J. Tan
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1
Journal article
(2026)
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Yi Xiao, Zedong Wang, Peng Jin, Hongkun Zhuang, Wenhua Zhao, Jian Tan, Binzhen Zhou
Integrating wave energy converters (WECs) into floating offshore wind turbines (FOWTs) offers the potential to reduce both power generation costs and platform motions. Placing WECs within the hollow side columns of the wind turbine platform represents a novel approach, providing protection against direct wave impact and corrosion. However, the mechanisms and performances of such hybrid systems remain unclear. In this study, a novel wind-wave hybrid system is proposed and investigated, consisting of a 10 MW OO-STAR type platform with built-in WECs. A frequency-domain model based on potential flow theory is developed, and a multi-objective optimization framework using the NSGA-II algorithm is applied to optimize the power take-off (PTO) parameters. Results indicate that global optimization across operational sea-state ranges can effectively mitigates abnormally large pitch motions in specific period ranges, thereby reducing the maximum pitch response across all sea states and broadening the energy absorption bandwidth. By introducing the metric of annual average power generation per unit mass, the economic efficiency of the system is further enhanced. Moreover, the mechanisms by which the PTO parameters influence motion responses and power generation performance of the hybrid system are revealed. These findings provide practical guidance for design and application of wind-wave hybrid systems.
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Integrating wave energy converters (WECs) into floating offshore wind turbines (FOWTs) offers the potential to reduce both power generation costs and platform motions. Placing WECs within the hollow side columns of the wind turbine platform represents a novel approach, providing protection against direct wave impact and corrosion. However, the mechanisms and performances of such hybrid systems remain unclear. In this study, a novel wind-wave hybrid system is proposed and investigated, consisting of a 10 MW OO-STAR type platform with built-in WECs. A frequency-domain model based on potential flow theory is developed, and a multi-objective optimization framework using the NSGA-II algorithm is applied to optimize the power take-off (PTO) parameters. Results indicate that global optimization across operational sea-state ranges can effectively mitigates abnormally large pitch motions in specific period ranges, thereby reducing the maximum pitch response across all sea states and broadening the energy absorption bandwidth. By introducing the metric of annual average power generation per unit mass, the economic efficiency of the system is further enhanced. Moreover, the mechanisms by which the PTO parameters influence motion responses and power generation performance of the hybrid system are revealed. These findings provide practical guidance for design and application of wind-wave hybrid systems.
Phase-resolved wave estimation during operation of floating structures based on motion measurements provides an efficient, low-cost approach to enhancing operations. Prolate spheroidal wave functions (PSWFs) enable the reconstruction of wave profiles in short time windows with the help of a wave-to-motion response amplitude operator (RAO). Although fully linear hydrodynamic modeling can efficiently derive the RAO of floating structures, its applicability is highly limited to rather linear operation conditions. This study extends the PSWF methodology for wave estimation by combining it with the statistical linearization approach, which allows nonlinearities to be incorporated into the RAO based on the measured motion. The combined methodology is verified with motions for a floating cylinder and sphere, whose motions were calculated using a time domain simulation based on Cummins equation. Viscous drag and nonlinear hydrostatic forces were investigated. The results showed that the combined methodology increased the accuracy of the resulting wave profiles, measured in terms of correlation and spectral differences. Combining PSWFs and statistical linearization reproduced wave profiles with correlation values above 0.9 in waves with periods greater than 9 s. Combining both nonlinear effects for the sphere slightly increased the method’s accuracy due to the reduced motion amplitudes.
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Phase-resolved wave estimation during operation of floating structures based on motion measurements provides an efficient, low-cost approach to enhancing operations. Prolate spheroidal wave functions (PSWFs) enable the reconstruction of wave profiles in short time windows with the help of a wave-to-motion response amplitude operator (RAO). Although fully linear hydrodynamic modeling can efficiently derive the RAO of floating structures, its applicability is highly limited to rather linear operation conditions. This study extends the PSWF methodology for wave estimation by combining it with the statistical linearization approach, which allows nonlinearities to be incorporated into the RAO based on the measured motion. The combined methodology is verified with motions for a floating cylinder and sphere, whose motions were calculated using a time domain simulation based on Cummins equation. Viscous drag and nonlinear hydrostatic forces were investigated. The results showed that the combined methodology increased the accuracy of the resulting wave profiles, measured in terms of correlation and spectral differences. Combining PSWFs and statistical linearization reproduced wave profiles with correlation values above 0.9 in waves with periods greater than 9 s. Combining both nonlinear effects for the sphere slightly increased the method’s accuracy due to the reduced motion amplitudes.
