G. Lavidas
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Wave energy arrays are essential for reducing the Levelised Cost of Energy, yet the performance of traditional mono-device arrays is often limited by destructive hydrodynamic interactions and directional sensitivity. This work focuses on ”mixed arrays,” wherein different types and geometries of wave energy converters operating in different degrees of freedom (point Absorber and a flap) are deployed within the same array to exploit complementary device dynamics, whilst reducing spatial requirements. Using a weakly non-linear frequency-domain model utilising the solver HAMS-MREL, a systematic comparison is performed across 3360 cases considering varying array sizes, spacings, wave directions, and control strategies (active and passive). Comparison of array performance is based on the well known q-factor and a new geometry dependent metric (M-factor). The results demonstrate that mixed arrays can outperform mono-device arrays by leveraging favourable hydrodynamic cross-coupling and radiated wave-field alignment. For a 10-device staggered configuration, mixed arrays achieved a peak q-factor of 1.6 and an M-factor of 2.25 under regular waves, showing a 175% increase in point absorber heave response under displacement constraints and 34% increase in flap excitation forces. Performance is sensitive to the spacing-to-wavelength ratio, mixed arrays exhibit superior directional robustness, and reduced efficiency collapse compared to mono-flap arrays. The findings suggest that mixed-device configurations can provide a robust alternative for optimising energy capture, reducing spatial requirements, offering new collaboration opportunities and contributing to the viability of wave energy arrays.
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Wave energy arrays are essential for reducing the Levelised Cost of Energy, yet the performance of traditional mono-device arrays is often limited by destructive hydrodynamic interactions and directional sensitivity. This work focuses on ”mixed arrays,” wherein different types and geometries of wave energy converters operating in different degrees of freedom (point Absorber and a flap) are deployed within the same array to exploit complementary device dynamics, whilst reducing spatial requirements. Using a weakly non-linear frequency-domain model utilising the solver HAMS-MREL, a systematic comparison is performed across 3360 cases considering varying array sizes, spacings, wave directions, and control strategies (active and passive). Comparison of array performance is based on the well known q-factor and a new geometry dependent metric (M-factor). The results demonstrate that mixed arrays can outperform mono-device arrays by leveraging favourable hydrodynamic cross-coupling and radiated wave-field alignment. For a 10-device staggered configuration, mixed arrays achieved a peak q-factor of 1.6 and an M-factor of 2.25 under regular waves, showing a 175% increase in point absorber heave response under displacement constraints and 34% increase in flap excitation forces. Performance is sensitive to the spacing-to-wavelength ratio, mixed arrays exhibit superior directional robustness, and reduced efficiency collapse compared to mono-flap arrays. The findings suggest that mixed-device configurations can provide a robust alternative for optimising energy capture, reducing spatial requirements, offering new collaboration opportunities and contributing to the viability of wave energy arrays.
Due to the complexity of the ocean environment and wave energy converter (WEC) system, it has been an effort-demanding work to assess either the power performance or fatigue loads of WECs. This work attempts to apply a data-driven approach to increase the efficiency of the collective prediction of the power and fatigue load of a point-absorber type WEC. Nonlinear time-domain modeling is first established to estimate the power and fatigue loads, which is considered the reference data in this work. To demonstrate the performance of the applied data-driven approach, two prevalent power take-off (PTO) mechanisms are implemented to represent different characteristics of WECs. A data-driven approach, active learning Kriging (AK), is adapted to predict power and fatigue loads collectively, and a new learning function is defined to select the enriched wave cases for the active learning process. Results show that the applied active learning approach can accurately and simultaneously predict power and fatigue loads in both PTO mechanisms. Compared to pure numerical simulation, the proposed method only requires 15 simulations of sea state, and the computational effort is reduced by more than 20 times. The maximum prediction error is less than 2%. The data-driven approach could be a powerful tool for WEC system optimization, considering both power performance and fatigue loads.
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Due to the complexity of the ocean environment and wave energy converter (WEC) system, it has been an effort-demanding work to assess either the power performance or fatigue loads of WECs. This work attempts to apply a data-driven approach to increase the efficiency of the collective prediction of the power and fatigue load of a point-absorber type WEC. Nonlinear time-domain modeling is first established to estimate the power and fatigue loads, which is considered the reference data in this work. To demonstrate the performance of the applied data-driven approach, two prevalent power take-off (PTO) mechanisms are implemented to represent different characteristics of WECs. A data-driven approach, active learning Kriging (AK), is adapted to predict power and fatigue loads collectively, and a new learning function is defined to select the enriched wave cases for the active learning process. Results show that the applied active learning approach can accurately and simultaneously predict power and fatigue loads in both PTO mechanisms. Compared to pure numerical simulation, the proposed method only requires 15 simulations of sea state, and the computational effort is reduced by more than 20 times. The maximum prediction error is less than 2%. The data-driven approach could be a powerful tool for WEC system optimization, considering both power performance and fatigue loads.
Marine resources such as wind and wave are expected to play an important role in decarbonising the UK’s energy network, as part of the global transition from fossil fuels to renewable energy. However, potential increases in global weather systems variability due to climate change cast doubt on the long-term sustainability of offshore renewable development and the ambitions of the UK government to rapidly expand current capacity. As such, growing interest in co-located wind–wave systems is being paid as a means of enhancing the climate resilience of the future energy network. This study investigates the impacts of climate change on wind and wave resources in the UK from 2015 to 2100, using available CMIP6 datasets and numerical wave modelling using SWAN. In doing so, an initial assessment of the potential for co-located infrastructure is undertaken to inform future research into its role in strengthening the climate resilience of ocean renewable generation. The results reveal gradual reductions in resource availability under a high emission scenario, with statistically significant annual trends detected across most of the study area. Reductions in average annual wind energy reach −16.0% in coastal areas of Northern Ireland towards the end of the century, while decreases in wave energy of more than 25% are projected in certain regions of the North Sea. These trends are primarily driven by seasonal reductions during summer months, with decreases in average wind power during these months as much as −29.0% and decreases in wave power of over −40%. In addition, increases in resource variability from the mid-century onwards suggest that climate change is likely to negatively affect the availability of the UK’s wind and wave energy resources in the long term.
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Marine resources such as wind and wave are expected to play an important role in decarbonising the UK’s energy network, as part of the global transition from fossil fuels to renewable energy. However, potential increases in global weather systems variability due to climate change cast doubt on the long-term sustainability of offshore renewable development and the ambitions of the UK government to rapidly expand current capacity. As such, growing interest in co-located wind–wave systems is being paid as a means of enhancing the climate resilience of the future energy network. This study investigates the impacts of climate change on wind and wave resources in the UK from 2015 to 2100, using available CMIP6 datasets and numerical wave modelling using SWAN. In doing so, an initial assessment of the potential for co-located infrastructure is undertaken to inform future research into its role in strengthening the climate resilience of ocean renewable generation. The results reveal gradual reductions in resource availability under a high emission scenario, with statistically significant annual trends detected across most of the study area. Reductions in average annual wind energy reach −16.0% in coastal areas of Northern Ireland towards the end of the century, while decreases in wave energy of more than 25% are projected in certain regions of the North Sea. These trends are primarily driven by seasonal reductions during summer months, with decreases in average wind power during these months as much as −29.0% and decreases in wave power of over −40%. In addition, increases in resource variability from the mid-century onwards suggest that climate change is likely to negatively affect the availability of the UK’s wind and wave energy resources in the long term.
