Offshore Power Research Articles

Structural Integrity Analysis of Marine Dynamic Cables: Water Trees and Fatigue

Abstract Offshore power cables are typically designed to have a service life of around 25 years. A pattern is emerging where these cables only last 10 years or even as little as two. The main consensus as to why the service life is so short is due to a combination of fatigue and fretting/wear damages of the copper conductors and water treeing in the insulation material. This study presents a method that can be used to analyze the structural integrity of dynamic subsea power cables and estimate their service life determined by the factors above. The numerical simulation models developed and used to carry out global and local fatigue analyses of dynamic subsea power cables are presented, together with methods and models for assessing fretting, wear, and growth of water tree defects. A methodology for structural integrity assessment that includes all these factors is proposed. A dynamic subsea power cable connected to a wave energy converter is used as the case study for comparison of the service life when these factors are considered compared to when, e.g., the growth of water trees is excluded. A numerical sensitivity analysis demonstrates that the value of the seawater's electrical conductivity and the insulation material's threshold stress-intensity factor greatly influence the cable's service life.

Challenges in Offshore Power Systems: Pushing HVac Transmission to the Limit

Challenges in Offshore Power Systems: Pushing HVac Transmission to the Limit

Sensitivity analysis on heat pump - mechanical vapor recompression desalination system by recovering waste heat of offshore power converter station

Abstract Offshore wind power converter stations produce massive low-temperature waste heat, which can hardly be used constrained by their offshore location. Therefore, the recovery of the waste heat has been raising widespread concern. Meanwhile, a large amount of fresh water is needed for its cooling system. So, a novel system combining high temperature heat pump and a mechanical vapor recompression system (HP-MVR) was proposed, and sensitivity analysis was performed to optimize it. The heat pump was used to absorb the waste heat and to produce high temperature water. The mechanical vapor recompression system was adopted to produce fresh water and to recover the condensation heat from the steam. In order to determine the impact parameters on the two crucial performance indicators of freshwater production and unit energy consumption, this article introduces a sensitivity analysis method, focusing on analyzing the sensitivity of the three operating parameters of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature to these two performance indicators. The results show that the sensitivity coefficients of heat pump condensation temperature, saturated water vapor inlet temperature entering the compressor, and freshwater condensation temperature are 1.13, -0.26, and 1.56. So, the freshwater condensation temperature has the most significant effect on freshwater output. Their sensitivity coefficients to unit energy consumption are 1.02, 1.41, and -0.64. The saturated water vapor inlet temperature entering the compressor has the most significant impact on the required power consumption per unit of freshwater. It will give some guidance for the application of low-temperature waste heat in seawater desalination and the reduction of operating costs.

Identifying critical demand scenarios for the robust capacitated network design problem using principal component analysis

AbstractIn this paper, we consider the single‐commodity robust network design problem. Given an undirected graph with capacity installation costs on its edges and a set of scenarios with associated flow balance vectors that represent different scenarios of node supplies and demands, the goal is to find integer edge capacities that minimize the total installation cost and permit a feasible single commodity flow for each scenario. This problem arises, for example, in the design of power networks, which are dimensioned to accommodate many different load scenarios. We propose a new method to identify a small subset of the given scenarios, such that solving the robust network design problem for the smaller scenario set leads to almost the same capacities as solving it for the full scenario set . By considering only the scenarios in , the size of the model that needs to be solved can be reduced substantially, while the error introduced by neglecting the remaining scenarios is kept very small. Our method only employs simple techniques from statistical data analysis, namely principal component analysis (PCA), and convex hull computations in low dimensions. Thus, its computational effort is very small and it is easily applicable to more complex network design problems. We evaluate the effectiveness of the method in computational experiments for instances stemming from offshore power grid planning and telecommunication networks. Our results show that the proposed techniques are indeed well suited to identify small scenario subsets that lead to significantly reduced models with high quality solutions.