Obtaining the hydrodynamic pressure distribution on the wetted surface of floating structures is a critical step in structural analysis and is commonly achieved through pressure regeneration based on predicted global dynamic responses. Using derived hydrodynamic coefficients, various dynamic modeling approaches, including Cummins-equation-based nonlinear time-domain modeling, statistical linearization, and Lorentz linearization, can be applied to solve for the global dynamics of structures subjected to specific wave conditions. These dynamic modeling approaches differ in both computational efficiency and modeling fidelity. Despite their widespread use, a systematic comparison of these approaches, particularly between statistical and Lorentz linearization in predicting global dynamics and regenerated pressure fields, remains limited. This study addresses this gap by conducting a comparative study of linear-potential-flow-based dynamic modeling approaches using a generic cylindrical floater, incorporating a representative nonlinear external machinery effect through different modeling approaches. The resulting global responses are used to regenerate hydrodynamic pressure distributions, showing that all the dynamic modeling approaches agree well under low wave steepness. As wave steepness increases, the prediction performance of statistical linearization, Lorentz linearization, and a simplified Lorentz linearization, gradually decreases relative to the nonlinear time-domain model. Among these, the statistical linearization approach provides results closer to the nonlinear time-domain model than both Lorentz-based linearization methods, particularly in capturing global dynamics and reconstructing hydrodynamic pressure distributions under relatively high wave steepness. Given its high computational efficiency, the statistical linearization approach has the potential to be further developed as an efficient alternative modeling for estimating dynamic responses and hydrodynamic pressure distributions.
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Obtaining the hydrodynamic pressure distribution on the wetted surface of floating structures is a critical step in structural analysis and is commonly achieved through pressure regeneration based on predicted global dynamic responses. Using derived hydrodynamic coefficients, various dynamic modeling approaches, including Cummins-equation-based nonlinear time-domain modeling, statistical linearization, and Lorentz linearization, can be applied to solve for the global dynamics of structures subjected to specific wave conditions. These dynamic modeling approaches differ in both computational efficiency and modeling fidelity. Despite their widespread use, a systematic comparison of these approaches, particularly between statistical and Lorentz linearization in predicting global dynamics and regenerated pressure fields, remains limited. This study addresses this gap by conducting a comparative study of linear-potential-flow-based dynamic modeling approaches using a generic cylindrical floater, incorporating a representative nonlinear external machinery effect through different modeling approaches. The resulting global responses are used to regenerate hydrodynamic pressure distributions, showing that all the dynamic modeling approaches agree well under low wave steepness. As wave steepness increases, the prediction performance of statistical linearization, Lorentz linearization, and a simplified Lorentz linearization, gradually decreases relative to the nonlinear time-domain model. Among these, the statistical linearization approach provides results closer to the nonlinear time-domain model than both Lorentz-based linearization methods, particularly in capturing global dynamics and reconstructing hydrodynamic pressure distributions under relatively high wave steepness. Given its high computational efficiency, the statistical linearization approach has the potential to be further developed as an efficient alternative modeling for estimating dynamic responses and hydrodynamic pressure distributions.
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.
Advanced constitutive modelling for deformation prediction of deep excavations in structured soft clay
Experimental validation and parametric analysis
Deep excavations in urban areas underlain by structured soft clay are critical for transportation infrastructure development, yet their deformation behavior is strongly influenced by natural soil structure and stress-path-dependent degradation. Conventional constitutive models (e.g., MCC and HS/HSS), which neglect soil structure and intermediate principal stress, often lead to unconservative deformation predictions. A modified constitutive model for structured soft clay is developed within the critical state framework, incorporating the superloading surface concept to represent soil structure. The model considers three key mechanisms governing excavation-induced deformation: (i) the intermediate principal stress effect through the SMP yield criterion, (ii) the initial soil structure described by a structural parameter R* , and (iii) strain-path-dependent structural degradation. A modified evolution law is introduced, in which a parameter A is used to distinguish the relative contributions of plastic volumetric and deviatoric strains to structural degradation. The model is implemented in finite element analyses and validated against centrifuge model tests. Parametric analyses are conducted to investigate the effects of intermediate principal stress, initial soil structure, and the plastic strain ratio parameter. The results show that neglecting intermediate principal stress underestimates wall deflection and ground surface settlement, while accounting for soil structure increases predicted deformation. This effect is moderated when strain-path-dependent structural degradation is considered, leading to improved agreement with experimental observations. Overall, the proposed approach provides a more realistic framework for deformation prediction of deep excavations in structured soft clay, with direct relevance to underground transportation infrastructure design.
