Modeling and Economic Evaluation of PV Net-Metering and Self-consumption Schemes

  • Georgios C. Christoforidis
  • Ioannis P. Panapakidis
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 149)


Due to the high rate of Photovoltaics (PV) installations in many countries, the need for data processing and exploitation is a crucial factor that determines the success of the economic profitability of the installation. Machine learning is a family of tools for information retrieval and knowledge extraction. In the present study, clustering is applied to a set of PV power generation curves that correspond to locational distributed PV installations with the aim of formulating the PV generation profiles and PV clusters. Next, a techno-economic assessment of different policy schemes is applied to selected cluster. The scope is to reduce the need for conducting economic analyses per PV site; grouping PV installations in homogenous clusters can lead to reduced effort in the phase of techno-economic evaluation of the overall operation of the PV technology.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Georgios C. Christoforidis
    • 1
  • Ioannis P. Panapakidis
    • 2
  1. 1.Department of Electrical EngineeringWestern Macedonia University of Applied SciencesKila Kozanis, KozaniGreece
  2. 2.Department of Electrical EngineeringTechnological Educational Institute of ThessalyLarisaGreece

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