An original multi-criteria decision-making algorithm for solar panels selection in buildings. (15th February 2021)

• Record Type: Journal Article
• Authors: El-Bayeh, Claude Ziad; Alzaareer, Khaled; Brahmi, Brahim; Zellagui, Mohamed; Eicker, Ursula
• Is Part Of: Energy. Volume 217(2021)
• Publication Date: 2021-02-15
• Subjects: Multi-criteria decision-making -- TOPSIS -- Self-sufficiency -- Smart buildings -- Solar energy -- Optimal selection.; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119396
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Nowadays, there are several thousand solar panels (SP) in the market. These panels vary in size, efficiency, cost, warranty, technology, etc. Selecting the best SP becomes complicated when other factors are added to the list, such as the available roof area, weather conditions, electricity tariffs, energy consumptions, etc. Therefore, it becomes crucial to propose an algorithm that selects the best SP for a specific client and provides the best combination of quality-cost-satisfaction. This paper presents an original multi-criteria decision-making algorithm based on the concept of Rank-Weight-Rank to select the best SP by considering many criteria. For validation purposes, our method is compared to TOPSIS, and it shows advantages, especially regarding the simulation time and the accuracy of the selection. Our approach is faster than TOPSIS, and the speed of finding the solution increases exponentially when the number of criteria and alternatives increases. Moreover, it is reliable and accurate since the probability is more than 78% for similarity of 90%–100% between both methods in selecting the same best alternative. Results show that the highest SP efficiency and the most expensive ones are not the best alternatives, nor the lowest efficient neither the cheapest SPs are the worst alternatives. Highlights: Original Multi-Criteria Decision Making Algorithm for solar panel selection. The proposed algorithm is called Rank-Weigh-Rank MCDM Algorithm. Comparison between the proposed algorithm and TOPSIS method. Our algorithm is faster than TOPSIS with 78% of similarities in ranking.