A model for measuring the success of distributed small-scale photovoltaic systems projects

• Published in: Solar energy Vol. 205; pp. 241 - 253
• Main Authors: Rigo, Paula D., Siluk, Julio Cezar M., Lacerda, Daniel P., Rediske, Graciele, Rosa, Carmen B.
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.07.2020; Pergamon Press Inc
• Subjects: Analytic hierarchy process; Business metrics; Decision analysis; Distributed generation; Energy; Indicators; Investment; Multiple criterion; Photovoltaic cells; Photovoltaics; Public policy; Small scale technology; Small-scale generation; Solar energy; Solar photovoltaic energy; Success; Support decision; DG; Support decision; KPI; PV; CSF; MCDA; Small-scale generation; AHP; Distributed generation; Solar photovoltaic energy; FPV
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2020.04.078

[Display omitted] •A mathematical modeling to measure success considering six perspectives;•A computational conceptual model based on BPMN notation;•The application in 32 small-scale projects (residence, commerce, and industry);•Reliability analysis and sensitivity analysis. Small-scale Distributed Generation through photovoltaic technology is promising, driven by government policies and lower component prices. However, the large amount to be invested, the characteristics of photovoltaic energy, and the uncertainties regarding this technology make it difficult to secure the investment decision and to visualize the success potentiality. Our objective is to propose a success measurement model for the small-scale distributed generation projects' implementation of photovoltaic energy. The methodological approach to modeling encompasses the concepts of Key Performance Indicators and Multicriteria Decision Analysis based on Analytic Hierarchy Process. We researched with 19 experts (researchers) and 32 investors in photovoltaic energy. The model made it possible to weigh the indicators and measure the projects' success under evaluation. Of the projects diagnosed, 15 achieved a Global Success Index of over 76%, considered “Full Success” and 17 were judged as “Potential Success”. We identified that improvement in some Key Performance Indicators could advance to “Full Success” level projects framed as “Potential Success”. Thus, the model contributes to reflection and learning, given our indicators analysis. The main contribution we highlight is the measurement approach developed for the model serving to generate new measurement models. Such models may incorporate other themes, contextual factors, and considerations different from those performed in this case. Applying this model to future projects can provide consistent decisions or make robust new small-scale photovoltaic projects.