A comprehensive data analytics framework for risk management in photovoltaic system design projects

Abstract

Risk management is an essential step of any project, which leads to a reduction in the cost of sudden losses. In the meantime, given the limited time available to make risk management decisions and the large volume of risks that cannot be considered, they should be prioritized with a comprehensive approach. In this paper, in addition to identifying the risks of the project life cycle, the aim is to use a hybrid multi-criteria decision-making (MCDM) method under fuzzy uncertainty for risk management in any photovoltaic system design (PSD) project. First, by reviewing the background, the risk factors of PSD projects are identified according to the stages of the project life cycle and introduced in the form of 2 factors in 4 categories. Next, these factors have been prioritized with a hybrid MCDM approach. These risk factors are prioritized with the cloud model (CM) and fuzzy TOPSIS method (CM-FTOPISIS). The results obtained from fuzzy TOPSIS integrate CM evaluation, which can reduce the uncertainty of the results. The research results show that incorrect project design, human resources risks, negotiation and contract signing risks, previous data risks, consumption audit risks, and equipment risks are the most critical risks in any PSD project.