Introducing Multi-Stage Qualification for Micro-Level Decision-Making (MSQMLDM) Method in the Energy Sector – A case study of Photovoltaic and Wind Power in Tehran

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Sami Saleki


Buildings are consuming approximately 60% of the total electricity supply and 40% of the primary energy consumption around the world. Further, they are responsible for approximately one third of the greenhouse gas (GHG) emissions. Various approaches have been adopted to reduce energy consumption and GHG emissions in buildings such as green buildings and low-carbon buildings. In spite of the existing differences among these methods, some similarities are available, especially in using renewable energy. The present study aims to create a method for non-experts such as architects and building owners to choose the best renewable building-integrated power production units based on multiple criteria. Multi-Stage Qualification for Micro-Level Decision-Making (MSQMLDM) method is implemented to compare the electric power production units from renewable and non-renewable sources in term of technical and financial clusters. The application of the new method seems easier than the conventional Multi-Criteria Decision Making (MCDM) models, which is mostly performed by experts. Results indicates that photovoltaic and wind turbine should be adopted as two types of renewable energy technologies in Tehran. These technologies were investigated by MSQMLDM method based on different technical and energy policy conditions. Then, the best choices were classified by Preference logic, based on Optimality Theory (OT). Finally, the best choices were ranked based on cost priority and payback period priority. Based on the results, photovoltaic system without battery, with selling-contract and subsidy is regarded as the best alternative. The method tries to simplify the use of MCDM models by focusing on technical and financial issues. It is predicted that this method could be useful for larger scale projects by adding other important technical or financial priorities to the sequence.

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