Wave-to-Wire (W2W) modeling simulates the whole operation process of wave energy converters (WECs), which plays a pivotal role in the systematic design and optimization of WECs. Existing W2W models are predominantly constructed based on time-domain (TD) analysis to coherently incorporate relevant nonlinearities. However, TD models require a high computational cost, which hinders the design iterations of WECs. As a newly emerging alternative approach, spectral-domain (SD) modeling has demonstrated the applicability of describing the W2W process while efficiently covering nonlinear effects through statistical linearization. This study aims to develop an SD W2W modeling approach for WECs coupled with a gearbox and rotary generator. The application of the proposed model is exemplified in two case studies: (1) a point absorber with a rack-pinion system and a rotary generator; (2) a flap-type WEC with a revolving gearbox and a rotary generator. The simulation results obtained by the SD W2W model are compared against a higher-fidelity nonlinear TD W2W model to verify its accuracy across a variety of sea states. A good agreement between the two modeling approaches is observed, in which the maximum relative error is below 7 % with regard to the estimation of important system outputs. Meanwhile, the computational efficiency of the SD W2W model is thousands of times higher than the TD modeling approach.
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Wave-to-Wire (W2W) modeling simulates the whole operation process of wave energy converters (WECs), which plays a pivotal role in the systematic design and optimization of WECs. Existing W2W models are predominantly constructed based on time-domain (TD) analysis to coherently incorporate relevant nonlinearities. However, TD models require a high computational cost, which hinders the design iterations of WECs. As a newly emerging alternative approach, spectral-domain (SD) modeling has demonstrated the applicability of describing the W2W process while efficiently covering nonlinear effects through statistical linearization. This study aims to develop an SD W2W modeling approach for WECs coupled with a gearbox and rotary generator. The application of the proposed model is exemplified in two case studies: (1) a point absorber with a rack-pinion system and a rotary generator; (2) a flap-type WEC with a revolving gearbox and a rotary generator. The simulation results obtained by the SD W2W model are compared against a higher-fidelity nonlinear TD W2W model to verify its accuracy across a variety of sea states. A good agreement between the two modeling approaches is observed, in which the maximum relative error is below 7 % with regard to the estimation of important system outputs. Meanwhile, the computational efficiency of the SD W2W model is thousands of times higher than the TD modeling approach.
Recent studies have demonstrated the merits of spectral-domain (SD) modeling in efficiently addressing nonlinear dynamic behvavior of stand-alone wave energy converters (WECs). However, the potential of the SD modeling approach deserves further exploitation by examining its applicability in simulating the entire wave-to-wire (W2W) process of WEC arrays. This article proposed and verified a SD W2W model of WEC arrays. The WEC arrays are considered as five same-sized heaving cylindrical point absorbers, and they are all equipped with linear Permanent Magnet (PM) generators. The established SD W2W model is verified by being compared with results of a nonlinear time-domain-based W2W model across a variety of operation conditions. The computational efficiency of the two simulation approaches in modeling WEC arrays is also identified and compared. The results suggest that the SD W2W model is associated with a relative error of less than 11 % to the nonlinear time-domain reference, with regard to the estimates of significant statistical performance indicators, such as WEC velocity, absorbed and electrical power of individual power, and total electrical power production of the WEC arrays. At the same time, the SD W2W model presents a high computational efficiency, being around 2000 times faster than the time-domain W2W model of WEC arrays.
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Recent studies have demonstrated the merits of spectral-domain (SD) modeling in efficiently addressing nonlinear dynamic behvavior of stand-alone wave energy converters (WECs). However, the potential of the SD modeling approach deserves further exploitation by examining its applicability in simulating the entire wave-to-wire (W2W) process of WEC arrays. This article proposed and verified a SD W2W model of WEC arrays. The WEC arrays are considered as five same-sized heaving cylindrical point absorbers, and they are all equipped with linear Permanent Magnet (PM) generators. The established SD W2W model is verified by being compared with results of a nonlinear time-domain-based W2W model across a variety of operation conditions. The computational efficiency of the two simulation approaches in modeling WEC arrays is also identified and compared. The results suggest that the SD W2W model is associated with a relative error of less than 11 % to the nonlinear time-domain reference, with regard to the estimates of significant statistical performance indicators, such as WEC velocity, absorbed and electrical power of individual power, and total electrical power production of the WEC arrays. At the same time, the SD W2W model presents a high computational efficiency, being around 2000 times faster than the time-domain W2W model of WEC arrays.
Wave power for e-fuels and e-chemicals production
Technical feasibility, economic viability, and regional opportunities
Journal article
(2026)
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Rasul Satymov, Dmitrii Bogdanov, George Lavidas, Shona Pennock, Sarah Kluge, Benjamin Lehner, Christian Breyer
The global energy transition necessitates the defossilisation of the energy-intensive industry and hard-to-abate transport sectors, where direct electrification falls short due to limitations in energy density. Electricity-based fuels and chemicals (e-fuels and e-chemicals) emerge as a viable alternative, offering high energy density and compatibility with existing infrastructure. However, their production hinges on access to vast amounts of low-cost renewable electricity, a challenge for regions with limited land. This study explores wave power as an underexplored source for e-fuel production, focusing on regions with exceptional wave energy: New Zealand, Chile, and Ireland. Using energyHub-LUT, a newly developed optimisation model, the research evaluates the techno-economics of wave power, alongside solar photovoltaics and wind power, for producing e-fuels and e-chemicals. The results show that wave power supplies more stable power for e-fuel production compared to onshore wind power and solar photovoltaics, cutting the need for batteries by 25-100%, depending on location. Chile produces the lowest cost e-fuels when wave power is integrated alongside solar photovoltaics and onshore wind power, thanks to over 7000 full load hours, but its higher capital expenditures render it less competitive than onshore renewable energy. The study concludes that wave power's economic viability is limited even in regions with very high full load hours but also highlights its potential as an alternative where land scarcity hinders large-scale renewable energy projects or in cases of near baseload direct electricity need.
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The global energy transition necessitates the defossilisation of the energy-intensive industry and hard-to-abate transport sectors, where direct electrification falls short due to limitations in energy density. Electricity-based fuels and chemicals (e-fuels and e-chemicals) emerge as a viable alternative, offering high energy density and compatibility with existing infrastructure. However, their production hinges on access to vast amounts of low-cost renewable electricity, a challenge for regions with limited land. This study explores wave power as an underexplored source for e-fuel production, focusing on regions with exceptional wave energy: New Zealand, Chile, and Ireland. Using energyHub-LUT, a newly developed optimisation model, the research evaluates the techno-economics of wave power, alongside solar photovoltaics and wind power, for producing e-fuels and e-chemicals. The results show that wave power supplies more stable power for e-fuel production compared to onshore wind power and solar photovoltaics, cutting the need for batteries by 25-100%, depending on location. Chile produces the lowest cost e-fuels when wave power is integrated alongside solar photovoltaics and onshore wind power, thanks to over 7000 full load hours, but its higher capital expenditures render it less competitive than onshore renewable energy. The study concludes that wave power's economic viability is limited even in regions with very high full load hours but also highlights its potential as an alternative where land scarcity hinders large-scale renewable energy projects or in cases of near baseload direct electricity need.
