This contribution discusses the combined impact of the uncertainties related to the forecasts of the power production from Renewable Energy Sources, the Electrical Load and the Thermal Load on the operation costs of a microgrid. To quantify the possible variation of the cost determined by an Energy Management System, a stochastic approach has been adopted. The perturbation of the forecasted data is obtained adding to the abovementioned variables random numbers according to a suitable Probability Density Function. To this purpose, both Uniform and Normal distribution have been used. The analysis is developed referring to a test case facility: the Smart Polygeneration Microgrid of the University of Genoa. Among the possible cases, four combinations have been presented, to perturb the data with a 5%, 20% and 50% variation. The analyzed cases show that an increase in the error on the forecasts of the Electrical Load, the Thermal Load and the production from Renewable Energy Sources, causes a final cost increase. As expected, lower perturbations produce lower deviations with respect to the cost calculated by the Energy Management System. For all the presented cases, no significant differences in the minimum and maximum deviation from the costs calculated by the Energy Management System when variables are perturbated using a Normal or Uniform Probability Density Function have been found. The application of perturbations on a real test facility shows the reliability of the calculations performed by the Energy Management System, also considering the fact that the Electric Load, the Thermal Load and the power production from Renewable Energy Sources are parameters affected by uncertainty.

Impact of the uncertainties of load and forecast of power production from renewables on the operating cost of a microgrid

Alice La Fata;Massimo Brignone;Stefano Bracco
2022

Abstract

This contribution discusses the combined impact of the uncertainties related to the forecasts of the power production from Renewable Energy Sources, the Electrical Load and the Thermal Load on the operation costs of a microgrid. To quantify the possible variation of the cost determined by an Energy Management System, a stochastic approach has been adopted. The perturbation of the forecasted data is obtained adding to the abovementioned variables random numbers according to a suitable Probability Density Function. To this purpose, both Uniform and Normal distribution have been used. The analysis is developed referring to a test case facility: the Smart Polygeneration Microgrid of the University of Genoa. Among the possible cases, four combinations have been presented, to perturb the data with a 5%, 20% and 50% variation. The analyzed cases show that an increase in the error on the forecasts of the Electrical Load, the Thermal Load and the production from Renewable Energy Sources, causes a final cost increase. As expected, lower perturbations produce lower deviations with respect to the cost calculated by the Energy Management System. For all the presented cases, no significant differences in the minimum and maximum deviation from the costs calculated by the Energy Management System when variables are perturbated using a Normal or Uniform Probability Density Function have been found. The application of perturbations on a real test facility shows the reliability of the calculations performed by the Energy Management System, also considering the fact that the Electric Load, the Thermal Load and the power production from Renewable Energy Sources are parameters affected by uncertainty.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1098333
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