Abstract
At present, China's offshore photovoltaic (PV) industry is developing rapidly. Risk assessment on offshore PV power generation (OPVPG) projects is important. The existing risk assessment methods in OPVPG projects in China are insufficient in dealing with different types of uncertainties. In this paper, we propose a computational model based on D Numbers and analytic network process (ANP) method to handle risk assessment on OPVPG projects. Firstly, factors that influencing offshore photovoltaic power generation projects in China are identified and the weights of the factors are determined by domain analyst using ANP. Secondly, risk evaluation judgment on each factor is given by expert referring to predefined anchors and linguistic labels under specific situations. Thirdly, the judgments are represented as D numbers and are integrated into a fused D number. Finally, the overall risk level of OPVPG in China is obtained based on the fused D number. The main contribution of the proposed method based on D numbers is to deal with uncertainties and the degree of confidence in experts judgments. Uncertainty includes situations like: do not know how to assign accurate beliefs to risk levels and incomplete frame of discernment. The degree of confidence shows the cognition of the experts. The situation that the confidence of expert is equal to 1 shows the certainty of experts. When the confidence of expert is equal to 0, it means that experts cannot decide the risk levels. It can be considered as a new strategy for risk assessment and enriches the framework of decision-making. Several case studies are illustrated to show the effectiveness and flexibility of the proposed method.
Highlights
Due to the serious consequences of the greenhouse effect, global energy reform is imperative to improve environmental issues
We propose a new risk assessment fusion strategy for offshore PV power generation (OPVPG) based on the D numbers and analytic network process (ANP), which can solve different kinds of uncertainty problems, and add experts’ confidence
We suggest ratings ‘‘−3, −2, −1, 0, 1, 2, 3’’ to represent different risk levels ‘‘Very Low (VL)’’, ‘‘Low (L)’’, ‘‘Medium Low (ML)’’, ‘‘Moderate (M)’’, ‘‘Medium High (MH)’’, ‘‘High (H)’’, ‘‘Very High (VH)’’
Summary
Due to the serious consequences of the greenhouse effect, global energy reform is imperative to improve environmental issues. Due to some uncertain factors such as meteorology and technology, the development of offshore photovoltaic power generation projects is restricted, and better solutions for these uncertain factors can greatly improve the stability of offshore photovoltaic power generation to reduce the risk To address this problem, a GIS based on spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis is represented [14]. We propose a new risk assessment fusion strategy for OPVPG based on the D numbers and ANP, which can solve different kinds of uncertainty problems, and add experts’ confidence (experts have a certain degree of confidence in their own judgments).
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