Wave energy arrays are essential for reducing the Levelised Cost of Energy, yet the performance of traditional mono-device arrays is often limited by destructive hydrodynamic interactions and directional sensitivity. This work focuses on ”mixed arrays,” wherein different types and geometries of wave energy converters operating in different degrees of freedom (point Absorber and a flap) are deployed within the same array to exploit complementary device dynamics, whilst reducing spatial requirements. Using a weakly non-linear frequency-domain model utilising the solver HAMS-MREL, a systematic comparison is performed across 3360 cases considering varying array sizes, spacings, wave directions, and control strategies (active and passive). Comparison of array performance is based on the well known q-factor and a new geometry dependent metric (M-factor). The results demonstrate that mixed arrays can outperform mono-device arrays by leveraging favourable hydrodynamic cross-coupling and radiated wave-field alignment. For a 10-device staggered configuration, mixed arrays achieved a peak q-factor of 1.6 and an M-factor of 2.25 under regular waves, showing a 175% increase in point absorber heave response under displacement constraints and 34% increase in flap excitation forces. Performance is sensitive to the spacing-to-wavelength ratio, mixed arrays exhibit superior directional robustness, and reduced efficiency collapse compared to mono-flap arrays. The findings suggest that mixed-device configurations can provide a robust alternative for optimising energy capture, reducing spatial requirements, offering new collaboration opportunities and contributing to the viability of wave energy arrays.
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Wave energy arrays are essential for reducing the Levelised Cost of Energy, yet the performance of traditional mono-device arrays is often limited by destructive hydrodynamic interactions and directional sensitivity. This work focuses on ”mixed arrays,” wherein different types and geometries of wave energy converters operating in different degrees of freedom (point Absorber and a flap) are deployed within the same array to exploit complementary device dynamics, whilst reducing spatial requirements. Using a weakly non-linear frequency-domain model utilising the solver HAMS-MREL, a systematic comparison is performed across 3360 cases considering varying array sizes, spacings, wave directions, and control strategies (active and passive). Comparison of array performance is based on the well known q-factor and a new geometry dependent metric (M-factor). The results demonstrate that mixed arrays can outperform mono-device arrays by leveraging favourable hydrodynamic cross-coupling and radiated wave-field alignment. For a 10-device staggered configuration, mixed arrays achieved a peak q-factor of 1.6 and an M-factor of 2.25 under regular waves, showing a 175% increase in point absorber heave response under displacement constraints and 34% increase in flap excitation forces. Performance is sensitive to the spacing-to-wavelength ratio, mixed arrays exhibit superior directional robustness, and reduced efficiency collapse compared to mono-flap arrays. The findings suggest that mixed-device configurations can provide a robust alternative for optimising energy capture, reducing spatial requirements, offering new collaboration opportunities and contributing to the viability of wave energy arrays.
The proper design of wave energy converters (WECs) is crucial for ensuring robustness in harsh wave climates without incurring the additional expense of unnecessary overdesign. The power take-off (PTO) mechanism, serving as a vital link between the moving body and the electric generator, is a key component in the design load analysis of WECs. However, the setting of PTO system parameters significantly impacts the dynamic behavior of the entire WEC system, leading to alterations in estimated loads. This work is dedicated to studying the influence of PTO control strategies on the identification of extreme loads of a heaving point absorber WEC. A nonlinear time-domain model is established to estimate the dynamic responses and loads of the WEC. Both PTO loads and end-stop loads under extreme conditions are examined, considering the wave climate of a realistic sea site. The results suggest that the PTO setting strategies significantly impact the extreme load exerted on both the PTO system and the end-stop system. Varying the PTO damping within a certain range could lead to a difference of 57% and 63% in short-term extreme loads for the PTO system and the end-stop system, respectively. Furthermore, the impacts of the PTO control strategy appear to be specific to each WEC component. The PTO parameters selected for reducing the extreme PTO loads might increase the extreme end-stop loads. A holistic examination is therefore recommended for estimating the extreme loads of WECs.
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The proper design of wave energy converters (WECs) is crucial for ensuring robustness in harsh wave climates without incurring the additional expense of unnecessary overdesign. The power take-off (PTO) mechanism, serving as a vital link between the moving body and the electric generator, is a key component in the design load analysis of WECs. However, the setting of PTO system parameters significantly impacts the dynamic behavior of the entire WEC system, leading to alterations in estimated loads. This work is dedicated to studying the influence of PTO control strategies on the identification of extreme loads of a heaving point absorber WEC. A nonlinear time-domain model is established to estimate the dynamic responses and loads of the WEC. Both PTO loads and end-stop loads under extreme conditions are examined, considering the wave climate of a realistic sea site. The results suggest that the PTO setting strategies significantly impact the extreme load exerted on both the PTO system and the end-stop system. Varying the PTO damping within a certain range could lead to a difference of 57% and 63% in short-term extreme loads for the PTO system and the end-stop system, respectively. Furthermore, the impacts of the PTO control strategy appear to be specific to each WEC component. The PTO parameters selected for reducing the extreme PTO loads might increase the extreme end-stop loads. A holistic examination is therefore recommended for estimating the extreme loads of WECs.
Different numerical modeling methods have been developed and applied to evaluate a variety of performance indicators of wave energy converters (WECs), including the power performance, structural loads, levelized cost of energy, etc. Based on the modeling fidelity, the commonly used numerical modeling approaches can be classified as linear modeling, weakly nonlinear modeling and fully nonlinear modeling approaches. Each method differs in accuracy and computational efficiency, making them suitable for different stages of WEC design. However, the selection of modeling approach could significantly impact evaluation outcomes. For instance, simplified linear models may underestimate structural loads or overestimate energy production in some operational conditions, potentially leading to less cost-effective designs. Given the widespread utilization of these models, it is essential to understand the uncertainties brought by them in performance evaluations. This work is dedicated to benchmarking different linear-potential-flow-based numerical models for evaluating the systematic performance of WECs. Three representative numerical modeling approaches are considered in this work, including linear frequency-domain modeling, statistically linearized spectral-domain modeling and Cummins equation-based nonlinear time-domain modeling. A generic point absorber WEC is considered as the research reference in this work, and different sea sites are taken into account. The numerical models are utilized to predict critical performance indicators, including power performance, the annual energy production, the capacity factor, the levelized cost of energy and the PTO fatigue loads. By comparing the results, this work identifies the uncertainties associated with different modeling approaches in evaluating WEC performance.
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Different numerical modeling methods have been developed and applied to evaluate a variety of performance indicators of wave energy converters (WECs), including the power performance, structural loads, levelized cost of energy, etc. Based on the modeling fidelity, the commonly used numerical modeling approaches can be classified as linear modeling, weakly nonlinear modeling and fully nonlinear modeling approaches. Each method differs in accuracy and computational efficiency, making them suitable for different stages of WEC design. However, the selection of modeling approach could significantly impact evaluation outcomes. For instance, simplified linear models may underestimate structural loads or overestimate energy production in some operational conditions, potentially leading to less cost-effective designs. Given the widespread utilization of these models, it is essential to understand the uncertainties brought by them in performance evaluations. This work is dedicated to benchmarking different linear-potential-flow-based numerical models for evaluating the systematic performance of WECs. Three representative numerical modeling approaches are considered in this work, including linear frequency-domain modeling, statistically linearized spectral-domain modeling and Cummins equation-based nonlinear time-domain modeling. A generic point absorber WEC is considered as the research reference in this work, and different sea sites are taken into account. The numerical models are utilized to predict critical performance indicators, including power performance, the annual energy production, the capacity factor, the levelized cost of energy and the PTO fatigue loads. By comparing the results, this work identifies the uncertainties associated with different modeling approaches in evaluating WEC performance.
