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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Enhancing energy system resilience using tidal stream energy

Authors: Coles, D; Coyne, R; Miles, J;

Enhancing energy system resilience using tidal stream energy

Abstract

During autumn 2021, high global gas demand led to a 400% increase in imported wholesale gas prices in the UK. This coincided with (i) an extended period of low wind resource, where wind turbines provided 60% less energy than typical levels for the time of year, (ii) low nuclear power availability and (iii) depleting domestic natural gas reserves. These simultaneous events led to UK wholesale electricity prices more than doubling. The 2022 military and political impact of Russia’s invasion of Ukraine has led to additional increases in imported fuel prices. These types of disruption have the potential to cause damage worth years of sector revenues [1]. In the future, energy resilience challenges must be overcome whilst also achieving net-zero to limit global warming to within 1.5 degrees Celsius above pre-industrial levels, whilst electricity demand at least doubles. This research investigates the role of tidal stream energy in enhancing energy system resilience during periods when the energy system is highly stressed, such as during autumn 2021 in the UK. The concept of resilience refers to the ability of the system to survive strong and unexpected disruptions and to recover quickly afterward [1]. This research is motivated by the acknowledgement that the commercial viability of marine power relies on the sector being able to explain how it can provide contributions beyond decarbonisation [2]. We build on an energy system modelling case study of the Isle of Wight [3], using the EnerSyM-RC energy system model. Wind data between 2012 – 2020 is analysed to identify and characterise periods of low wind resource. These data form the inputs to the EnerySyM-RC modelling. The model then applies a simple brute force optimisation method to investigate the most suitable mix of solar PV, offshore wind, tidal stream and energy storage that enhances system resilience on the Isle of Wight. Initial results show that the adoption of tidal stream energy compliments solar and wind generation by reducing reliance on reserve energy (e.g. imported gas) during high-stress periods. Reduced reliance on imported energy is also achieved because of the distinct generation pattern of tidal power (i.e. 4 periods of power generation, each separated by slack tide, every day), which enhances the utilisation of local energy storage. References [1] Jasiunas J, et al., 2021, Energy system resilience – A review, Renewable and Sustainable Energy Reviews, 150:111476 [2] Pacific Northwest National Laboratory, 2021, Grid Value Proposition of Marine Energy: A Preliminary Analysis, PNNL -31123, Technical report [3] Coles DS et al., 2023, Impacts of tidal stream power on energy system security: An Isle of Wight case study, Applied Energy, 334:120686

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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