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Deep excavations in urban areas underlain by structured soft clay are critical for transportation infrastructure development, yet their deformation behavior is strongly influenced by natural soil structure and stress-path-dependent degradation. Conventional constitutive models (e.g., MCC and HS/HSS), which neglect soil structure and intermediate principal stress, often lead to unconservative deformation predictions. A modified constitutive model for structured soft clay is developed within the critical state framework, incorporating the superloading surface concept to represent soil structure. The model considers three key mechanisms governing excavation-induced deformation: (i) the intermediate principal stress effect through the SMP yield criterion, (ii) the initial soil structure described by a structural parameter R* , and (iii) strain-path-dependent structural degradation. A modified evolution law is introduced, in which a parameter A is used to distinguish the relative contributions of plastic volumetric and deviatoric strains to structural degradation. The model is implemented in finite element analyses and validated against centrifuge model tests. Parametric analyses are conducted to investigate the effects of intermediate principal stress, initial soil structure, and the plastic strain ratio parameter. The results show that neglecting intermediate principal stress underestimates wall deflection and ground surface settlement, while accounting for soil structure increases predicted deformation. This effect is moderated when strain-path-dependent structural degradation is considered, leading to improved agreement with experimental observations. Overall, the proposed approach provides a more realistic framework for deformation prediction of deep excavations in structured soft clay, with direct relevance to underground transportation infrastructure design.
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.
Ensuring safety and preventing accidents in waterway channels are critical challenges for networked marine surface vessel systems (NMSVs). This study introduces a regulation-aware decision-making system designed to minimize traffic conflicts and enhance navigational safety in inland waterway traffic separation schemes. The proposed framework integrates a hierarchical conditional state machine with chance-constrained model predictive control, allowing NMSVs to handle complex traffic situations while complying with safety regulations. The hierarchical conditional state machine effectively identifies vessel maneuver states, implementing safety constraints that proactively avoid collisions. Meanwhile, the chance-constrained model predictive control optimizes vessel trajectories, factoring in uncertainties and potential risks, while simultaneously enhancing operational efficiency. Simulation and experimental results demonstrate that the proposed system significantly reduces the likelihood of accidents and improves overall safety by efficiently managing vessel interactions. Compared to traditional methods, the regulation-aware approach ensures better collision avoidance, greater regulation compliance, and superior safety performance. This study confirms that the proposed decision-making system can be effectively implemented in real time, offering practical benefits for improving waterway safety and mitigating accident risks.
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Ensuring safety and preventing accidents in waterway channels are critical challenges for networked marine surface vessel systems (NMSVs). This study introduces a regulation-aware decision-making system designed to minimize traffic conflicts and enhance navigational safety in inland waterway traffic separation schemes. The proposed framework integrates a hierarchical conditional state machine with chance-constrained model predictive control, allowing NMSVs to handle complex traffic situations while complying with safety regulations. The hierarchical conditional state machine effectively identifies vessel maneuver states, implementing safety constraints that proactively avoid collisions. Meanwhile, the chance-constrained model predictive control optimizes vessel trajectories, factoring in uncertainties and potential risks, while simultaneously enhancing operational efficiency. Simulation and experimental results demonstrate that the proposed system significantly reduces the likelihood of accidents and improves overall safety by efficiently managing vessel interactions. Compared to traditional methods, the regulation-aware approach ensures better collision avoidance, greater regulation compliance, and superior safety performance. This study confirms that the proposed decision-making system can be effectively implemented in real time, offering practical benefits for improving waterway safety and mitigating accident risks.
