TY - JOUR
T1 - Validations of HOMER and SAM tools in predicting energy flows and economic analysis for renewable systems
T2 - Comparison to a real-world system result
AU - Vargas-Salgado, Carlos
AU - Díaz-Bello, Dácil
AU - Alfonso-Solar, David
AU - Lara-Vargas, Fabian
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/7/25
Y1 - 2024/7/25
N2 - HOMER and SAM are commonly used in the scientific field to predict future energy balances and economic analysis, but it must be evaluated if such tools provide satisfactory predictions and results when using available inputs. This paper evaluates HOMER and SAM for predicting energy balance and conducting economic analyses of renewable energy systems. Using real PV system data until 2021, the study examines the tool's accuracy in predicting energy flows, costs, and payback. Error is assessed by comparing simulation results to real results. Real data from 2022 were implemented to evaluate prediction errors. Results show that, with the data inputs used, the most significant errors occurred in load and PV production, ranging from 4.9% to 7.6% in SAM and 4.9% to 5.3% in HOMER. The study reports errors in self-consumption and electricity from/to the grid, with values ranging from 0.9% to 4.4% in SAM and 3.1% to 3.8% in HOMER. The payback error is 1.2% for SAM and 3.8% for HOMER. Finally, having validated the tools, a sensitivity analysis compares scenarios modifying energy costs and the influence of implementing battery systems.
AB - HOMER and SAM are commonly used in the scientific field to predict future energy balances and economic analysis, but it must be evaluated if such tools provide satisfactory predictions and results when using available inputs. This paper evaluates HOMER and SAM for predicting energy balance and conducting economic analyses of renewable energy systems. Using real PV system data until 2021, the study examines the tool's accuracy in predicting energy flows, costs, and payback. Error is assessed by comparing simulation results to real results. Real data from 2022 were implemented to evaluate prediction errors. Results show that, with the data inputs used, the most significant errors occurred in load and PV production, ranging from 4.9% to 7.6% in SAM and 4.9% to 5.3% in HOMER. The study reports errors in self-consumption and electricity from/to the grid, with values ranging from 0.9% to 4.4% in SAM and 3.1% to 3.8% in HOMER. The payback error is 1.2% for SAM and 3.8% for HOMER. Finally, having validated the tools, a sensitivity analysis compares scenarios modifying energy costs and the influence of implementing battery systems.
KW - HOMER
KW - Renewable system
KW - System Advisor Model (SAM)
KW - Tools validation
KW - Tools validation
KW - Renewable system
KW - HOMER
KW - System Advisor Model (SAM)
UR - http://www.scopus.com/inward/record.url?scp=85199366473&partnerID=8YFLogxK
U2 - 10.1016/j.seta.2024.103896
DO - 10.1016/j.seta.2024.103896
M3 - Artículo en revista científica indexada
AN - SCOPUS:85199366473
SN - 2213-1388
VL - 69
JO - Sustainable Energy Technologies and Assessments
JF - Sustainable Energy Technologies and Assessments
M1 - 103896
ER -