Marine renewables in Energy Systems
Impacts of climate data, generators, energy policies, opportunities, and untapped potential for 100% decarbonised systems
Journal article
(2025)
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George Lavidas, Lefteris Mezilis, Matías Alday G., Harish Baki, Jian Tan, Avni Jain, Tabea Engelfried, Vaibhav Raghavan
The Energy Transition requires meticulous planning, taking into consideration economic, technical, social, and resource constraints. In Europe ambitious targets have been set for system electrification, however, integrating the potential of marine renewables have not been thoroughly investigated. This study extends the framework of PyPSA-Eur into PyPSA-Eur-MREL that for the first time incorporates all marine renewables, using high resolution datasets, that uncover the potential of marine renewables. Marine renewables are modelled in terms of power estimations, deployment strategies and revised packing density, and expected benefits for 2030, and 2050 across all European Countries are quantified. Higher spatio-temporal data have an immediate impact in estimates, and reduction of energy storage by 73%. Wind energy has a reduced installation capacity by 50%, but the higher fidelity of resource matches production to demand and reduces curtailments up to 60%. System costs with high resolution data are 40% reduced to 160 billion € for a 2030 100% renewable reliant system. The benefits of having more marine renewables are not limited to cost and more efficient demand matching, reduced energy storage, but it also with the area required to decarbonise the system. The results are encouraging and outline the importance and further need for marine renewable energies.
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The Energy Transition requires meticulous planning, taking into consideration economic, technical, social, and resource constraints. In Europe ambitious targets have been set for system electrification, however, integrating the potential of marine renewables have not been thoroughly investigated. This study extends the framework of PyPSA-Eur into PyPSA-Eur-MREL that for the first time incorporates all marine renewables, using high resolution datasets, that uncover the potential of marine renewables. Marine renewables are modelled in terms of power estimations, deployment strategies and revised packing density, and expected benefits for 2030, and 2050 across all European Countries are quantified. Higher spatio-temporal data have an immediate impact in estimates, and reduction of energy storage by 73%. Wind energy has a reduced installation capacity by 50%, but the higher fidelity of resource matches production to demand and reduces curtailments up to 60%. System costs with high resolution data are 40% reduced to 160 billion € for a 2030 100% renewable reliant system. The benefits of having more marine renewables are not limited to cost and more efficient demand matching, reduced energy storage, but it also with the area required to decarbonise the system. The results are encouraging and outline the importance and further need for marine renewable energies.
As the necessity for the decarbonisation of the global electricity market increases, a range of renewable energy technologies will be implemented, one of which is wave energy. A key step in this process is the thorough quantification of both the power resource at locations of interest, and the impacts of these devices on the natural environment. The present work streamlines these 2 processes into one methodology by investigating the long-term impacts of an array of 20 WECs on the nearshore Dutch wave climate, while also calculating the potential power resource at the site considering intra-array wake effects. Simulations of 10 year duration were conducted in the baseline scenario (no farm present) and with 2 array configurations, using the spectral wave model SWAN on an unstructured mesh. It was demonstrated that the power production of the farm during this period, when wake effects are considered, is calculated to be up to 1.8% less than traditional methods. The presence of the farm is shown to reduce significant wave height and wave power in its lee, with the effects being largely attenuated at the coast. It was shown that the magnitude of the change is dependent on both the period and height of the waves at the farm, and notably the magnitude of the reduction does not increase consistently with the wave height, contradicting the sentiment that wave farms are effective protection mechanisms against damaging high-energy conditions. Furthermore, the present work suggests that changes to the nearshore breaker index may impact longshore currents that are essential for nutrient and sediment transport, the effect of which on the ecosystem is not yet well quantified.
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As the necessity for the decarbonisation of the global electricity market increases, a range of renewable energy technologies will be implemented, one of which is wave energy. A key step in this process is the thorough quantification of both the power resource at locations of interest, and the impacts of these devices on the natural environment. The present work streamlines these 2 processes into one methodology by investigating the long-term impacts of an array of 20 WECs on the nearshore Dutch wave climate, while also calculating the potential power resource at the site considering intra-array wake effects. Simulations of 10 year duration were conducted in the baseline scenario (no farm present) and with 2 array configurations, using the spectral wave model SWAN on an unstructured mesh. It was demonstrated that the power production of the farm during this period, when wake effects are considered, is calculated to be up to 1.8% less than traditional methods. The presence of the farm is shown to reduce significant wave height and wave power in its lee, with the effects being largely attenuated at the coast. It was shown that the magnitude of the change is dependent on both the period and height of the waves at the farm, and notably the magnitude of the reduction does not increase consistently with the wave height, contradicting the sentiment that wave farms are effective protection mechanisms against damaging high-energy conditions. Furthermore, the present work suggests that changes to the nearshore breaker index may impact longshore currents that are essential for nutrient and sediment transport, the effect of which on the ecosystem is not yet well quantified.
Numerical modelling plays a pivotal role in the design and optimization of wave energy converters. Spectral-domain (SD) modelling has recently received significant research interest as a newly emerging numerical tool. SD modelling is commonly characterized as an extension of frequency-domain (FD) modelling but can incorporate nonlinearities. Thereby, it combines high computational efficiency and adequate accuracy. Previous studies have demonstrated the applicability of SD modelling to a variety of nonlinear hydrostatic/hydrodynamic effects, including viscous drag force, nonlinear hydrostatic force, nonlinear mooring force, etc. However, there also exist influential nonlinear effects in the power generation phase in wave energy conversion. For instance, previous studies have demonstrated that the current limit of the electrical generator could impact the PTO force and the dynamics of the whole system. Therefore, it is necessary to further develop the SD modelling to cover the entire wave-to-wire process in WECs.
In this paper, a SD model is derived to simulate the wave-to-wire process of a point absorber WEC. A mechanical PTO system coupled with a rotary permanent-magnet generator is considered for the WEC. Representative nonlinear effects of the wave-to-wire process are incorporated, including viscous drag force, nonlinear PTO force, and the current limit of the generator. A nonlinear time-domain (TD) wave-to-wire model is established correspondingly to serve as the accuracy reference because it is inherently associated with higher modelling fidelity. The dynamic response and the power performance of the proposed SD model are verified against those of the nonlinear TD wave-to-wire model. Additionally, the computational efficiency of the proposed SD model and the TD model is identified and compared. ...
In this paper, a SD model is derived to simulate the wave-to-wire process of a point absorber WEC. A mechanical PTO system coupled with a rotary permanent-magnet generator is considered for the WEC. Representative nonlinear effects of the wave-to-wire process are incorporated, including viscous drag force, nonlinear PTO force, and the current limit of the generator. A nonlinear time-domain (TD) wave-to-wire model is established correspondingly to serve as the accuracy reference because it is inherently associated with higher modelling fidelity. The dynamic response and the power performance of the proposed SD model are verified against those of the nonlinear TD wave-to-wire model. Additionally, the computational efficiency of the proposed SD model and the TD model is identified and compared. ...