Wave energy converter (WEC) arrays should be designed to ensure consistent and optimal power production over long operational periods. This requires an understanding of stochastic wave variability, interactive effects among devices and their mutual dependence. In this work, a computationally efficient surrogate modelling framework was developed using data-driven polynomial chaos expansion (PCE) to analyze the performance of WEC arrays under realistic sea state conditions spanning 30 years. For this purpose, using Latin hypercube sampling scheme on a joint probability distribution derived from the ECHOWAVE hindcast dataset, resulting $10^6$ combinations of significant wave height (Hs), wave period (Tp), and WEC radius (R) for two array configurations—interacting and non-interacting cases were evaluated. The surrogate model was set up to evaluate the performance of WEC arrays by means of global sensitivity analysis using Sobol indices. The results conclude that the interactive effects significantly alter the contribution of design parameters (like geometry and spatial configurations) to power output, emphasizing the inadequacy of single-device analysis for array optimization. The findings highlight the importance of tailored WEC design within arrays and offer a robust approach for long-term performance prediction and optimization of wave energy farms.
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Wave energy converter (WEC) arrays should be designed to ensure consistent and optimal power production over long operational periods. This requires an understanding of stochastic wave variability, interactive effects among devices and their mutual dependence. In this work, a computationally efficient surrogate modelling framework was developed using data-driven polynomial chaos expansion (PCE) to analyze the performance of WEC arrays under realistic sea state conditions spanning 30 years. For this purpose, using Latin hypercube sampling scheme on a joint probability distribution derived from the ECHOWAVE hindcast dataset, resulting $10^6$ combinations of significant wave height (Hs), wave period (Tp), and WEC radius (R) for two array configurations—interacting and non-interacting cases were evaluated. The surrogate model was set up to evaluate the performance of WEC arrays by means of global sensitivity analysis using Sobol indices. The results conclude that the interactive effects significantly alter the contribution of design parameters (like geometry and spatial configurations) to power output, emphasizing the inadequacy of single-device analysis for array optimization. The findings highlight the importance of tailored WEC design within arrays and offer a robust approach for long-term performance prediction and optimization of wave energy farms.
Wave energy holds substantial promise as a renewable resource, but its commercial deployment remains limited. Research primarily focuses on individual wave energy converter (WEC) devices, while the interactions within WEC arrays have received less attention. Optimizing these interactions is essential for maximizing energy capture and minimizing operational costs. However, due to the variability of wave conditions, it is unlikely that a single WEC configuration will be effective across all scenarios. Therefore, to optimize performance, a large number of simulations are required, which is computationally expensive with traditional high-fidelity numerical methods. This paper addresses this challenge by utilizing a surrogate model based on polynomial chaos expansion (PCE), which efficiently captures the behavior of a WEC array over a 30-year probabilistic based on a high-fidelity wave dataset. The surrogate model is compared to a frequency domain model, demonstrating a high efficiency. The surrogate model is used to simulate the performance of an array of five point absorber WECs under varying wave conditions. The study highlights the following requirements for optimal array performance: the spatial configuration of WECs must consistently produce optimal power throughout the operational period and must adapt to the high variability of wave parameters. The results reveal that the fixed array configuration under study, produces power that is inconsistent over varying sea conditions, showing suboptimal energy production under most wave conditions, and higher power output only under less probable wave scenarios. These findings provide insights into the physical interactions influencing WEC array performance and can inform future design methodologies for wave energy farms. The proposed surrogate modeling framework offers a highly efficient tool for conducting large-scale probabilistic analyses of WEC arrays, significantly reducing computational effort while enabling more accurate performance predictions.
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Wave energy holds substantial promise as a renewable resource, but its commercial deployment remains limited. Research primarily focuses on individual wave energy converter (WEC) devices, while the interactions within WEC arrays have received less attention. Optimizing these interactions is essential for maximizing energy capture and minimizing operational costs. However, due to the variability of wave conditions, it is unlikely that a single WEC configuration will be effective across all scenarios. Therefore, to optimize performance, a large number of simulations are required, which is computationally expensive with traditional high-fidelity numerical methods. This paper addresses this challenge by utilizing a surrogate model based on polynomial chaos expansion (PCE), which efficiently captures the behavior of a WEC array over a 30-year probabilistic based on a high-fidelity wave dataset. The surrogate model is compared to a frequency domain model, demonstrating a high efficiency. The surrogate model is used to simulate the performance of an array of five point absorber WECs under varying wave conditions. The study highlights the following requirements for optimal array performance: the spatial configuration of WECs must consistently produce optimal power throughout the operational period and must adapt to the high variability of wave parameters. The results reveal that the fixed array configuration under study, produces power that is inconsistent over varying sea conditions, showing suboptimal energy production under most wave conditions, and higher power output only under less probable wave scenarios. These findings provide insights into the physical interactions influencing WEC array performance and can inform future design methodologies for wave energy farms. The proposed surrogate modeling framework offers a highly efficient tool for conducting large-scale probabilistic analyses of WEC arrays, significantly reducing computational effort while enabling more accurate performance predictions.
