Photovoltaics output model with independent weather factors. Implications for the capacity management and its sensitivity analysis
Model empiryczny produkcji fotowoltaicznej z niezależnymi zmiennymi meteo. Rekomendacje dla planowania mocy zainstalowanej i jej analizy wrażliwości
Tomasz Brzeczek
Streszczenie
Businesses and households that operate photovoltaics became prosumers of energy. A prosumer produces solar
energy for self-consumption and exports production surplus to the grid. When consumption exceeds production the missing
energy is imported from the grid. We analyze the photovoltaics stand-alone optimal capacity for which energy flows between
a prosumer and the grid compensate fully. This considers that net-metering equals 0 and export to the grid is balanced with
import from the grid. Under net-billing energy export is subject to financial risk due to market price. However, installation of
energy warehouse of appropriate capacity mitigates this problem. We apply the optimization model known from the literature
although verified here with empirical hourly output during whole year and its generalized least squares regression. We propose
how to measure risk of energy flows imbalance with confidence interval for mean efficiency of photovoltaics. Additionally,
costs relation range for the optimal capacity solution is considered. The bigger the estimate is the smaller the output risk is
and the shorter is optimal capacity interval. We control results for weather independent variables such as wind, air pressure,
temperature and humidity.
energy for self-consumption and exports production surplus to the grid. When consumption exceeds production the missing
energy is imported from the grid. We analyze the photovoltaics stand-alone optimal capacity for which energy flows between
a prosumer and the grid compensate fully. This considers that net-metering equals 0 and export to the grid is balanced with
import from the grid. Under net-billing energy export is subject to financial risk due to market price. However, installation of
energy warehouse of appropriate capacity mitigates this problem. We apply the optimization model known from the literature
although verified here with empirical hourly output during whole year and its generalized least squares regression. We propose
how to measure risk of energy flows imbalance with confidence interval for mean efficiency of photovoltaics. Additionally,
costs relation range for the optimal capacity solution is considered. The bigger the estimate is the smaller the output risk is
and the shorter is optimal capacity interval. We control results for weather independent variables such as wind, air pressure,
temperature and humidity.