Numerical modelling plays a pivotal role in the design and optimization of wave energy converters. Spectral-domain (SD) modelling has recently received significant research interest as a newly emerging numerical tool. SD modelling is commonly characterized as an extension of frequency-domain (FD) modelling but can incorporate nonlinearities. Thereby, it combines high computational efficiency and adequate accuracy. Previous studies have demonstrated the applicability of SD modelling to a variety of nonlinear hydrostatic/hydrodynamic effects, including viscous drag force, nonlinear hydrostatic force, nonlinear mooring force, etc. However, there also exist influential nonlinear effects in the power generation phase in wave energy conversion. For instance, previous studies have demonstrated that the current limit of the electrical generator could impact the PTO force and the dynamics of the whole system. Therefore, it is necessary to further develop the SD modelling to cover the entire wave-to-wire process in WECs.
In this paper, a SD model is derived to simulate the wave-to-wire process of a point absorber WEC. A mechanical PTO system coupled with a rotary permanent-magnet generator is considered for the WEC. Representative nonlinear effects of the wave-to-wire process are incorporated, including viscous drag force, nonlinear PTO force, and the current limit of the generator. A nonlinear time-domain (TD) wave-to-wire model is established correspondingly to serve as the accuracy reference because it is inherently associated with higher modelling fidelity. The dynamic response and the power performance of the proposed SD model are verified against those of the nonlinear TD wave-to-wire model. Additionally, the computational efficiency of the proposed SD model and the TD model is identified and compared.
In this paper, a SD model is derived to simulate the wave-to-wire process of a point absorber WEC. A mechanical PTO system coupled with a rotary permanent-magnet generator is considered for the WEC. Representative nonlinear effects of the wave-to-wire process are incorporated, including viscous drag force, nonlinear PTO force, and the current limit of the generator. A nonlinear time-domain (TD) wave-to-wire model is established correspondingly to serve as the accuracy reference because it is inherently associated with higher modelling fidelity. The dynamic response and the power performance of the proposed SD model are verified against those of the nonlinear TD wave-to-wire model. Additionally, the computational efficiency of the proposed SD model and the TD model is identified and compared.
The deployment of marine renewables (MRE) is important for transitioning to a low-carbon energy system. However, their performance is highly dependent on the deployment location, making the selection of feasible sites critical for large-scale implementation. To contribute meaningfully to Europe’s renewable energy strategy and support a carbon-neutral energy system by 2050, the environmental performance of MREs must be taken into account in site selection, beyond the typical economic and technical aspects. Therefore, this study presents a geospatial analysis of the climate change mitigation potential of two wave energy converters, floating offshore photovoltaics, and floating wind turbines in northern European coastal waters. By combining a detailed life cycle assessment model of the four MREs with spatial data, the distribution of their life cycle global warming impact and carbon payback periods is assessed across multiple regions. The results show significantly varying impact levels of the different MREs, with carbon-neutral deployment not guaranteed at every location. Wave energy converters only partially reach carbon neutrality, while floating photovoltaics fail to do so across the entire study area. Floating wind turbines can be considered carbon-neutral nearly across their entire theoretical application area. The findings highlight the importance of taking into account site-specific environmental performance of MREs in order to ensure a positive contribution to climate change mitigation. By providing spatially explicit maps of MREs’ global warming impacts and carbon payback periods, this study enables as the first of its kind the inclusion of climate change mitigation considerations in the site selection process for MREs.
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The deployment of marine renewables (MRE) is important for transitioning to a low-carbon energy system. However, their performance is highly dependent on the deployment location, making the selection of feasible sites critical for large-scale implementation. To contribute meaningfully to Europe’s renewable energy strategy and support a carbon-neutral energy system by 2050, the environmental performance of MREs must be taken into account in site selection, beyond the typical economic and technical aspects. Therefore, this study presents a geospatial analysis of the climate change mitigation potential of two wave energy converters, floating offshore photovoltaics, and floating wind turbines in northern European coastal waters. By combining a detailed life cycle assessment model of the four MREs with spatial data, the distribution of their life cycle global warming impact and carbon payback periods is assessed across multiple regions. The results show significantly varying impact levels of the different MREs, with carbon-neutral deployment not guaranteed at every location. Wave energy converters only partially reach carbon neutrality, while floating photovoltaics fail to do so across the entire study area. Floating wind turbines can be considered carbon-neutral nearly across their entire theoretical application area. The findings highlight the importance of taking into account site-specific environmental performance of MREs in order to ensure a positive contribution to climate change mitigation. By providing spatially explicit maps of MREs’ global warming impacts and carbon payback periods, this study enables as the first of its kind the inclusion of climate change mitigation considerations in the site selection process for MREs.
This study presents a first long term (30 years) assessment to quantify the effects of both, the wave spectrum representation, and occurrences of multi-modal sea states, on power production estimations from a point-absorber Wave Energy Converter (WEC). Analysis in 3 different offshore locations (Portugal, Ireland and The Netherlands) is included to ensure robustness of results. In general, traditional methods based on the use of the JONSWAP spectrum, with an adequate gamma shape value, can lead to mean overestimation in yearly power production >12% when compared to reference hindcast spectral data. This can be partially reduced when capping is applied to power production, but still can be close to 10%. An alternative method is proposed to modulate the JONSWAP spectrum at each time step which helps to reduce differences, but leads to slight yearly underestimations (−2.5 to −5% in average). Although in all analyzed sites the occurrences of multi-modal spectra is >30%, contribution to errors due to misrepresentation of these sea states are estimated to be of about 2.5%. These findings provide valuable insights on the uncertainties introduced in power production estimations, related to wave conditions characterization, that can have important economic impact when planning for large scale deployments.
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This study presents a first long term (30 years) assessment to quantify the effects of both, the wave spectrum representation, and occurrences of multi-modal sea states, on power production estimations from a point-absorber Wave Energy Converter (WEC). Analysis in 3 different offshore locations (Portugal, Ireland and The Netherlands) is included to ensure robustness of results. In general, traditional methods based on the use of the JONSWAP spectrum, with an adequate gamma shape value, can lead to mean overestimation in yearly power production >12% when compared to reference hindcast spectral data. This can be partially reduced when capping is applied to power production, but still can be close to 10%. An alternative method is proposed to modulate the JONSWAP spectrum at each time step which helps to reduce differences, but leads to slight yearly underestimations (−2.5 to −5% in average). Although in all analyzed sites the occurrences of multi-modal spectra is >30%, contribution to errors due to misrepresentation of these sea states are estimated to be of about 2.5%. These findings provide valuable insights on the uncertainties introduced in power production estimations, related to wave conditions characterization, that can have important economic impact when planning for large scale deployments.
