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.
| Original language | English |
|---|---|
| Article number | 119396 |
| Journal | Energy |
| Volume | 217 |
| DOIs | |
| State | Published - 15 Feb 2021 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Elsevier Ltd
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Multi-criteria decision-making
- Optimal selection.
- Self-sufficiency
- Smart buildings
- Solar energy
- TOPSIS
ASJC Scopus subject areas
- Civil and Structural Engineering
- Modeling and Simulation
- Renewable Energy, Sustainability and the Environment
- Building and Construction
- Fuel Technology
- Energy Engineering and Power Technology
- Pollution
- Mechanical Engineering
- General Energy
- Management, Monitoring, Policy and Law
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
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