Techno-Economic Assessment of a Full-Chain Hydrogen Production by Offshore Wind Power

Offshore wind power stands out as a promising renewable energy source, offering substantial potential for achieving low carbon emissions and enhancing energy security. Despite its potential, the expansion of offshore wind power faces considerable constraints in offshore power transmission. Hydrogen production derived from offshore wind power emerges as an efficient solution to overcome these limitations and effectively transport energy. This study systematically devises diverse hydrogen energy supply chains tailored to the demands of the transportation and chemical industries, meticulously assessing the levelized cost of hydrogen (LCOH). Our findings reveal that the most cost-efficient means of transporting hydrogen to the mainland is through pipelines, particularly when the baseline distance is 50 km and the baseline electricity price is 0.05 USD/kWh. Notably, delivering hydrogen directly to the port via pipelines for chemical industries proves considerably more economical than distributing it to hydrogen refueling stations, with a minimal cost of 3.6 USD/kg. Additionally, we assessed the levelized cost of hydrogen (LCOH) for supply chains that transmit electricity to ports via submarine cables before hydrogen production and subsequent distribution to chemical plants. In comparison to offshore hydrogen production routes, these routes exhibit higher costs and reduced competitiveness. Finally, a sensitivity analysis was undertaken to scrutinize the impact of delivery distance and electricity prices on LCOH. The outcomes underscore the acute sensitivity of LCOH to power prices, highlighting the potential for substantial reductions in hydrogen prices through concerted efforts to lower electricity costs.

Analysis of bias correction of HRRR model outputs for offshore wind power ramp events

This study examines the impact of bias correction on the prediction of offshore wind power ramp events (WPREs) using NOAA's High-Resolution Rapid Refresh (HRRR) model. The analysis focuses on New England's offshore region, using Light Detection and Ranging (LiDAR) wind observations and the power curve derived from the nearby Block Island wind farm as a reference. The study characterizes bias in terms of amplitude and phase, finding a 30-min systematic lag error and a marginal underestimation of high wind speeds. Perfect bias correction treatments including both the amplitude and the phase are applied to HRRR wind speed, and their impact on WPREs is assessed using categorical performance measures. A large discrepancy in the number of cases with HRRR having much fewer cases than the reference is found, which is attributed to the model's temporal and spatial resolution. The results show that the amplitude bias correction has a marginal impact on reducing frequency bias, while the dynamic time warping (DTW) used in the phase bias correction shows promising results but limited performance. The study concludes that phase bias correction can be a feasible option to reduce bias in WPREs in offshore power systems.

Stochastic optimization framework for hybridization of existing offshore wind farms with wave energy and floating photovoltaic systems

Due to the complementarity of renewable energy sources, there has been a focus on technology hybridization in recent years. In the area of hybrid offshore power plants, the current research projects mostly focus on the combinational implementation of wind, solar, and wave energy technologies. Accordingly, considering the already existing offshore wind farms, there is the potential for the implementation of hybrid power plants by adding wave energy converters and floating photovoltaics. In this work, a stochastic sizing model is developed for the hybridization of existing offshore wind farms using wave energy converters and floating photovoltaics considering the export cable capacity limitation. The problem is modeled from an investor perspective to maximize the economic profits of the hybridization, while the costs and revenues regarding the existing units and the export cable are excluded. Furthermore, to tackle the uncertainties of renewable energy generation, as well as the energy price, a scenario generation method based on copula theory is proposed to consider the dependency structure between the different random variables. Altogether, the hybridization study is modeled in a mixed integer linear programming optimization framework considering the net present value of the project as the objective function. The results showed that hybrid-sources-based energy generation provided the highest economic profit in the studied cases in the different geographical locations. Furthermore, the technical specifications of the farms have also been considerably improved providing more stable energy generation, guaranteeing a minimum level of power in a high share of the time, and with a better utilization of the capacity of the cable while the curtailment of energy is maintained within the acceptable range.

The Energy Conversion and Coupling Technologies of Hybrid Wind–Wave Power Generation Systems: A Technological Review

Based on the mutual compensation of offshore wind energy and wave energy, a hybrid wind–wave power generation system can provide a highly cost-effective solution to the increasing demands for offshore power. To provide comprehensive guidance for future research, this study reviews the energy conversion and coupling technologies of existing hybrid Wind–wave power generation systems which have not been reported in previous publications. The working principles of various wind and wave energy conversion technologies are summarised in detail. In addition, existing energy coupling technologies are specifically classified and described. All aforementioned technologies are comprehensively compared and discussed. Technological gaps are highlighted, and future development forecasts are proposed. It is found that the integration of hydraulic wind turbines and oscillating wave energy converters is the most promising choice for hybrid wind–wave power extraction. DC and hydraulic coupling are expected to become mainstream energy coupling schemes in the future. Currently, the main technological gaps include short their operating life, low energy production, limited economic viability, and the scarcity of theoretical research and experimental tests. The field offers significant opportunities for expansion and innovation.

