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A positive/negative average real variability index and techno-economic analysis of a hybrid energy storage system

机译:A positive/negative average real variability index and techno-economic analysis of a hybrid energy storage system

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摘要

The energy storage systems are considered the prime candidates to increase the stability and penetration of renewable energy sources. However, their cost and reliability may prove to be significant obstacles for their development. A solution that is gaining momentum and can augment performance and reduce costs is hybrid energy storage systems (H-ESS). In the current study, two novel indexes are introduced aiming to capture the connection between the net demand time series volatility and a H-ESS with fast response characteristics. A new methodological framework to derive the nominal values of a H-ESS coupled to a PV/Wind system is presented. The proposed H-ESS comprises a lithium-ion battery and superconducting magnetic energy storage (SMES). The flywheel energy storage (FES) is also considered instead of the SMES to compare the performance and economic viability with the fast reserve incentive of a mature and developing technology. The techno-economic viability of the system with/without H-ESS is calculated by the levelized cost of electricity (LCOE), revealing that with a fast reserve incentive, the integration of SMES at an LCOE of 36.734 euro/MWh is the more favorable configuration compared to FES at 36.756 euro/MWh and only battery at 40.367 euro/MWh. A sensitivity analysis for the SMES and FES is conducted, concluding that we can achieve 0.84 % and 0.87 % reduction in the LCOE of SMES and FES, respectively, if the costs are halved. Furthermore, the two novel indexes verify the intuition that a net demand time series with high volatility favors a H-ESS with fast response characteristics, which can be quantified to an LCOE of 62.791 euro/MWh and 64.712 euro/MWh without fast reserve for SMES/battery and only battery configurations, respectively. This work can be utilized by market participants and/or potential investors to optimally determine their portfolios.

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