Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and ...Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.展开更多
目前储能技术路线多样,不同类型的储能各具应用前景,但储能选型需要综合考虑经济性、安全性等因素,是一个复杂的多目标决策问题,因此储能选型是工程应用中的关键问题之一。提出一种将层次分析法(analytic hierarchy process,AHP)和优劣...目前储能技术路线多样,不同类型的储能各具应用前景,但储能选型需要综合考虑经济性、安全性等因素,是一个复杂的多目标决策问题,因此储能选型是工程应用中的关键问题之一。提出一种将层次分析法(analytic hierarchy process,AHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)-模糊综合分析法相结合的储能选型评价体系。首先,通过建立评价体系的判断矩阵,利用AHP获取指标权重;其次,将判断矩阵里量纲不同的指标类型用TOPSIS做规范化处理,以此获得更客观的权重向量,改善AHP法的主观性;而后,将指标权重对角化处理并与标准化后的矩阵相乘获得加权判断矩阵,并求取贴近度向量。最后,加权判断矩阵与模糊综合分析法关系矩阵相乘获取储能类型的隶属度评价结果,并以隶属度最大值所在的等级为最终评价,处于等级Ⅰ中最佳,等级Ⅱ次之并以此类推;由此通过TOPSIS获得更客观的权重向量,改善AHP法的主观性,得到的权重向量也更客观。最后以锂离子电池、钠硫电池和铅酸电池等七种储能类型在应用于削峰填谷、电网保供电和改善电压质量场景为例,并与现有的储能选型方法进行比较,体现该评价体系的创新,检验所提评价体系和选型方法的有效性。展开更多
文摘Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.
文摘目前储能技术路线多样,不同类型的储能各具应用前景,但储能选型需要综合考虑经济性、安全性等因素,是一个复杂的多目标决策问题,因此储能选型是工程应用中的关键问题之一。提出一种将层次分析法(analytic hierarchy process,AHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)-模糊综合分析法相结合的储能选型评价体系。首先,通过建立评价体系的判断矩阵,利用AHP获取指标权重;其次,将判断矩阵里量纲不同的指标类型用TOPSIS做规范化处理,以此获得更客观的权重向量,改善AHP法的主观性;而后,将指标权重对角化处理并与标准化后的矩阵相乘获得加权判断矩阵,并求取贴近度向量。最后,加权判断矩阵与模糊综合分析法关系矩阵相乘获取储能类型的隶属度评价结果,并以隶属度最大值所在的等级为最终评价,处于等级Ⅰ中最佳,等级Ⅱ次之并以此类推;由此通过TOPSIS获得更客观的权重向量,改善AHP法的主观性,得到的权重向量也更客观。最后以锂离子电池、钠硫电池和铅酸电池等七种储能类型在应用于削峰填谷、电网保供电和改善电压质量场景为例,并与现有的储能选型方法进行比较,体现该评价体系的创新,检验所提评价体系和选型方法的有效性。
