A recent study published in the journal Sustainability evaluated the performance of two reanalysis datasets for estimating solar radiation, wind speed, and temperature in La Guajira, Colombia's coastal region. The researchers also assessed how these datasets influence the optimal configuration of a renewable energy-based water desalination plant across various operational scenarios.
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Background
The global challenge of unequal access to water and electricity drives the exploration of solutions based on renewable energies and desalination. Accurate sizing of renewable systems necessitates reliable and extensive time series data, often unavailable. Reanalysis models offer a potential solution, but their local accuracy must be rigorously evaluated using performance metrics.
About the Research
In this paper, the authors evaluated the fifth-generation accurate global atmospheric reanalysis (ERA5) land (ERA5-Land) and the modern-era retrospective analysis for research and applications, version 2 (MERRA2) datasets. They aimed to assess the feasibility of using reanalysis data to address the data scarcity issue for planning renewable energy projects, specifically for water desalination in La Guajira.
The researchers utilized HOMER Pro software to model and simulate hybrid renewable energy systems incorporating photovoltaic (PV) panels, batteries, converters, and diesel generators. This approach aimed to determine optimal configurations considering different operational regimes, energy consumption levels, and annual capacity shortages to supply electricity to a reverse osmosis seawater desalination (SWRO) plant for a population of 10,000.
The study investigated three energy consumption values per cubic meter of water (2.5 kWh/m³, 4.0 kWh/m³, and 8.5 kWh/m³) and three annual capacity shortage levels (0%, 5%, and 10%). It also examined two operational regimes for the desalination plant: 24-hour and 8-hour operation during daylight hours.
Hourly time series data for solar radiation, wind speed, and temperature from 2016 served as inputs for the HOMER model. These data were sourced from three references: the Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM) station at Aeropuerto Almirante Padilla, the ERA5-Land reanalysis dataset, and the MERRA2 reanalysis dataset.
The performance of the reanalysis datasets was evaluated against ground measurements from a local meteorological station, employing four statistical metrics: normalized root-mean-square error (NRMSE), bias (BIAS), Spearman correlation coefficient (ρS), and Nash–Sutcliffe efficiency coefficient (NSE).
Paired t-tests and Wilcoxon tests were conducted to compare the optimal systems derived from the reanalysis datasets with those based on ground measurements. Variables such as the cost of electricity (COE), PV size, energy storage capacity, and excess electricity were considered in these comparative analyses.
Research Findings
The outcomes indicated that ERA5-Land outperformed MERRA2 in matching solar radiation, wind speed, and temperature time series from the IDEAM station, showing lower errors and biases and higher correlations and efficiencies. The authors also noted that the impact of reanalysis datasets on wind speed estimation was more significant than on solar radiation, with positive biases up to 40%. Interestingly, despite discrepancies, optimal systems did not include wind turbines, with PV dominating in all cases.
The paper indicated that the optimal systems derived from ERA5-Land were statistically similar to those obtained from IDEAM, while those obtained from MERRA2 showed significant differences. This suggests a higher accuracy and reliability of ERA5-Land as an alternative data source.
Regarding the cost analysis, the researchers found that the cost of electricity (COE) for the optimal systems ranged from 83 EUR/MWh to 199 EUR/MWh, depending on factors such as operational regime, energy consumption, and annual capacity shortage. Notably, the 8-hour operating regime resulted in a lower COE than the 24-hour regime. Relaxing the annual capacity shortage to 5% also led to lower COE and excess electricity.
The cost of producing water from SWRO ranged from 0.20 EUR/m³ to 1.60 EUR/m³, depending on similar factors. These costs were compared with those reported in the literature and observed in the region, indicating they were competitive and attractive for addressing the water scarcity problem.
Applications
The research showcased the promise of harnessing renewable energy sources to offer clean and sustainable solutions for water production and other fundamental needs in data-scarce regions like La Guajira. It underscored the importance of leveraging reanalysis datasets, particularly ERA5-Land, to address the absence of reliable data for planning renewable energy initiatives, specifically for water desalination projects. The study offered an initial assessment of such endeavors' economic and technical viability, laying the groundwork for more in-depth investigations.
Conclusion
The researchers summarized that ERA5-Land reanalysis is a reliable alternative for mitigating the shortage of solar resource data in coastal regions. In contrast, MERRA2 reanalysis struggled to replicate wind speed patterns accurately and resulted in significantly divergent optimal system configurations, indicating lower reliability and accuracy.
They recommended future studies to integrate systems that address community water production and electricity supply needs, utilizing extended time series in regions with greater wind power potential within La Guajira. To improve the reliability of such analyses further, they suggested employing correction methods to enhance the precision of reanalysis datasets.
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Source:
Vargas-Brochero, J.; Hurtado-Castillo, S.; Altamiranda, J.; de Menezes Filho, F.C.M.; Beluco, A.; Canales, F.A. Optimizing Renewable Energy Systems for Water Security: A Comparative Study of Reanalysis Models. Sustainability 2024, 16, 4862. https://doi.org/10.3390/su16114862