Part-load thermal efficiency enhancement in gas turbine combined cycles by exhaust gas recirculation

Gas turbine power plants are popular for offshore power generation due to high power density and their reliability. However, growing usage of renewable energies put gas turbines in a load following backup operation. These power plants suffer part-load efficiency losses when operating at less than full capacity, resulting in higher carbon dioxide (CO2) emission from natural gas combined cycles or higher consumption of carbon-free fuels in decarbonized gas turbines. In this article, a solution is proposed for enhancement of power plant part-load thermal efficiency based on exhaust gas recirculation in the gas turbine cycle. Recirculating exhaust gas into the gas turbine have been studied by several researchers and engineers due to its benefit for carbon-free combustion and carbon capture mechanisms. The proposed operation strategy is evaluated for single-spool and two-spool gas turbines operating jointly with a steam bottoming cycle harvesting the waste heat for further power production. In the suggested strategy, eliminating the necessity to cool down the recirculated gas resulted in less equipment footprint for the power plant which makes it more favorable for offshore applications. An in-house design and simulation tool is developed for evaluating gas turbines with modern gas recirculating systems and a flexibility in operation with carbon-free fuel mixtures. The enhancement in efficiency boost, emission reduction, and fuel consumption is quantified demonstrating the improvements with the proposed solution.

Operation and control of compact offshore combined cycles for power generation

Gas turbines are the main means for generating power in offshore installations. To increase energy efficiency, and thus reduce CO2 emissions, a steam bottoming cycle can be added to produce additional power by recovering surplus heat from the gas turbine exhaust. Due to space constraints, this solution is not widespread for offshore power generation. To enable deployment, the system must be compact and be able to provide varying power demands. In this paper, we analyze the operation and control problem for such compact combined cycles, consisting of two gas turbines and one steam bottoming cycle. We analyze the steady-state performance of the combined cycle with respect to efficiency and CO2 emissions for two control strategies for coordinating the power setpoint of the two gas turbines. Equal load allocation of the gas turbines showed a higher thermal efficiency and lower emissions compared to keeping one gas turbine close to nominal and letting the second one handle load variations. The main controlled variables for the steam bottoming cycle are the superheated steam pressure and temperature. We implement decentralized control strategies based on standard PID-controllers and nonlinear feedforward. Due to reduced throttle losses, sliding pressure shows higher efficiency and lower CO2 emissions compared to keeping a constant steam pressure, which conversely provides a better temperature dynamic response and may be necessary with highly varying power demand.

Converting the energy of sea waves into electrical energy

AbstractThe study is highly relevant as ocean waves hold significant potential for producing electricity. Improvements in production, usage and rectification of research errors are crucial for meeting the energy demands of diverse consumers. The aim of this work is to put forward recommendations for eliminating design and implementation errors in wave energy conversion systems, specifically for offshore power plants, and to analyze their performance. Various methods were employed, including the analytical method, classification method, functional method, statistical method, synthesis method, and others. During the study, the characteristics and differences of ocean waves were observed, along with an analysis of the errors that can occur during the operation of offshore power plants designed for wave energy production and their associated causes. Uncertainties affecting the development of these power stations were identified, and the potential of sea waves as an energy resource was examined. Recommendations for enhanced regulation were put forward. The practicality lies in applying the identified findings to rectify errors in offshore power stations that use sea waves. This guarantees reliable operation by considering various factors and assists in recommending the optimal use of energy resources.

Improving Centralized Offshore Power Generation Design With Petri Net-Based Availability and Reliability Analysis

Abstract The offshore industry has actively sought technological solutions that reduce CO2 emissions from platform operations. One of the possible solutions being studied is the implementation of Power Hubs, which would generate electricity and distribute it to nearby platforms. Unlike the traditional approach, in which the electricity is generated in the platform for its operation, centralizing such generation via Power Hubs can make the process more efficient, reducing CO2 emissions. However, such a configuration increases the complexity of the operation and can impact the reliability and availability of platforms connected to the Power Hub. Therefore, this work aims to perform reliability and availability estimates of this type of operational configuration and compare it with the traditional offshore operation to quantify the difference between them. Various kinds of Power Hubs configurations were also analyzed to compare the results obtained. Such analyzes were performed using Generalized Stochastic Petri Nets (GSPNs) models. Results show that, depending on their configurations, Power Hubs can guarantee an average availability of energy generation close to 100% even in periods of higher demand for oil and gas production.

