Long-term validated simulation of a building integrated photovoltaic system

• Published in: Solar energy Vol. 78; no. 2; pp. 163 - 176
• Main Authors: Mondol, J.D., Yohanis, Y.G., Smyth, M., Norton, B.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Oxford Elsevier Ltd 01.01.2005; Elsevier; Pergamon Press Inc
• Subjects: Applied sciences; Building integrated photovoltaics; Energy; Equipments, installations and applications; Exact sciences and technology; Inverter; Natural energy; Photovoltaic conversion; Simulation; Solar energy; TRNSYS; Inverter; TRNSYS; Simulation; Building integrated photovoltaics; Weather; Statistical test; Linear equation; Insolation; Simulation program; System simulation; Tilt; Long term; Inclined surface; Transients
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2004.04.021

Electrical and thermal simulations of a building integrated photovoltaic system were undertaken with a transient system simulation program using real field input weather data. Predicted results were compared with actual measured data. A site dependent global-diffuse correlation is proposed. The best-tilted surface radiation model for estimating insolation on the inclined surface was selected by statistical tests. To predict the module temperature, a linear correlation equation is developed which relates the temperature difference between module and ambient to insolation. Different combinations of tilted surface radiation model, global-diffuse correlation model and predicted module temperature were used to carry out the simulation and corresponding simulated results compared with the measured data to determine the best combination which gave the least error. Results show that modification of global-diffuse correlation and module temperature prediction improved the overall accuracy of the simulation model. The monthly error between measured and predicted PV output was lied below 16%. Over the period of simulation, the monthly average error between measured and predicted PV output was estimated to be 6.79% whereas, the monthly average error between measured and predicted inverter output was 4.74%.