4.8 Article

Superposition of Renewable-Energy Supply from Multiple Sites Maximizes Demand-Matching: Towards 100% Renewable Grids in 2050

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APPLIED ENERGY
卷 284, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2020.116402

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Solar; Wind; 100% renewable energy; Jordan; Levelized cost of electricity; Multi-objective optimization

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This research shows that optimizing a hybrid solar-wind system at multiple locations is more effective than a system at a single high-potential site, leading to a higher renewable energy system fraction. The study in Jordan demonstrates that through multi-objective optimization, it is possible to achieve nearly 100% renewable energy without the need for energy storage systems.
When planning for the transition to 100% renewable grids, areas of high solar-insolation or wind energy are often looked at as alluring sites for installation to match a country's hourly or total demand. Due to the intermittent nature of renewable energies that generate a supply-demand mismatch, this often required relatively large energy-storage systems. In this work, however, we show using Jordan as a case study, and through comparison to previous designs, that a single high-potential-site system is devious, and optimization of multiple sites to simultaneously feed into the grid can lead to a much higher renewable energy system (RES) fraction (>99%) even without storage systems; a result of utilizing the superposition of the varying energy-supply profiles at different sites to match the demand profile. Multi-objective optimization was performed using the global ParetoSearch algorithm, with RES and demand-supply fractions (DSF) on one hand, and the Levelized Cost of electricity on the other hand as a conflicting objective. Results showed that a hybrid solar-wind system optimized at multiple locations can supply 99% of the hourly demand in Jordan, forecasted for the year 2050 without an energy storage system (ESS). Additionally, the size of the RES without ESS is reduced by almost 16% when multiple sites were used compared to a single high potential location, with better matching of 99.33%. Even with an energy storage system, multiple locations led to a 14% reduction in the RES size and almost three folds reduction in ESS size compared to the single location approach.

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