一种考虑权重不确定性的机组综合评价模型
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摘要
针对大型燃煤机组深层次节能降耗阶段的综合性能评价问题,以机组与周围环境组成的广义能量系统为对象,考虑机组可靠性、经济性及环保性等因素,综合运用蒙特卡罗方法、熵权法及层次分析法(AHP)得到评价指标线性组合权重,并采用灰色关联方法建立了燃煤机组性能综合评价模型。对6台600 MW燃煤机组应用模型进行了实例分析,以AHP权重为基础进行正态分布随机抽样,进而得到组合权重,分别取各机组指标最优值组成机组理想方案,对各机组方案与理想方案的灰色关联度进行了统计分析。结果不仅可以给出常规综合评价方法下的机组性能优劣排序,而且能够给出各机组对指标权重同时变化时的敏感性信息。当抽样标准差σ由0.015增大到0.045时,4号、3号和1号机组灰色关联度变化范围增大明显,且1号机组与6号及2号机组关联度取值区间有交集。结果表明,该评价模型具有较好的不确定因素处理能力,评价结果同时综合了专家知识与客观信息,符合客观实际,具有较好的适用性。
For comprehensive performance evaluation of large coal-fired units in the deep energy saving phase,a comprehensive evaluation model based on Monte Carlo method was established,which took the unit and its surrounding environment as object,considering the unit energy consumption,water consumption and pollution emissions factors,using gray relational method and combined weighs method. The linear combined weight was obtained by the Entropy Method and Analytic Hierarchy Process( AHP) method. A case study of six 600 MW coal-fired units was performed. A normal random sampling was carried out based on the AHP weights,and then a group of new index weight was got combined with the entropy weights. Gray relational degree of each unit was analyzed with the ideal solution,which set as the optimal value of each evaluation indices. The results can be given not only the merits of unit performance sorting which can be got under regular comprehensive evaluation method,but also the sensitive information of the index weight at the same time. And when the sample standard deviation increases from 0. 015 to 0. 045,the gray relational degree range of unit 4,3 and 1 is increased significantly,and the value of unit 1 intersect with the unit 2 and 6. The results show that this evaluation model has good ability of uncertainty processing,and also integrating in the expert knowledge and the objective information,thus it is applicable for the coal-fired unit comprehensive evaluation.
For comprehensive performance evaluation of large coal-fired units in the deep energy saving phase,a comprehensive evaluation model based on Monte Carlo method was established,which took the unit and its surrounding environment as object,considering the unit energy consumption,water consumption and pollution emissions factors,using gray relational method and combined weighs method. The linear combined weight was obtained by the Entropy Method and Analytic Hierarchy Process( AHP) method. A case study of six 600 MW coal-fired units was performed. A normal random sampling was carried out based on the AHP weights,and then a group of new index weight was got combined with the entropy weights. Gray relational degree of each unit was analyzed with the ideal solution,which set as the optimal value of each evaluation indices. The results can be given not only the merits of unit performance sorting which can be got under regular comprehensive evaluation method,but also the sensitive information of the index weight at the same time. And when the sample standard deviation increases from 0. 015 to 0. 045,the gray relational degree range of unit 4,3 and 1 is increased significantly,and the value of unit 1 intersect with the unit 2 and 6. The results show that this evaluation model has good ability of uncertainty processing,and also integrating in the expert knowledge and the objective information,thus it is applicable for the coal-fired unit comprehensive evaluation.
引文
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[2]王宁玲,杨勇平,杨志平.多变边界条件下火电机组能耗基准状态诊断[J].中国电机工程学报,2013,33(26):2-7.
[3]中华人民共和国环境保护部.GB13223-2011火电厂大气污染物排放标准[S].北京:中国标准出版社,2011.
[4]王军,李永华,阎维平.一种燃煤发电节能减排综合评价指数[J].中国电机工程学报,2011,31(S1):144-148.
[5]齐敏芳,付忠广,景源,等.基于信息熵与主成分分析的火电机组综合评价方法[J].中国电机工程学报,2013,33(2):58-64.
[6]满若岩,付忠广.基于模糊综合评判的火电厂状态评估[J].中国电机工程学报,2009,29(5):5-10.
[7]徐贵林,罗斌,马瑞.基于模糊综合评判的火电厂节能状态评估[J].电力科学与技术学报,2012,27(1):86-90.
[8]靳涛,付忠广,满若岩,等.火电厂综合评估的模糊评价法[J].热能动力工程,2010,25(5):473-477.
[9]罗毅,周创立,刘向杰.多层次灰色关联分析法在火电机组运行评价中的应用[J].中国电机工程学报,2012,32(17):97-103.
[10]黄元生,宋河,汤新发,等.基于G1-GRA的火电厂综合性能评价模型研究[J].华北电力大学学报,2014,41(2):99-102.
[11]曹国庆,邢金城,涂光备.基于灰色层次分析理论的烟气脱硫技术评价方法[J].中国电机工程学报,2006,26(4):51-55.
[12]XU G,YANG Y P,LU S Y,et al.Comprehensive evaluation of coal-fired power plants based on grey relational analysis and analytic hierarchy process[J].Energy Policy,2011,39(5):2343-2351.
[13]王新华.复杂大系统评价理论与技术[M].济南:山东大学出版社,2010.
[14]符向前,刘光临,蒋劲,等.基于信息熵的机组运行劣化度综合指标[J].电力系统自动化,2005,29(7):75-78.
[15]CHOUDHARY D,SHANKAR R.An Steep-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location:A case study from India[J].Energy,2012,42(1):510-521.
[16]董玉亮,顾煜炯,杨昆.基于蒙特卡洛模拟的发电厂设备重要度分析[J].中国电机工程学报,2003,23(8):201-205.
[17]杨允,张士杰,肖云汉,等.蒙特卡罗法在分布式供能系统不确定性评价中的应用[J].中国电机工程学报,2013,33(2):16-23.
[18]MOHAMMAD A,HASHEM S,REZA M.Monte Carlo Analytic Hierarchy Process(MAHP)approach to selection of optimum mining method[J].International Journal of Mining Science and Technology,2013,23(4):573-578.
[19]侯雨伸,王秀丽,刘杰,等.基于拟蒙特卡罗方法的电力系统可靠性评估[J].电网技术,2015,39(3):744-750.
[20]YARAGHI N,TABESH P,GUAN P,et al.Comparison of AHP and monte carlo AHP under different levels of uncertainty[J].IEEE Transactions on Engineering Management.2015,62(1):122-132.
[21]YANG J.Convergence and uncertainty analyses in monte carlo based sensitivity analysis[J].Environmental Modelling and Software,2011,26(4):444-457.
[22]李青,公维平.火力发电厂节能和指标管理技术[M].北京:中国电力出版社,2006.