Selection of a trigeneration system using a fuzzy AHP multi-criteria decision-making approach

Abstract

SUMMARYOwing to the wide range of trigeneration systems suitable for small-scale applications, the selection of the optimal system according to the end users' requirements and environmental conditions is crucial. The evaluation and comparison of possible alternatives of trigeneration systems are a multi-criteria decision problem because not only economic aspects must be considered but also technical, environmental and social aspects. This paper presents the case of selection of a trigeneration system for a typical residential building. Several kinds of trigeneration systems, whose dynamical sources are Stirling engines, micro-turbines, reciprocating engines and fuel cells, respectively, and a separate generation system are evaluated and compared in detail. As the evaluation criteria are a mixture of quantitative and qualitative criteria, quantitative multi-criteria methods are inadequate for handling this type of problems. Therefore a multi-criteria decision-making method, which combines the subjectivity of decision maker and the objectivity of numerical data, based on Fuzzy Set Theory and Analytic Hierarchy Process is proposed to solve this selection problem.

Decision making under uncertainty using a qualitative TOPSIS method for selecting sustainable energy alternatives

“…Linguistic approaches have been widely used in MCDM methods in several fields such as power generation for trigeneration systems (Nieto-Morote et al 2010;Wang et al 2008;Chang et al 2008), life cycle impact assessment (Kara and Onut 2010;Cherubini and Strømman 2011), and urban planning (Chang et al 2008;Kowkabi et al 2013;Mosadeghi et al 2015), among others. In energy planning, different aspects of environmental assessments have been considered in various studies, and examples include: developing local energy sources to rank energy alternatives (Goumas and Lygerou 2000), evaluating water resources (Dai et al 2010), assessing renewable energy alternatives (Doukas et al 2007;Kahraman et al 2010) and finding optimal locations for energy projects (Aras et al 2004;San Cristóbal 2012;Yeh and Huang 2014;Afsordegan et al 2016).…”

Selection the optimal technology for electricity generation of 5 MW using a fuzzy multi-criteria decision-making approach

“…Therefore, the selection of criteria is of prime importance in the resolution of any selection problem, meaning, that it is vital to identify a coherent family of criteria and not just any set of criteria [1]. The selection of an optimal technology for electricity generation has often been based on a single criterion: economic or technological criterion.…”

“…With respect to the social acceptance, the criterion enhances consensus among social partners. Finally the labour impact, it takes into account the direct and indirect employment and the possible indirect creation of new professional figures are also assessed [1].…”

Evaluation of Combined Heat and Power (CHP) Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

“…In particular, we can mention the following: Wang et al, (2008) who offered a fuzzy multicriteria decision-making model (FMCDM) for the selection and evaluation of several kinds of trigeneration systems [15]; Nieto-Morote et al, (2011), who presented the case of the selection of a trigeneration system for a typical residential building [16]; Pilavachi et al, (2006), who evaluated 16 kinds of CHP systems using a multicriteria method [17]; , who evaluated 16 kinds of CHP systems using weighting methodologies following a multicriteria approach [18]; Ebrahimi and Keshavarz (2013), who proposed a multicriteria sizing function (MCSF) for designing the optimum size and operating strategy of a residential micro-combined cooling heating and power (CCHP) system [19], and, finally, Carvalho, Lozano and Serra (2012), who proposed a mixed-integer linear programming (MILP) model to assess a trigeneration system to be installed in a hospital [20].…”