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.
The cooperative control of multiple autonomous surface vehicles (ASVs) is a critical area of research due to its significant applications in maritime operations, such as search and rescue and environmental monitoring. However, challenges such as communication delays and dynamic topologies often hinder stable cooperative control in practical scenarios. This study addresses these challenges by developing a formation control method based on consensus theory, focusing on both formation control and time delay. First, a simplified ASV characteristic model is established, and a basic consensus control algorithm is designed and analyzed for stability, considering different communication topologies. Then, to handle delays, the formation control method is extended, and the stability of the revised algorithm is rigorously proven using the Lyapunov function. Simulation results demonstrate that the proposed control strategy effectively maintains formations, even in the presence of communication delays. In the end, comparative simulations are carried out to demonstrate the effectiveness and robustness of the proposed controller. Simulation results demonstrate that the proposed control strategy effectively maintains formations, even in the presence of communication delays, with a convergence time of approximately 100 s and a formation error stabilizing at around 7 m. This research lays a foundation for more reliable cooperative control systems for ships, with potential applications in a variety of maritime and autonomous systems.
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The cooperative control of multiple autonomous surface vehicles (ASVs) is a critical area of research due to its significant applications in maritime operations, such as search and rescue and environmental monitoring. However, challenges such as communication delays and dynamic topologies often hinder stable cooperative control in practical scenarios. This study addresses these challenges by developing a formation control method based on consensus theory, focusing on both formation control and time delay. First, a simplified ASV characteristic model is established, and a basic consensus control algorithm is designed and analyzed for stability, considering different communication topologies. Then, to handle delays, the formation control method is extended, and the stability of the revised algorithm is rigorously proven using the Lyapunov function. Simulation results demonstrate that the proposed control strategy effectively maintains formations, even in the presence of communication delays. In the end, comparative simulations are carried out to demonstrate the effectiveness and robustness of the proposed controller. Simulation results demonstrate that the proposed control strategy effectively maintains formations, even in the presence of communication delays, with a convergence time of approximately 100 s and a formation error stabilizing at around 7 m. This research lays a foundation for more reliable cooperative control systems for ships, with potential applications in a variety of maritime and autonomous systems.
Journal article
(2025)
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Chen Xi, Jian Tan, George Lavidas, Hongyi Jiang, Shengjie Rui, Yujie Jiang, Zhen Guo
A critical challenge to the practical deployment of wave energy converters (WECs) is their vulnerability to extreme wave loads. This study proposes a novel design for an oscillating body-WEC, called adjustable draft WEC (ADWEC), which aims to enhance resilience under extreme wave conditions while maintain extraction efficiency at normal sea states. The present numerical simulations focus on the interaction between regular extreme waves and ADWEC in both fixed and dynamic conditions. It is found that the excitation force is highly sensitive to wave nonlinearities, appearing as an asymmetric excitation force in the horizontal direction and a double-peak phenomenon in the vertical direction. Increasing the draft can significantly reduce vertical loads and heave motion, thereby enhancing survivability by mitigating impact forces and buoyancy fluctuations. A shallower draft allows for greater heave amplitude and higher energy conversion, particularly under short-period conditions. The present findings reveal that the draft of the ADWEC has significant effects on the wave loads, hydrodynamic performance and energy extraction, which provides guidance to the practical design of WECs for survivability.
