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This paper presents a life cycle assessment (LCA) of the International Energy Agency (IEA) 15 MW Reference Wind Turbine (RWT), on floating platforms, deployed in commercial-scale arrays at multiple locations around Scotland in the ScotWind leasing round. Site-specific energy production and vessel operations are provided by a dedicated offshore wind farm operations and maintenance (O&M) model, COMPASS, allowing service operation vessel (SOV) O&M impacts to be assessed with increased confidence. For climate change, the median global warming impact varied from 17.4 to 26.3 gCO2eq/kWh across the four sites within a 95% confidence interval using an uncertainty assessment of both foreground and background data. As is common with other offshore renewable energy systems, materials and manufacture account for 71% to 79% of global warming impact, while O&M comprise between 9% and 16% of the global warming impacts. High-voltage direct current (HVDC) export cables, floating platforms, and composite blades are significant contributors to the environmental impacts of these arrays (by mass and material choice), while the contributions from ballast, vessel transportation emissions, and power-train components are lower. The results suggest that material efficiencies, circularity, and decarbonizing material supply inventories should be a priority for the Scottish floating wind sector, followed by minimizing vessel operations and the decarbonization of vessel propulsion, while avoiding burden shifting to other impact categories. [ABSTRACT FROM AUTHOR]

Hybrid renewable hydrogen energy systems could play a key role in delivering sustainable solutions for enabling the Net Zero ambition; however, the lack of exact computational modelling tools for sizing the integrated system components and simulating their real-world dynamic behaviour remains a key technical challenge against their widespread adoption. This paper addresses this challenge by developing a precise dynamic model that allows sizing the rated capacity of the hybrid system components and accurately simulating their real-world dynamic behaviour while considering effective energy management between the grid-integrated system components to ensure that the maximum possible proportion of energy demand is supplied from clean sources rather than the grid. The proposed hybrid system components involve a solar PV system, electrolyser, pressurised hydrogen storage tank and fuel cell. The developed hybrid system model incorporates a set of mathematical models for the individual system components. The developed precise dynamic model allows identifying the electrolyser's real-world hydrogen production levels in response to the input intermittent solar energy production while also simulating the electrochemical behaviour of the fuel cell and precisely quantifying its real-world output power and hydrogen consumption in response to load demand variations. Using a university campus case study building in Scotland, the effectiveness of the developed model has been assessed by benchmarking comparison between its results versus those obtained from a generic model in which the electrochemical characteristics of the electrolyser and fuel cell systems were not taken into consideration. Results from this comparison have demonstrated the potential of the developed model in simulating the real-world dynamic operation of hybrid solar hydrogen energy systems for grid-connected buildings while sizing the exact capacity of system components, avoiding oversizing associated with underutilisation costs and inaccurate simulation. [ABSTRACT FROM AUTHOR]

This paper is a literature review of fuel and transport poverty in the U.K. with a focus on contextualising this challenge in Scotland. Building on the discussion in the literature, we see that the objective of policy interventions should be to provide a mechanism for identifying vulnerable households. First, we analyse the definitions of fuel, energy, and transport poverty and observe that definitions in policy have been used to limit the scope of the issue to make it more easily addressable. In contrast, academic research points out that fuel poverty should not only encompass all energy use, including household heating, but that transport poverty should be considered under the same umbrella as the drivers overlap. We then consider the indicators used to measure fuel and transport poverty, finding that the thresholds set are arbitrary and only measure one of many possible drivers, namely expenditure. Through an analysis of the drivers, it is clear that both fuel and transport poverty are complex multidimensional challenges requiring a combination of indicators to allow the policy to accurately identify vulnerable households. [ABSTRACT FROM AUTHOR]

The main obstacle against the penetration of wind power into the power grid is its high variability in terms of wind speed fluctuations. Accurate power forecasting, while making maintenance more efficient, leads to the profit maximisation of power traders, whether for a wind turbine or a wind farm. Machine learning (ML) models are recognised as an accurate and fast method of wind power prediction, but their accuracy depends on the selection of the correct hyperparameters. The incorrect choice of hyperparameters will make it impossible to extract the maximum performance of the ML models, which is attributed to the weakness of the forecasting models. This paper uses a novel optimisation algorithm to tune the long short-term memory (LSTM) model for short-term wind power forecasting. The proposed method improves the power prediction accuracy and accelerates the optimisation process. Historical power data of an offshore wind turbine in Scotland is utilised to validate the proposed method and compare its outcome with regular ML models tuned by grid search. The results revealed the significant effect of the optimisation algorithm on the forecasting models' performance, with improvements of the RMSE of 7.89, 5.9, and 2.65 percent, compared to the persistence and conventional grid search-tuned Auto-Regressive Integrated Moving Average (ARIMA) and LSTM models. [ABSTRACT FROM AUTHOR]