Harnessing wave energy from the oceans using wave energy converters (WECs) offers a huge opportunity to diversify Europe’s future renewable energy system. Although the energy conversion of this pre-commercial technology is not directly linked to greenhouse gas emissions, environmental sustainability over the full life cycle needs to be ensured for a future-proof large-scale application of WECs. Therefore, we present a cradle-to-grave full life cycle assessment (LCA) study for a generic point absorber WEC based on a fully transparent and adaptable life cycle inventory. Within the study we assess the environmental impacts of a single point absorber device, the influence of different hull materials, hotspots in the impacts of WEC components, and variations induced by different deployment locations. For a WEC deployed in the North Sea, we found a global warming impact of 300-325gCO2eq./kWh with periphery and 52-77gCO2eq./kWh without periphery, depending on the hull material. Using an alternative fibre-reinforced concrete material for the hull can reduce the impact across all categories by between 10% (marine eutrophication) and 78% (human toxicity, carcinogenic). In addition to the WEC itself we found that the electrical cable and vessel operations, particularly for maintenance, are significant contributors. These two elements will also be relevant to other marine renewables such as offshore wind and floating solar. Overall, this study shows potential for improving environmental impacts from WECs and identifies possible levers to achieve such a reduction.
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Harnessing wave energy from the oceans using wave energy converters (WECs) offers a huge opportunity to diversify Europe’s future renewable energy system. Although the energy conversion of this pre-commercial technology is not directly linked to greenhouse gas emissions, environmental sustainability over the full life cycle needs to be ensured for a future-proof large-scale application of WECs. Therefore, we present a cradle-to-grave full life cycle assessment (LCA) study for a generic point absorber WEC based on a fully transparent and adaptable life cycle inventory. Within the study we assess the environmental impacts of a single point absorber device, the influence of different hull materials, hotspots in the impacts of WEC components, and variations induced by different deployment locations. For a WEC deployed in the North Sea, we found a global warming impact of 300-325gCO2eq./kWh with periphery and 52-77gCO2eq./kWh without periphery, depending on the hull material. Using an alternative fibre-reinforced concrete material for the hull can reduce the impact across all categories by between 10% (marine eutrophication) and 78% (human toxicity, carcinogenic). In addition to the WEC itself we found that the electrical cable and vessel operations, particularly for maintenance, are significant contributors. These two elements will also be relevant to other marine renewables such as offshore wind and floating solar. Overall, this study shows potential for improving environmental impacts from WECs and identifies possible levers to achieve such a reduction.
To accelerate the energy transition, offshore renewable energy is increasingly moving toward array deployment. This shift demands accurate, reliable analysis of hydrodynamics and array interactions at low computational cost. Frequency-domain tools, especially those based on the Boundary Integral Equation Method (BIEM), have thus become widely adopted in the renewables community. Hydrodynamic Analysis of Marine Structures-Marine Renewable Energies Lab (HAMS-MREL) is a recently developed open-source multi-body BIEM solver that computes diffraction and radiation problems, yielding hydrodynamic coefficients and excitation forces on structures. The solver has been validated across a range of geometries using experiments, semi-analytical solutions, and cross-model comparisons, demonstrating high accuracy. This study extends HAMS-MREL with several new features—including wave field calculations (free-surface elevation and pressure), global symmetry, irregular frequency suppression, and generalized (dry) modes—all of which have been validated for accuracy and computational efficiency. OpenMP parallelization has been integrated into each feature, delivering significant computational speed-ups ranging from 13.5 to 47.2.
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To accelerate the energy transition, offshore renewable energy is increasingly moving toward array deployment. This shift demands accurate, reliable analysis of hydrodynamics and array interactions at low computational cost. Frequency-domain tools, especially those based on the Boundary Integral Equation Method (BIEM), have thus become widely adopted in the renewables community. Hydrodynamic Analysis of Marine Structures-Marine Renewable Energies Lab (HAMS-MREL) is a recently developed open-source multi-body BIEM solver that computes diffraction and radiation problems, yielding hydrodynamic coefficients and excitation forces on structures. The solver has been validated across a range of geometries using experiments, semi-analytical solutions, and cross-model comparisons, demonstrating high accuracy. This study extends HAMS-MREL with several new features—including wave field calculations (free-surface elevation and pressure), global symmetry, irregular frequency suppression, and generalized (dry) modes—all of which have been validated for accuracy and computational efficiency. OpenMP parallelization has been integrated into each feature, delivering significant computational speed-ups ranging from 13.5 to 47.2.
The increasing global demand for wind power underscores the importance of understanding and characterizing extreme ramp events, which are significant fluctuations in wind power generation over short periods that pose challenges for grid integration. This study focuses on modeling frontal low-level jets (FLLJs) and associated extreme ramp-down events, particularly their impact on wind power production at Belgium offshore wind farms. Using the Weather Research and Forecasting (WRF) model, we analyzed five cases of extreme wind power ramp-down events, including in-depth analysis of two cases and generalization of three additional cases. We assessed the sensitivity of various model configurations, including initial and boundary condition (IC/BC) datasets (ERA5 and CERRA), the activation of Fitch wind farm parameterization (WFP), planetary boundary layer (PBL) schemes, and single- versus nested-domain configuration. Our findings indicate that CERRA IC/BCs provide a superior representation of atmospheric flow compared to ERA5, resulting in more accurate predictions of ramp timing, intensity, and FLLJ characteristics. The WFP significantly impacts wind power output by modeling turbine interactions and wake effects, leading to slightly lower wind speeds. The scale-aware Shin and Hong PBL scheme yielded a stronger FLLJ core at higher altitudes with a more pronounced jet nose, although wind speeds below 200 m were lower compared to the Mellor–Yamada–Nakanishi–Niino 2.5 scheme. Single-domain configuration proved more effective in simulating wind power ramps but had higher core heights and higher wind speeds below 200 m, resulting in a diffused jet profile. Our analysis highlights that reliable simulation of extreme ramps associated with FLLJs using a single-domain configuration could reduce computational costs. Further, the FLLJs and associated extreme ramps can be predicted 1 d in advance, offering substantial benefits for operational efficiency in wind energy management.
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The increasing global demand for wind power underscores the importance of understanding and characterizing extreme ramp events, which are significant fluctuations in wind power generation over short periods that pose challenges for grid integration. This study focuses on modeling frontal low-level jets (FLLJs) and associated extreme ramp-down events, particularly their impact on wind power production at Belgium offshore wind farms. Using the Weather Research and Forecasting (WRF) model, we analyzed five cases of extreme wind power ramp-down events, including in-depth analysis of two cases and generalization of three additional cases. We assessed the sensitivity of various model configurations, including initial and boundary condition (IC/BC) datasets (ERA5 and CERRA), the activation of Fitch wind farm parameterization (WFP), planetary boundary layer (PBL) schemes, and single- versus nested-domain configuration. Our findings indicate that CERRA IC/BCs provide a superior representation of atmospheric flow compared to ERA5, resulting in more accurate predictions of ramp timing, intensity, and FLLJ characteristics. The WFP significantly impacts wind power output by modeling turbine interactions and wake effects, leading to slightly lower wind speeds. The scale-aware Shin and Hong PBL scheme yielded a stronger FLLJ core at higher altitudes with a more pronounced jet nose, although wind speeds below 200 m were lower compared to the Mellor–Yamada–Nakanishi–Niino 2.5 scheme. Single-domain configuration proved more effective in simulating wind power ramps but had higher core heights and higher wind speeds below 200 m, resulting in a diffused jet profile. Our analysis highlights that reliable simulation of extreme ramps associated with FLLJs using a single-domain configuration could reduce computational costs. Further, the FLLJs and associated extreme ramps can be predicted 1 d in advance, offering substantial benefits for operational efficiency in wind energy management.
