摘要:Computer-Assisted Personal Interviewing (CAPI) is a well-known methodology in the development of social surveys. In this work, CAPI is used to guide the flow of a questionnaire aiming for the acquisition of data and information fundamental to optimise a photovoltaic (PV) design. The questionnaire is implemented in an app, developed in the frame of the PV SPREAD project, which is aimed to support the supplier/designer of PV plants during all the stages of its development. To demonstrate how different choices of a client, specified during the interview with the designer, will have distinct economic results, two configurations are presented. In the first, the system is_allowed to determine and use the optimum inclination angle of the modules, while in the second a low angle is selected by the client, to comply with aesthetic restrictions. The first configuration improves naturally the internal rate of return of the investment, as this is the optimising cost function, but the system allows comparing both ones. The CAPI methodology and its use in the context of PV design show to be a relevant tool to support designers and to provide more informed investments to clients.
其他摘要:Computer-Assisted Personal Interviewing (CAPI) is a well-known methodology in the development of social surveys. In this work, CAPI is used to guide the flow of a questionnaire aiming for the acquisition of data and information fundamental to optimise a photovoltaic (PV) design. The questionnaire is implemented in an app, developed in the frame of the PV SPREAD project, which is aimed to support the supplier/designer of PV plants during all the stages of its development. To demonstrate how different choices of a client, specified during the interview with the designer, will have distinct economic results, two configurations are presented. In the first, the system is_allowed to determine and use the optimum inclination angle of the modules, while in the second a low angle is selected by the client, to comply with aesthetic restrictions. The first configuration improves naturally the internal rate of return of the investment, as this is the optimising cost function, but the system allows comparing both ones. The CAPI methodology and its use in the context of PV design show to be a relevant tool to support designers and to provide more informed investments to clients.