Offshore wind could both play a significant role in decarbonising the global energy system and supporting the energy needs of cities. Recent trends in offshore wind have seen the installation of turbines in deeper and more remote waters due to the presence of stronger and more consistent wind resources. This has led to the development of floating foundations for turbine mounting in water depths above 40 m, where conventional bottom-fixed foundations are not considered economically feasible. However, due to its emerging nature, floating wind must attain market maturity to be considered cost competitive. It is a widely accepted belief that market expansion yields technological maturity. Therefore, this paper adopts a systems approach to investigate the viability of floating offshore wind power generation in Scotland and South Africa. It does this through a content analysis of relevant secondary documentation, including policy documents, industry reports, press releases, online publications, and databases to determine the drivers and barriers of floating wind in the case contexts. The key findings are that substantial technical potential is required to attract floating wind investments, political support is necessary in order to scale up, a strong offshore wind supply chain could cushion the high-cost effects of floating wind projects, and more innovative business models such as corporate Power Purchasing Agreements could serve as social drivers for such projects. The main contextual conclusions drawn from this paper are that Scotland's inaugural floating wind projects benefitted from the Scottish government's Renewable Obligation scheme, however its discontinuation threatens the prospects of future projects. Alternatively, South Africa's technical potential, coupled with its government's healthy appetite for renewable energy development, could see the take up of this technology in the near future, with corresponding benefits for more sustainable energy in densely populated areas, compliant with SDG 7. [ABSTRACT FROM AUTHOR]

Wind energy plays a major role in decarbonisation of the electricity sector and supports achieving net-zero greenhouse gas emissions. Over the last decade, the wind energy deployments have grown steadily, accounting for more than one fourth of the annual electricity generation in countries like the United Kingdom, Denmark, and Germany. However, as the share of wind energy increases, system operators face challenges in managing excessive wind generation due to its nondispatchable nature. Currently, the most common practice is wind energy curtailment in which wind farm operators receive constraint payments to reduce their renewable energy production. This practice not only leads to wastage of large volumes of renewable energy, but also the associated financial cost is reflected to rate payers in the form of increased electricity bills. On-site energy storage technologies come to the forefront as a technology option to minimise wind energy curtailment and to harness wind energy in a more efficient way. To that end, this paper, first, systematically evaluates different energy storage options for wind energy farms. Second, a depth analysis of curtailment and constraint payments of major wind energy farms in Scotland are presented. Third, using actual wind and market datasets, a techno-economic analysis is conducted to examine the relationship between on-site energy storage size and the amount of curtailment. The results show that, similar to recent deployments, lithium-ion technology is best suited for on-site storage. As case studies, Whitelee and Gordon bush wind farms in Scotland are chosen. The most suitable storage capacities for 20 years payback period is calculated as follows: (i) the storage size for the Gordonbush wind farm is 100 MWh and almost 19% of total curtailment can be avoided and (ii) the storage size for the Whitlee farm is 125 MWh which can reduce the curtailment by 20.2%. The outcomes of this study will shed light into analysing curtailment reduction potential of future wind farms including floating islands, seaports, and other floating systems. [ABSTRACT FROM AUTHOR]

The performance of wind turbines is not only dependent on the wind turbine design itself, but is also dependent on the accurate assessment of wind resources at the installation site. In this paper, the numerical site calibration (NSC) method using three-dimensional Reynolds-averaged Navier–Stokes (RANS) simulation was proposed to accurately forecast the wind flow characteristics of wind turbine sites with complex terrains, namely Methil in Scotland, and Haenam in South Korea. From NSC at the Methil and Haenam sites, it was shown that the complicated and vortical flow fields around hills and valleys were captured using the three-dimensional RANS CFD simulation in Ansys CFX software based on a high-resolution scheme with a renormalization group (RNG)-based k-ε turbulence model. It was also shown that topographically induced wind profile and turbulence intensity over a local-scale complex terrain are remarkably dominated by flow separation after passing hills. It was concluded that the proposed NSC method using three-dimensional RANS simulation with a high-resolution scheme was an economically useful method for evaluating wind flow characteristics numerically to assess wind turbine sites with complex terrains and designing the wind farm layout. [ABSTRACT FROM AUTHOR]

