Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage

Baek, Seung Hyo; Lee, Byung Hee

doi:10.3390/su11051471

Cited by 3 publications

(2 citation statements)

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“…Using this table and by applying Model 1, we form the objective function and the constraints. The objective function is given by −0.436ω 1 + 0.283ω 2 − 0.753ω 3 + 0.326ω 4 + 0.615ω 5 − 1.163ω 6 , and the constraints are given by Step 5: Aggregate the matrices from Step 2 by using the operator proposed in Section 3.3. The order of the aggregated matrix is also 5 × 6.…”

Section: Example 1 Renewable Energy Source Selectionmentioning

confidence: 99%

“…Furthermore, there is uncertainty in the process of selection, which can be effectively managed by using fuzzy sets and its variants [5]. Baek and Lee et al [6] proposed a new design strategy for optimal selection of renewable energy system (RES) in buildings. Gonzalez et al [7] presented a conceptual model to understand the relationship among different factors that correspond to the sustainability and acceptance of RES projects.…”

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confidence: 99%

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Scientific Decision Framework for Evaluation of Renewable Energy Sources under Q-Rung Orthopair Fuzzy Set with Partially Known Weight Information

et al. 2019

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As an attractive generalization of the intuitionistic fuzzy set (IFS), q-rung orthopair fuzzy set (q-ROFS) provides the decision makers (DMs) with a wide window for preference elicitation. Previous studies on q-ROFS indicate that there is an urge for a decision framework which can make use of the available information in a proper manner for making rational decisions. Motivated by the superiority of q-ROFS, in this paper, a new decision framework is proposed, which provides scientific methods for multi-attribute group decision-making (MAGDM). Initially, a programming model is developed for calculating weights of attributes with the help of partially known information. Later, another programming model is developed for determining the weights of DMs with the help of partially known information. Preferences from different DMs are aggregated rationally by using the weights of DMs and extending generalized Maclaurin symmetric mean (GMSM) operator to q-ROFS, which can properly capture the interrelationship among attributes. Further, complex proportional assessment (COPRAS) method is extended to q-ROFS for prioritization of objects by using attributes' weight vector and aggregated preference matrix. The applicability of the proposed framework is demonstrated by using a renewable energy source prioritization problem from an Indian perspective. Finally, the superiorities and weaknesses of the framework are discussed in comparison with state-of-the-art methods.Sustainability 2019, 11, 4202 2 of 21 inferred from their analysis that India has a high scope for renewable energy sources and it can effectively manage energy crisis by proper planning and management. Recently, Mardani et al. [4] conducted a detailed analysis on the use of multi-attribute group decision-making (MAGDM) methods for solving energy management problems, and it can be inferred from the analysis that energy source evaluation and selection can be effectively solved by using MAGDM perspectives. Furthermore, there is uncertainty in the process of selection, which can be effectively managed by using fuzzy sets and its variants [5]. Baek and Lee et al. [6] proposed a new design strategy for optimal selection of renewable energy system (RES) in buildings. Gonzalez et al. [7] presented a conceptual model to understand the relationship among different factors that correspond to the sustainability and acceptance of RES projects. Cavallaro et al. [8,9] presented decision frameworks under intuitionistic fuzzy context to rationally select solar-hybrid power plants.Motivated by these claims, in this paper, we propose a new decision framework for rational prioritization of renewable energy sources. The preference information used here is q-rung orthopair fuzzy set (q-ROFS) [10], which is a powerful generalization of the intuitionistic fuzzy set (IFS) [11] and Pythagorean fuzzy set [12]. q-ROFS provides a wider window to decision makers (DMs) for preference elicitation by relaxing the constraint (sum of the degree of membership and non-membership less than or equal to...

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Section: Example 1 Renewable Energy Source Selectionmentioning

confidence: 99%

mentioning

confidence: 99%