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A critical challenge to the practical deployment of wave energy converters (WECs) is their vulnerability to extreme wave loads. This study proposes a novel design for an oscillating body-WEC, called adjustable draft WEC (ADWEC), which aims to enhance resilience under extreme wave conditions while maintain extraction efficiency at normal sea states. The present numerical simulations focus on the interaction between regular extreme waves and ADWEC in both fixed and dynamic conditions. It is found that the excitation force is highly sensitive to wave nonlinearities, appearing as an asymmetric excitation force in the horizontal direction and a double-peak phenomenon in the vertical direction. Increasing the draft can significantly reduce vertical loads and heave motion, thereby enhancing survivability by mitigating impact forces and buoyancy fluctuations. A shallower draft allows for greater heave amplitude and higher energy conversion, particularly under short-period conditions. The present findings reveal that the draft of the ADWEC has significant effects on the wave loads, hydrodynamic performance and energy extraction, which provides guidance to the practical design of WECs for survivability.
This article investigates the methodology and applicability of the statistical linearization (SL) method to incorporating multi-variate non-differentiable nonlinearities, with a focus on floating renewable energy devices. The SL method serves as a highly competitive approach for analyzing floating renewable energy structures, such as wave energy converters (WECs) and floating wind energy turbines, because it inherently combines adequate accuracy and high computational efficiency. The origin of high accuracy comes from its incorporation of nonlinear effects through statistically linearized representations. Yet, the statistically linearized solutions have only been derived and verified for a limited number of nonlinearities of floating renewable energy devices, mostly simply-formed and differentiable in their mathematical expressions. However, floating renewable energy devices usually exhibit a complex dynamic mechanism, in which the relevant nonlinear effects could appear to be highly complex for linearization process to describe. These nonlinear effects could make a significant impact on the system dynamics, exemplified by external machinery force saturation and nonlinear hydrostatics of floaters with a non-uniform geometry. To push forward the boundary of the SL method, it is crucial to demonstrate how it applies to nonlinearities of different features. In this paper, the existing SL method is extended to address the nonlinear effects expressed as multi-variate non-differentiable functions. Several case studies are carried out to exemplify the application of the extended SL approach to the concerned nonlinearities in floating renewable energy devices. The accuracy and computational efficiency of the extended SL approach are evaluated by verifying against the corresponding nonlinear time-domain (TD) and linear frequency-domain (FD) models. Despite the complexity of the given nonlinearities, the relative errors of the SL approach are no more than 6 % while its computational time is comparable to the FD model, being thousands of times faster than the TD model. Comparatively, the FD model leads to a relative error of over 70% in some cases.
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This article investigates the methodology and applicability of the statistical linearization (SL) method to incorporating multi-variate non-differentiable nonlinearities, with a focus on floating renewable energy devices. The SL method serves as a highly competitive approach for analyzing floating renewable energy structures, such as wave energy converters (WECs) and floating wind energy turbines, because it inherently combines adequate accuracy and high computational efficiency. The origin of high accuracy comes from its incorporation of nonlinear effects through statistically linearized representations. Yet, the statistically linearized solutions have only been derived and verified for a limited number of nonlinearities of floating renewable energy devices, mostly simply-formed and differentiable in their mathematical expressions. However, floating renewable energy devices usually exhibit a complex dynamic mechanism, in which the relevant nonlinear effects could appear to be highly complex for linearization process to describe. These nonlinear effects could make a significant impact on the system dynamics, exemplified by external machinery force saturation and nonlinear hydrostatics of floaters with a non-uniform geometry. To push forward the boundary of the SL method, it is crucial to demonstrate how it applies to nonlinearities of different features. In this paper, the existing SL method is extended to address the nonlinear effects expressed as multi-variate non-differentiable functions. Several case studies are carried out to exemplify the application of the extended SL approach to the concerned nonlinearities in floating renewable energy devices. The accuracy and computational efficiency of the extended SL approach are evaluated by verifying against the corresponding nonlinear time-domain (TD) and linear frequency-domain (FD) models. Despite the complexity of the given nonlinearities, the relative errors of the SL approach are no more than 6 % while its computational time is comparable to the FD model, being thousands of times faster than the TD model. Comparatively, the FD model leads to a relative error of over 70% in some cases.
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.
