒经济调度和备用配置[J].电工技术学报,2017,32(23):21-32.Luo Yi,Shao Zhouce,Zhang Lei&Yao Liangzhong.Robust economic dispatch and reserve configuration considering wind uncertainty and gas network constraints[J].Transactions of China Electrotechnical Society,2017,32(23):21-32.
[20]杨毅,周志斌,李长俊.天然气用户用气量分配优化模型[J].天然气工业,2009,29(4):115-116.Yang Yi,Zhou Zhibin&Li Changjun.An optimization model of gas consumption amount allocation for natural gas users[J].Natural Gas Industry,2009,29(4):115-116.
[21]BP.BP Statistical review of world energy 2018[R].London:BP,2018.
[22]周凌安,申建建,李继红,张俊,程春田,吴慧军.日启停燃气机组调峰运行方法[J].中国电机工程学报,2017,37(20):5913-5921.Zhou Ling'an,Shen Jianjian,Li Jihong,Zhang Jun,Cheng Chuntian&Wu Huijun.Peak regulation method for daily start-stop gas-fired units[J].Proceedings of the CSEE,2017,37(20):5913-5921.
[23]贾德香,韩净.燃气发电的发展及其对电网调峰和经济性影响研究[J].中国电力,2013,46(7):149-152.Jia Dexiang&Han Jing.Development planning of natural gas power generation and its influence on power system's peak load regulation and economy[J].Electric Power,2013,46(7):149-152.
[24]王智冬,刘连光,刘自发,王帅,由子昂.基于量子粒子群算法的风火打捆容量及直流落点优化配置[J].中国电机工程学报,2014,34(13):2055-2062.Wang Zhidong,Liu Lianguang,Liu Zifa,Wang Shuai&You Zi'ang.Optimal configuration of wind&coal power capacity and DC placement based on quantum PSO algorithm[J].Proceedings of the CSEE,2014,34(13):2055-2062.
[25]张宏宇,印永华,申洪,何剑,赵珊珊.大规模风电接入后的系统调峰充裕性评估[J].中国电机工程学报,2011,31(22):26-31.Zhang Hongyu,Yin Yonghua,Shen Hong,He Jian&Zhao Shanshan.Peak-load regulating adequacy evaluation associated with large-scale wind power integration[J].Proceedings of the CSEE,2011,31(22):26-31.
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