Journal article
(2025)
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Rasul Satymov, Dmitrii Bogdanov, George Lavidas, Shona Pennock, Sarah Kluge, Benjamin Lehner, Christian Breyer
The best wave energy resources are typically found far from land, especially in the far southern latitudes. However, these optimal locations often lie outside any single nation's exclusive economic zone (EEZ) and are located in deep ocean waters, though a few places stand out, namely Kerguelen Islands, the southern coast of Chile and the southern tip of New Zealand. The Kerguelen Islands are situated in a prime wave energy location, with a potential capacity factor exceeding 90% when using best of breed point-absorber wave energy converters (WECs). This could result in a levelised cost of electricity of 31.4 €/MWh by 2050. An earlier study showed that the Kerguelen Islands could support up to 7 GW of installable wave power capacity, utilising only 15% of the EEZ.
To evaluate the feasibility of establishing an energy hub on Kerguelen Islands, a scenario was developed using the EnergyPLAN modelling software. The scenario involves producing e-fuels and e-chemicals, which will be essential for sectors like marine and aviation transportation and chemicals as the world transitions to a defossilised economy. This analysis assumes that the islands could supply fuel for East Asia, particularly Japan, South Korea, and Taiwan. By 2050, the 7 GW wave power system could meet 3% of the demand for e-fuels and e-chemicals in these countries, producing 3.5 TWhth,LHV of e-kerosene, 2.6 TWhth,LHV of e-diesel, 19 TWhth,LHV of e-methanol, 2.5 TWhth,LHV of e-LNG, and 4.9 TWhth,LHV of e-ammonia. The cost projections for 2050 suggest that e-fuels and e-chemicals produced from Kerguelen Islands could be highly competitive, with projected costs of 95.0 €/MWh for e-kerosene and e-diesel, 78.7 €/MWh for e-methanol, 64.5 €/MWh for e-LNG, and 68.4 €/MWh for e-ammonia.
In addition to wave power, the system would incorporate 2 GWhcap of battery storage and 50 GWh of underground rock cavern hydrogen storage, further enhancing the energy hub's capacity and flexibility. These costs, assumed for 2050, are projected to be competitive compared to leading global sites, such as the Atacama Desert, which has excellent solar PV resources. For comparison, the Atacama Desert’s e-fuels production cost is estimated to range from 70-75 €/MWh, e-methanol is between 49-57 €/MWh and e-ammonia at 53 €/MWh.
However, the costs mentioned above do not include shipping costs. Shipping costs for ammonia for 10,000 km to East Asia could add up to 8 €/MWh, while shipping costs for methanol could add up to 4 €/MWh. For the Kerguelen Islands an attractive business model could be established to diversify the global e-fuels and e-chemicals production that may largely shift towards solar energy. This creates a promising opportunity for investment in a gigawatt-scale energy hub for e-fuels and e-chemicals on Kerguelen Islands, including the necessary infrastructure for shipping and workforce to maintain such a system. ...
To evaluate the feasibility of establishing an energy hub on Kerguelen Islands, a scenario was developed using the EnergyPLAN modelling software. The scenario involves producing e-fuels and e-chemicals, which will be essential for sectors like marine and aviation transportation and chemicals as the world transitions to a defossilised economy. This analysis assumes that the islands could supply fuel for East Asia, particularly Japan, South Korea, and Taiwan. By 2050, the 7 GW wave power system could meet 3% of the demand for e-fuels and e-chemicals in these countries, producing 3.5 TWhth,LHV of e-kerosene, 2.6 TWhth,LHV of e-diesel, 19 TWhth,LHV of e-methanol, 2.5 TWhth,LHV of e-LNG, and 4.9 TWhth,LHV of e-ammonia. The cost projections for 2050 suggest that e-fuels and e-chemicals produced from Kerguelen Islands could be highly competitive, with projected costs of 95.0 €/MWh for e-kerosene and e-diesel, 78.7 €/MWh for e-methanol, 64.5 €/MWh for e-LNG, and 68.4 €/MWh for e-ammonia.
In addition to wave power, the system would incorporate 2 GWhcap of battery storage and 50 GWh of underground rock cavern hydrogen storage, further enhancing the energy hub's capacity and flexibility. These costs, assumed for 2050, are projected to be competitive compared to leading global sites, such as the Atacama Desert, which has excellent solar PV resources. For comparison, the Atacama Desert’s e-fuels production cost is estimated to range from 70-75 €/MWh, e-methanol is between 49-57 €/MWh and e-ammonia at 53 €/MWh.
However, the costs mentioned above do not include shipping costs. Shipping costs for ammonia for 10,000 km to East Asia could add up to 8 €/MWh, while shipping costs for methanol could add up to 4 €/MWh. For the Kerguelen Islands an attractive business model could be established to diversify the global e-fuels and e-chemicals production that may largely shift towards solar energy. This creates a promising opportunity for investment in a gigawatt-scale energy hub for e-fuels and e-chemicals on Kerguelen Islands, including the necessary infrastructure for shipping and workforce to maintain such a system. ...
The best wave energy resources are typically found far from land, especially in the far southern latitudes. However, these optimal locations often lie outside any single nation's exclusive economic zone (EEZ) and are located in deep ocean waters, though a few places stand out, namely Kerguelen Islands, the southern coast of Chile and the southern tip of New Zealand. The Kerguelen Islands are situated in a prime wave energy location, with a potential capacity factor exceeding 90% when using best of breed point-absorber wave energy converters (WECs). This could result in a levelised cost of electricity of 31.4 €/MWh by 2050. An earlier study showed that the Kerguelen Islands could support up to 7 GW of installable wave power capacity, utilising only 15% of the EEZ.
To evaluate the feasibility of establishing an energy hub on Kerguelen Islands, a scenario was developed using the EnergyPLAN modelling software. The scenario involves producing e-fuels and e-chemicals, which will be essential for sectors like marine and aviation transportation and chemicals as the world transitions to a defossilised economy. This analysis assumes that the islands could supply fuel for East Asia, particularly Japan, South Korea, and Taiwan. By 2050, the 7 GW wave power system could meet 3% of the demand for e-fuels and e-chemicals in these countries, producing 3.5 TWhth,LHV of e-kerosene, 2.6 TWhth,LHV of e-diesel, 19 TWhth,LHV of e-methanol, 2.5 TWhth,LHV of e-LNG, and 4.9 TWhth,LHV of e-ammonia. The cost projections for 2050 suggest that e-fuels and e-chemicals produced from Kerguelen Islands could be highly competitive, with projected costs of 95.0 €/MWh for e-kerosene and e-diesel, 78.7 €/MWh for e-methanol, 64.5 €/MWh for e-LNG, and 68.4 €/MWh for e-ammonia.
In addition to wave power, the system would incorporate 2 GWhcap of battery storage and 50 GWh of underground rock cavern hydrogen storage, further enhancing the energy hub's capacity and flexibility. These costs, assumed for 2050, are projected to be competitive compared to leading global sites, such as the Atacama Desert, which has excellent solar PV resources. For comparison, the Atacama Desert’s e-fuels production cost is estimated to range from 70-75 €/MWh, e-methanol is between 49-57 €/MWh and e-ammonia at 53 €/MWh.