For manoeuvring surface target tracking in the presence of glint noise, Huber-based Kalman filters have been widely regarded as effective. However, when the proportion of outlier measurements is high, their numerical stability and estimation accuracy can deteriorate significantly. To address this issue, we propose a Robust Cubature Kalman Filter with the Current Statistical (RCKF_CS) model. Inspired by the Huber equivalent weight function, an adaptive factor incorporating a penalty strategy based on a smoothing approximation function is introduced to suppress the adverse effects of glint noise. The proposed method is then integrated into the Cubature Kalman Filter framework combined with the Current Statistical model. Unlike conventional Huber-based approaches, which process measurement residuals independently in each dimension, the proposed method evaluates the residuals jointly to improve robustness. Numerical stability analysis and extensive simulation experiments confirm that the proposed RCKF_CS achieves improved numerical robustness and filtering performance, even under strong glint noise conditions. Compared with existing Huber-based filters, the proposed method enhances filtering performance by 2.66% to 10.18% in manoeuvring surface target tracking tasks affected by glint noise.
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For manoeuvring surface target tracking in the presence of glint noise, Huber-based Kalman filters have been widely regarded as effective. However, when the proportion of outlier measurements is high, their numerical stability and estimation accuracy can deteriorate significantly. To address this issue, we propose a Robust Cubature Kalman Filter with the Current Statistical (RCKF_CS) model. Inspired by the Huber equivalent weight function, an adaptive factor incorporating a penalty strategy based on a smoothing approximation function is introduced to suppress the adverse effects of glint noise. The proposed method is then integrated into the Cubature Kalman Filter framework combined with the Current Statistical model. Unlike conventional Huber-based approaches, which process measurement residuals independently in each dimension, the proposed method evaluates the residuals jointly to improve robustness. Numerical stability analysis and extensive simulation experiments confirm that the proposed RCKF_CS achieves improved numerical robustness and filtering performance, even under strong glint noise conditions. Compared with existing Huber-based filters, the proposed method enhances filtering performance by 2.66% to 10.18% in manoeuvring surface target tracking tasks affected by glint noise.
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.
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.
A modified spectral-domain (SD) model is introduced in this study to address the nonlinear hydrostatic restoring force for heaving wave energy converters (WECs) with non-uniform cross-sectional areas. Distinguished from previous SD models, the modified SD model collectively includes the effects of incident wave elevation and buoy displacement, through the utilization of the multi-variate stochastic linearization method. The proposed SD model is verified against results obtained from a corresponding nonlinear time-domain (TD) model. Subsequently, a comprehensive comparison is carried out between the modified SD model, the other two existing SD models and the linear frequency-domain (FD) model. The nonlinear TD model is considered as the accuracy reference in this comparison. Various environmental and operational inputs, such as sea states, Power Take-Off (PTO) parameters, and buoy drafts, are systematically taken into account in the comparison. Additionally, the computational efficiency of each model is evaluated.
The results suggest that the modified SD model demonstrates significantly enhanced accuracy in cases where hydrostatic force nonlinearity intensifies, compared to the existing SD models and the FD model. Throughout the entire domain of the simulation cases, the maximum relative error of the modified SD model to the nonlinear TD model is below 5 %, while it is 20 % for the FD model and approximately 15 % for the two existing SD models. Moreover, the modeling accuracy of the FD model and existing SD models could be strongly disturbed by the variation of the environmental and operational inputs. Comparatively, the modified SD model is associated with much more stable accuracy. Nevertheless, the modified SD model only requires a modest increase in computational load compared to the FD model and existing SD models and it is still thousands of times faster than the nonlinear TD model. ...
The results suggest that the modified SD model demonstrates significantly enhanced accuracy in cases where hydrostatic force nonlinearity intensifies, compared to the existing SD models and the FD model. Throughout the entire domain of the simulation cases, the maximum relative error of the modified SD model to the nonlinear TD model is below 5 %, while it is 20 % for the FD model and approximately 15 % for the two existing SD models. Moreover, the modeling accuracy of the FD model and existing SD models could be strongly disturbed by the variation of the environmental and operational inputs. Comparatively, the modified SD model is associated with much more stable accuracy. Nevertheless, the modified SD model only requires a modest increase in computational load compared to the FD model and existing SD models and it is still thousands of times faster than the nonlinear TD model. ...
A modified spectral-domain (SD) model is introduced in this study to address the nonlinear hydrostatic restoring force for heaving wave energy converters (WECs) with non-uniform cross-sectional areas. Distinguished from previous SD models, the modified SD model collectively includes the effects of incident wave elevation and buoy displacement, through the utilization of the multi-variate stochastic linearization method. The proposed SD model is verified against results obtained from a corresponding nonlinear time-domain (TD) model. Subsequently, a comprehensive comparison is carried out between the modified SD model, the other two existing SD models and the linear frequency-domain (FD) model. The nonlinear TD model is considered as the accuracy reference in this comparison. Various environmental and operational inputs, such as sea states, Power Take-Off (PTO) parameters, and buoy drafts, are systematically taken into account in the comparison. Additionally, the computational efficiency of each model is evaluated.
