化工学报
化工學報
화공학보
JOURNAL OF CHEMICAL INDUSY AND ENGINEERING (CHINA)
2015年
3期
1051-1058
,共8页
许俊俊%罗向龙%王永真%朱倩南%陈颖%莫松平%黄宏宇
許俊俊%囉嚮龍%王永真%硃倩南%陳穎%莫鬆平%黃宏宇
허준준%라향룡%왕영진%주천남%진영%막송평%황굉우
有机朗肯循环%工质优选%多级模糊优化%非结构性模糊决策%过程系统%模型%优化设计
有機朗肯循環%工質優選%多級模糊優化%非結構性模糊決策%過程繫統%模型%優化設計
유궤랑긍순배%공질우선%다급모호우화%비결구성모호결책%과정계통%모형%우화설계
ORC%working fluid selection%multilevel fuzzy optimization%non-structural fuzzy decision%process systems%model%optimal design
工质的选择是有机朗肯循环(ORC)系统优化中的关键问题之一。建立了基于多级非结构性模糊决策分析方法的ORC工质优选体系,根据影响因素的非结构性的特点建立三级模糊优选模型,综合考虑ORC系统的技术性能、经济性能和环保性能3方面因素的影响,并针对影响 ORC 工质优选的因素复杂、确定隶属函数主观因素较强的情况引入非结构性模糊决策法以确定其隶属度与权重。应用此模型对150℃热源条件下某ORC系统进行工质的优选,得到了不同评价级对应的优选工质序列。R123是对应三级评价准则下该ORC系统的最优工质,验证了多级非结构性模糊决策模型在ORC工质优选中的适用性。
工質的選擇是有機朗肯循環(ORC)繫統優化中的關鍵問題之一。建立瞭基于多級非結構性模糊決策分析方法的ORC工質優選體繫,根據影響因素的非結構性的特點建立三級模糊優選模型,綜閤攷慮ORC繫統的技術性能、經濟性能和環保性能3方麵因素的影響,併針對影響 ORC 工質優選的因素複雜、確定隸屬函數主觀因素較彊的情況引入非結構性模糊決策法以確定其隸屬度與權重。應用此模型對150℃熱源條件下某ORC繫統進行工質的優選,得到瞭不同評價級對應的優選工質序列。R123是對應三級評價準則下該ORC繫統的最優工質,驗證瞭多級非結構性模糊決策模型在ORC工質優選中的適用性。
공질적선택시유궤랑긍순배(ORC)계통우화중적관건문제지일。건립료기우다급비결구성모호결책분석방법적ORC공질우선체계,근거영향인소적비결구성적특점건립삼급모호우선모형,종합고필ORC계통적기술성능、경제성능화배보성능3방면인소적영향,병침대영향 ORC 공질우선적인소복잡、학정대속함수주관인소교강적정황인입비결구성모호결책법이학정기대속도여권중。응용차모형대150℃열원조건하모ORC계통진행공질적우선,득도료불동평개급대응적우선공질서렬。R123시대응삼급평개준칙하해ORC계통적최우공질,험증료다급비결구성모호결책모형재ORC공질우선중적괄용성。
Selection of working fluid is one of the key issues in the organic Rankine cycle (ORC) waste-heat power generation technology. Multi-criteria methods for working fluid selection are urgent to be studied. Existing researches are mostly under the constraints of specific thermodynamic and structural conditions. Contradictory findings exist in many studies, because there is no general optimization method for ORC working fluid selection. A method using multi-level fuzzy optimization and non-structural fuzzy decision was developed to solve the problem. Comprehensive considerations of technical,economic performance and environmental protection of ORC systems are presented. Since the factors that influence ORC working fluid selection are multi-level and non-structural,establishment of a three-level fuzzy optimization model to obtain a more satisfactory result is preferable.