Hydrogen for harvesting the potential of offshore wind: A North Sea case study

Economical offshore wind developments depend on alternatives for cost-efficient transmission of the generated energy to connecting markets. Distance to shore, availability of an offshore power grid and scale of the wind farm may impede export through power cables. Conversion to H2 through offshore electrolysis may for certain offshore wind assets be a future option to enable energy export. Here, we analyse the cost sensitivity of offshore electrolysis for harvesting offshore wind in the North Sea using a technology-detailed multi-carrier energy system modelling framework for analysis of energy export. We include multiple investment options for electric power and hydrogen export including HVDC cables, new hydrogen pipelines, tie-in to existing pipelines and pipelines with linepacking. Existing hydropower is included in the modelling, and the effect on offshore electrolysis from increased pumping capacity in the hydropower system is analysed. Considering the lack of empirical cost data on offshore electrolysis, as well as the high uncertainty in future electricity and H2 prices, we analyse the cost sensitivity of offshore electrolysis in the North Sea by comparing costs relative to onshore electrolysis and energy prices relative to a nominal scenario. Offshore electrolysis is shown to be particularly sensitive to the electricity price, and an electricity price of 1.5 times the baseline assumption was needed to provide sufficient offshore energy for any significant offshore electrolysis investments. On the other hand, too high electricity prices would have a negative impact on offshore electrolysis because the energy is more valuable as electricity, even at the cost of increased wind power curtailment. This shows that there is a window-of-opportunity in terms of onshore electricity where offshore electrolysis can play a significant role in the production of H2. Pumped hydropower increases the maximum installed offshore electrolysis at the optimal electricity and H2 prices and makes offshore electrolysis more competitive at low electricity prices. Linepacking can make offshore electrolysis investments more robust against low H2 and high electricity prices as it allow for more variable H2 production through storing excess energy from offshore. The increased electrolysis capacity needed for variable electrolyser operation and linepacking is installed onshore due to its lower CAPEX compared to offshore installations.

Powering the Blue Economy: Marine Energy at Kelp Farm Sites

Abstract Marine energy (ME) has the potential to power businesses in the blue economy. Kelp farms are an emerging maritime market of the blue economy and are predicted to grow, but they are not currently using ME for their power needs. As the number and size of kelp farms increase, more offshore power will be needed onsite for operations, monitoring, and harvesting. ME devices such as tidal current energy converters and wave energy converters (WECs) may be used to supply power for these needs. This article assesses the status of kelp farming in the continental United States, investigates the electricity needs of kelp farms, and examinesthe feasibility of generating the required electricity from wave and tidal current energy. The United States currently has 165 kelp farms that have either active or pending permits. The farms use electricity for boat operations, kelp drying, environmental monitoring, offshore lighting, and the raising and lowering of lines. Most kelp farms are in protected, nearshore waters that do not have significant wave energy resources. The limited available wave energy could be used to power small devices, but WECs have not yet been developed for that application. Some kelp farms are in locations that feature significant tidal energy resources, but small tidal current energy converters that are compatible with existing farm operations are not yet commercially available. As low-power WECs and tidal current energy converters are developed, kelp farms could be research partners and early adopters of the new technologies, which would encourage their broader use by other blue economy businesses.

Impact of epistemic uncertainty on tradeoff in model-based decision support for methane hydrate development system design

Global decarbonization trends encouraged the consideration of a methane hydrate (MH) development system design combined with carbon capture and storage (CCS) in the Japanese national MH research program. Previous studies have also proposed decarbonized MH development systems, but the conclusions vary due to epistemic uncertainty. Epistemic uncertainty arises from the knowledge and understanding of the subject, and each expert has different assumptions. Therefore, we assume that developing a model encompassing epistemic uncertainty as a platform allows for discussion toward system design decisions. This study builds the evaluation model, considering epistemic uncertainty to support the decision-making on the system design and reveal the tradeoff. It identifies the epistemic uncertainty affecting the tradeoff by changing the conditions based on previous studies. The evaluation model consists of technological options as modules, and all system concepts are evaluated by combining them. Epistemic uncertainty was subdivided and implemented within the evaluation model. As a result, the evaluation model output the tradeoff with bands of uncertainty. While the development field significantly impacts the results, hydrogen-related systems and offshore power plant systems score well owing to synergies between options. The epistemic uncertainty analysis regarding the tradeoff suggests that system design uncertainty impacts the conclusions. This finding indicates the importance of the model development as a platform for the evaluation of various system designs. This study contributed to an approach to model-based decision-making with epistemic uncertainty.