The results suggest that the modified SD model demonstrates significantly enhanced accuracy in cases where hydrostatic force nonlinearity intensifies, compared to the existing SD models and the FD model. Throughout the entire domain of the simulation cases, the maximum relative error of the modified SD model to the nonlinear TD model is below 5 %, while it is 20 % for the FD model and approximately 15 % for the two existing SD models. Moreover, the modeling accuracy of the FD model and existing SD models could be strongly disturbed by the variation of the environmental and operational inputs. Comparatively, the modified SD model is associated with much more stable accuracy. Nevertheless, the modified SD model only requires a modest increase in computational load compared to the FD model and existing SD models and it is still thousands of times faster than the nonlinear TD model.
The results suggest that the modified SD model demonstrates significantly enhanced accuracy in cases where hydrostatic force nonlinearity intensifies, compared to the existing SD models and the FD model. Throughout the entire domain of the simulation cases, the maximum relative error of the modified SD model to the nonlinear TD model is below 5 %, while it is 20 % for the FD model and approximately 15 % for the two existing SD models. Moreover, the modeling accuracy of the FD model and existing SD models could be strongly disturbed by the variation of the environmental and operational inputs. Comparatively, the modified SD model is associated with much more stable accuracy. Nevertheless, the modified SD model only requires a modest increase in computational load compared to the FD model and existing SD models and it is still thousands of times faster than the nonlinear TD model.
An adjustable draft point absorber was recently proposed as a novel approach to improve power absorption with constrained power take-off (PTO) capacities. The key feature of the novel wave energy converter (WEC) concept is to adjust the buoy draft by regulating the ballast water inside the buoy, which aims to enable variation of the natural frequency of the WEC. Although previous research has shown benefits for the energy absorption stage, the impact of the draft adjustment on the power conversion efficiency and overall performance has not been examined yet. Therefore, a wave-to-wire model is established to provide an in-depth insight into the systematic performance of the adjustable draft point absorber integrated with a linear permanent magnet generator. Both a nonlinear hydrodynamic model and an analytical generator model are derived, thus the complete process from the wave power input through the whole WEC system to the usable electricity is covered. Based on the established model, wave-to-wire responses of the novel concept are obtained and analyzed. The negative effects of the draft adjustment on the stroke and overlap between the stator and translator are demonstrated. Moreover, a comparison is made between this novel WEC and conventional fixed draft WEC, and both regular and irregular wave states are considered. The results show that the adjustable draft system could increase not only the absorbed power but also the generator conversion efficiency. In specific conditions, the delivered electrical power of the adjustable draft WEC was over 20 % and 10 % higher than a traditional fixed draft system for regular and irregular waves respectively.
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An adjustable draft point absorber was recently proposed as a novel approach to improve power absorption with constrained power take-off (PTO) capacities. The key feature of the novel wave energy converter (WEC) concept is to adjust the buoy draft by regulating the ballast water inside the buoy, which aims to enable variation of the natural frequency of the WEC. Although previous research has shown benefits for the energy absorption stage, the impact of the draft adjustment on the power conversion efficiency and overall performance has not been examined yet. Therefore, a wave-to-wire model is established to provide an in-depth insight into the systematic performance of the adjustable draft point absorber integrated with a linear permanent magnet generator. Both a nonlinear hydrodynamic model and an analytical generator model are derived, thus the complete process from the wave power input through the whole WEC system to the usable electricity is covered. Based on the established model, wave-to-wire responses of the novel concept are obtained and analyzed. The negative effects of the draft adjustment on the stroke and overlap between the stator and translator are demonstrated. Moreover, a comparison is made between this novel WEC and conventional fixed draft WEC, and both regular and irregular wave states are considered. The results show that the adjustable draft system could increase not only the absorbed power but also the generator conversion efficiency. In specific conditions, the delivered electrical power of the adjustable draft WEC was over 20 % and 10 % higher than a traditional fixed draft system for regular and irregular waves respectively.