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Title:
 
Advanced Performance Monitoring System for Improved Reliability and Optimized Levelized Cost of Electricity
 
Author(s):
 
G. Makrides, A. Phinikarides, J. Sutterlueti, S. Ransome, G.E. Georghiou
 
Keywords:
 
Lifetime, PV System, Forecasting, Energy Performance, c-Si Degradation
 
Topic:
 
Operation, Performance, Reliability and Sustainability of Photovoltaics
Subtopic: Operation of PV Systems
Event: 32nd European Photovoltaic Solar Energy Conference and Exhibition
Session: 5BV.2.38
 
Pages:
 
1973 - 1977
ISBN: 3-936338-41-8
Paper DOI: 10.4229/EUPVSEC20162016-5BV.2.38
 
Price:
 
 
0,00 EUR
 
Document(s): paper, poster
 

Abstract/Summary:


The key factor that will enable and enhance the further increase of the uptake of photovoltaic (PV) technology globally, is the reduction in PV electricity costs by increasing the lifetime output of PV systems. This can be achieved by improving the reliability and service lifetime performance through constant, solid and traceable PV plant monitoring of installed systems. In this way, the investment cost, levelised cost of electricity (LCoE) and in general PV competitiveness can be enhanced positively. It is with this background that the project “Innovative Performance Monitoring System for Improved Reliability and Optimized Levelised Cost of Electricity” (IPERMON) funded by the SOLAR-ERA.NET Transnational Calls PV3 and CSP3, has been initiated between Gantner Instruments (GI) GmbH and the PV Technology Laboratory of the University of Cyprus (UCY), in order to develop an innovative monitoring system with enhanced capabilities, far beyond the state-of-the-art. The proposed monitoring system will be capable to detect performance losses and failures, determine the degradation rate and provide accurate hourly and day-ahead power production forecasts. The scope of this work is to present the main scientific, technological and commercial objectives of the project in the field of PV performance monitoring systems and to present first results for the formulation and benchmarking of innovative guidelines and algorithms for the detection and diagnosis of performance losses, degradation and failures.