However, the costs mentioned above do not include shipping costs. Shipping costs for ammonia for 10,000 km to East Asia could add up to 8 €/MWh, while shipping costs for methanol could add up to 4 €/MWh. For the Kerguelen Islands an attractive business model could be established to diversify the global e-fuels and e-chemicals production that may largely shift towards solar energy. This creates a promising opportunity for investment in a gigawatt-scale energy hub for e-fuels and e-chemicals on Kerguelen Islands, including the necessary infrastructure for shipping and workforce to maintain such a system.
To evaluate the feasibility of establishing an energy hub on Kerguelen Islands, a scenario was developed using the EnergyPLAN modelling software. The scenario involves producing e-fuels and e-chemicals, which will be essential for sectors like marine and aviation transportation and chemicals as the world transitions to a defossilised economy. This analysis assumes that the islands could supply fuel for East Asia, particularly Japan, South Korea, and Taiwan. By 2050, the 7 GW wave power system could meet 3% of the demand for e-fuels and e-chemicals in these countries, producing 3.5 TWhth,LHV of e-kerosene, 2.6 TWhth,LHV of e-diesel, 19 TWhth,LHV of e-methanol, 2.5 TWhth,LHV of e-LNG, and 4.9 TWhth,LHV of e-ammonia. The cost projections for 2050 suggest that e-fuels and e-chemicals produced from Kerguelen Islands could be highly competitive, with projected costs of 95.0 €/MWh for e-kerosene and e-diesel, 78.7 €/MWh for e-methanol, 64.5 €/MWh for e-LNG, and 68.4 €/MWh for e-ammonia.
In addition to wave power, the system would incorporate 2 GWhcap of battery storage and 50 GWh of underground rock cavern hydrogen storage, further enhancing the energy hub's capacity and flexibility. These costs, assumed for 2050, are projected to be competitive compared to leading global sites, such as the Atacama Desert, which has excellent solar PV resources. For comparison, the Atacama Desert’s e-fuels production cost is estimated to range from 70-75 €/MWh, e-methanol is between 49-57 €/MWh and e-ammonia at 53 €/MWh.
However, the costs mentioned above do not include shipping costs. Shipping costs for ammonia for 10,000 km to East Asia could add up to 8 €/MWh, while shipping costs for methanol could add up to 4 €/MWh. For the Kerguelen Islands an attractive business model could be established to diversify the global e-fuels and e-chemicals production that may largely shift towards solar energy. This creates a promising opportunity for investment in a gigawatt-scale energy hub for e-fuels and e-chemicals on Kerguelen Islands, including the necessary infrastructure for shipping and workforce to maintain such a system.
Additional features in HAMS-MREL
A new open-source BIEM solver for offshore energy applications
HAMS-MREL is a recently developed open-source BIEM solver, which allows for the solution of the diffraction and radiation problem for multiple floating rigid structures, taking into account their interaction. This has shown to highly accurate when compared with semi-analytical solutions/commercial solver WAMIT, within a computationally efficient framework that is parallelized. The solver is currently capable of providing the hydrodynamic coefficients (added mass and radiation damping) and exciting forces for all 6 rigid body modes per body. With this research, the solver has been extended significantly to include the following features for the multiple body interaction problem 1) Removal of irregular frequencies, 2) Global symmetry, 3) Wave fields and 4) Generalized modes. This study contributes further to the open-source domain with the development of highly accurate numerical tools for the accelerated deployment of offshore renewables.
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HAMS-MREL is a recently developed open-source BIEM solver, which allows for the solution of the diffraction and radiation problem for multiple floating rigid structures, taking into account their interaction. This has shown to highly accurate when compared with semi-analytical solutions/commercial solver WAMIT, within a computationally efficient framework that is parallelized. The solver is currently capable of providing the hydrodynamic coefficients (added mass and radiation damping) and exciting forces for all 6 rigid body modes per body. With this research, the solver has been extended significantly to include the following features for the multiple body interaction problem 1) Removal of irregular frequencies, 2) Global symmetry, 3) Wave fields and 4) Generalized modes. This study contributes further to the open-source domain with the development of highly accurate numerical tools for the accelerated deployment of offshore renewables.
In line with the global shift to transition away from fossil fuels to sustainable energy sources, tidal stream energy has emerged as a promising renewable option. This study investigates the tidal stream energy resources along the Dutch coast and focuses on the impact of Mean Sea Level (MSL) rise on the future resource potential. A THETIS high-resolution unstructured model is used. The model is validated against sea surface elevations, and the Dutch tidal stream resource uncertainties are well defined. The validated model is used to evaluate the tidal stream energy potential of the Netherlands, regions in the Wadden Sea and Westerschelde in Zeeland display noteworthy potential, evidenced by maximum average flow velocities of 1.3 m/s and maximum average energy densities of 1600 W/m2 for the Wadden Sea and maximum average flow velocities of 0.75 m/s and maximum average energy densities of 300 W/m2 for the Westerschelde. Forecasting the 2050 tidal stream resource, considering a projected 118 mm MSL rise, results indicate persistent energy characteristics, with minimal fluctuations in average velocities and average energy density when compared to the 2016 model. In the Wadden Sea and Zeeland, respectively, only marginal changes of +25 W/m2, and +8 W/m2 are observed in average energy density for those same locations. Furthermore, the inclusion of long-term constituents has negligible effects on the 2050 results, emphasising the stability of the tidal stream energy source. Tidal stream energy in the Netherlands stands out as a reliable and resilient energy source, demonstrating consistency in the face of projected MSL rise. Such predictability has the potential to contribute significantly to fostering a sustainable and secure energy system in the Netherlands, while aligning with global efforts to combat climate change.
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In line with the global shift to transition away from fossil fuels to sustainable energy sources, tidal stream energy has emerged as a promising renewable option. This study investigates the tidal stream energy resources along the Dutch coast and focuses on the impact of Mean Sea Level (MSL) rise on the future resource potential. A THETIS high-resolution unstructured model is used. The model is validated against sea surface elevations, and the Dutch tidal stream resource uncertainties are well defined. The validated model is used to evaluate the tidal stream energy potential of the Netherlands, regions in the Wadden Sea and Westerschelde in Zeeland display noteworthy potential, evidenced by maximum average flow velocities of 1.3 m/s and maximum average energy densities of 1600 W/m2 for the Wadden Sea and maximum average flow velocities of 0.75 m/s and maximum average energy densities of 300 W/m2 for the Westerschelde. Forecasting the 2050 tidal stream resource, considering a projected 118 mm MSL rise, results indicate persistent energy characteristics, with minimal fluctuations in average velocities and average energy density when compared to the 2016 model. In the Wadden Sea and Zeeland, respectively, only marginal changes of +25 W/m2, and +8 W/m2 are observed in average energy density for those same locations. Furthermore, the inclusion of long-term constituents has negligible effects on the 2050 results, emphasising the stability of the tidal stream energy source. Tidal stream energy in the Netherlands stands out as a reliable and resilient energy source, demonstrating consistency in the face of projected MSL rise. Such predictability has the potential to contribute significantly to fostering a sustainable and secure energy system in the Netherlands, while aligning with global efforts to combat climate change.