Fuzzy Model of Investor´s Decision into Photovoltaic Technologies During Pre-Design Phase

Abstract

Dissertation deals with fuzzy knowledge base supporting investor’s investment decision into the photovoltaic technologies during pre-design phase, when the engineering solution is not known yet. Probably, majority of investors have particular image about the cost and risk coming from investment into the photovoltaic technologies. However, this image is limited to the restricted knowledge areas of each investor. During the period, when the investor is planning investment into the costly photovoltaic technologies at complex, vague and heavily qualified information about the conditions and risks of investment in the specific region, where the environment is constantly inconsistent and multidimensional, it is possible to solve this complex situation with fuzzy logic. This dissertation is focusing on creation of fuzzy knowledge base with selected installed projects in Europe since 2008 and its use with expert system. Furthermore, is covering the definition and description of the variables, which are included in the investor decision making process. The complete designed architecture of the fuzzy knowledge base is tuned and five projects with different size are tested. The fuzzy knowledge base consists of overall 24 variables and 187 statements. The fuzzy knowledge base is tested with 5 projects