Assessing the Validity of Analytical Equations for Offshore Power Cable Bending with Fixed and Loose Tube Fiber Strain Sensors

Assessing the Validity of Analytical Equations for Offshore Power Cable Bending with Fixed and Loose Tube Fiber Strain Sensors

Offshore Wind Power Transmission Decision-making Based on Grey Correlation and Topsis

With the profound transformation of the global energy structure, the development and utilization of wind energy have become the focus of global attention. The offshore wind power industry has ushered in a historic development opportunity and China’s offshore wind power industry has entered the fast track of development. However, due to the variety of transmission schemes available for offshore wind power, there are many differences in the economy, reliability, environment, risk, and other aspects of different transmission schemes, so it is difficult to make the optimal decision. To comprehensively compare the advantages and disadvantages of different transmission schemes in actual scenarios, this paper first identifies their influencing factors to obtain an evaluation index system and uses the entropy weight method to determine the index weight based on the index evaluation data of typical offshore wind power transmission projects at home and abroad, and the grey correlation method and TOPSIS method are integrated to build a comprehensive evaluation model suitable for offshore power transmission. Finally, the scientific and rigorous nature of the research method and model is verified by example analysis. The optimal decision comprehensive evaluation model constructed in this paper can realize scientific and comprehensive evaluation of offshore wind power transmission schemes and has important decision-making significance for the selection of transmission schemes in different scenarios.

High variability and exceptionally low thermal conductivities in nearshore sediments: a case study from the Eckernförde Bay

Heat flow measurements are a standard technique in Geophysics both onshore and offshore. Recently, such measurements became increasingly important in shallow waters. The increasing amount of offshore power installations makes it necessary to have a good knowledge about the subsurface heat flow and the thermal properties of the sediments to optimize the construction of the necessary powerlines. While the thermal properties are well studied for deep ocean sediments, only few published data exist for nearshore sediments. In this study, we investigate the sediment temperatures and thermal conductivities of nearshore sediments in the German part of the Baltic Sea. The shallow sediment temperatures reflect the interplay of the response to the seasonal cycle in connection with the sediments’ thermal conductivity. We find thermal conductivity values ranging from 0.67 to 3.34 W/(m*K) for the sediments down to ~ 4.2 m below seafloor. This variability exceeds that of conservative estimates widely used for coastal sediments and is also much higher than the variability found in the deep oceans. Sandy sediments show thermal conductivities larger than 1 W/(m*K) whereas organic-rich muds have lower values (< 1 W/(m*K)). Furthermore, the thermal conductivities seem to decrease with increasing free gas content in the sediment. The latter needs to be confirmed by further investigations.

A GIS-based FAHP and FEDAS analysis framework for suitable site selection of a hybrid offshore wind and solar power plant

This study presents a Geographic Information System (GIS) based suitable site selection methodology for a hybrid system that includes offshore wind and solar PV. The methodology utilizes open source databases about decision criteria and applies this data using GIS to determine suitable sites for offshore wind and solar PV systems. For the assessment of multi-criteria which affect the potential hybrid energy power plants and the determination of the best suitable areas, Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Evaluation based on Distance Average Solution (FEDAS) are used in the study. Results show that technical criteria has the priority weight of 0.60 while the weight of social criteria is about 0.07. Among sub-criteria, the wind speed has the highest priority weight while distance to port and visibility are the highest criteria of priority weight under economic and social main criteria, respectively. Among the alternatives, Area 2 (A-2) is determined as the best alternative for hybrid offshore power plants in the study area. This proposed methodology can be utilized by decision-makers to determine the best suitable locations for hybrid offshore wind and solar PV systems at any location. This paper suggests a new approach integrating GIS, fuzzy setbased AHP and EDAS as a novelty.

Consistent mapping of marine structures with an autonomous surface vehicle using motion compensation and submap-based filtering

Inspection and maintenance of marine energy farms are becoming increasingly important as more farms are developed and constructed. In this study, structural monitoring system using an autonomous surface vehicle (ASV) has been proposed to enable the inspection of an offshore power plant under harsh ocean disturbances. In particular, the ASV uses guidance and control laws to minimize the deviation from the desired path in waypoint tracking. The ASV was also equipped with multi-modal sensors – sonar and light detection and ranging (LiDAR) – for mapping underwater and surface structures. By utilizing the navigation sensors, the motion of the ASV in ocean disturbances was accurately estimated and incorporated into the mapping process to produce consistent multi-modal maps. Furthermore, dedicated outlier removal methods were proposed to improve the performance over conventional approaches in real offshore data. We considered the sparsity of the sonar and LiDAR data in their respective modality during acquisition and designed novel submap-based filtering to remove the outliers. To validate the proposed system, a field test was conducted on an offshore wave farm structure. It was verified that the ASV can cope with ocean disturbances in its waypoint tracking, and the resulting multi-modal maps are consistent and outlier-free.