As tidal current and marine hydro-kinetic energy converters start to be deployed in pre-commercial arrays, it is critical that the design conditions are properly characterised. Turbulence is known to influence fatigue loads and power production, so developers use turbulence models to generate unsteady flows in order to simulate device performance. Most such models construct a synthetic flow field using a combination of measured parameters and theoretical assumptions. The majority in use today are based on atmospheric flow conditions and may have limited applicability in tidal environments. In the present work, we compare key turbulence model assumptions (which are recommended by the tidal turbine standards and are used in design software) to turbulence measurements from two tidal test sites in Scotland and Canada. Here, we show that the two sites have different levels of conformity to theoretical models, with significant variability within nearby locations at the same site. The agreement with spectral models is shown to be depth-dependent. The vertical component spectrum is better represented by the Kaimal model, while the streamwise spectrum is better represented by the von Kármán model. With the exception of one site, the shear profiles follow a power law, although with a different exponent to that commonly assumed. Both sites show significant deviations from the theoretical length scales and isotropy ratios. Such deviations are likely to misrepresent the loads experienced by a device. These results highlight the turbulence characteristics at real deployment sites, which are not well represented by current models, and, hence, which must be determined using field measurements. [ABSTRACT FROM AUTHOR]

In this research, a hierarchical met-ocean data selection model is proposed to reduce the computational cost in stochastic simulation of operation and maintenance (O&M) and enable rapid evaluation of offshore renewable energy systems. The proposed model identifies the most representative data for each calendar month from the long-term historical met-ocean data in two steps, namely the preselection and the refined selection. The preselection incorporates three distinct metrics to evaluate the characteristics of statistical distributions, including the Jensen–Shannon divergence, the encapsulation of extreme met-ocean conditions, as well as the overall vessel accessibility. For the refined selection, a component of temporal synchrony is devised to emulate dynamic changes of met-ocean conditions. As such, a met-ocean reference year comprising twelve representative historical months is subsequently produced and deployed as the input for O&M stochastic simulation. While this research focuses on the development of a generalised methodology for selecting representative met-ocean data, the proposed statistical method is validated empirically using a case study inspired by real-life floating offshore wind installations in Scotland, e.g., Hywind and Kincardine projects. According to the O&M simulation results with five capacity scenarios, the proposed data selection model reduces the computational cost by up to 97.65% while emulating the original results with minor deviations, i.e., within ± 5%. The simulation speed is therefore 43 times quicker. Overall, the proposed met-ocean data selection model attains an excellent trade off between computational efficiency and accuracy in O&M stochastic simulation. [ABSTRACT FROM AUTHOR]

Photovoltaic solar energy is booming due to the continuous improvement in photovoltaic panel efficiency along with a downward trend in production costs. In addition, the European Union is committed to easing the implementation of renewable energy in many companies in order to obtain funding to install their own panels. Nonetheless, the nature of solar energy is intermittent and uncontrollable. This leads us to an uncertain scenario which may cause instability in photovoltaic systems. This research addresses this problem by implementing intelligent models to predict the production of solar energy. Real data from a solar farm in Scotland was utilized in this study. Finally, the models were able to accurately predict the energy to be produced in the next hour using historical information as predictor variables. [ABSTRACT FROM AUTHOR]

Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( C F ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that C F values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying. [ABSTRACT FROM AUTHOR]

Domestic heating accounts for 64% of domestic energy usage in the UK, yet there are currently very few viable options for low carbon residential heating. The government's carbon plan commits to improving the uptake of district heating connections in new build dwellings, but the greatest carbon saving can be made through targeting traditional housing stock. This paper aims to quantify the potential carbon and energy savings that can be made by connecting a traditional tenement building to a district heating scheme. The study uses a transient system simulation tool (TRNSYS) model to simulate the radiator system in a tenement block and shows that a significant benefit can be achieved by reducing the supply temperature; however, the minimum supply temperature is drastically limited by the building condition. Therefore, the study also critically compares the benefits of a lower supply temperature against minor refurbishments. It was found that improving building conditions alone could offer a 30% reduction in space heating energy consumption, while building improvements and integration of a river source heat pump could offer almost a 70% reduction. It is the recommendation of this study that a dwelling be improved as much as economically possible to achieve the greatest carbon and energetic savings. [ABSTRACT FROM AUTHOR]

The oil and gas industry is a major economic driver in many regions and countries, providing workers with well-paid jobs and spurring investments and economic growth. The need to transition these industries in order to meet climate commitments presents a major challenge. How can the costs and risks to workers and communities of the transition be mitigated? How can stakeholders be included in decisions that impact them? How do transitions impact the broader economy of these regions and what are they transitioning to? Importantly, how can regional development policies support this process? This comparative policy review explores just transition management in three oil and gas dependent regions that have signified the need to transition away from the oil and gas sector, i.e., Taranaki (New Zealand), the northeast of Scotland, and the Jutland peninsula in southwest Denmark, drawing out key lessons and leading practices. These cases are positioned within an empirically grounded, conceptual framework of national and regional just transition policies. [ABSTRACT FROM AUTHOR]

The decarbonisation of heating in the United Kingdom is likely to entail both the mass adoption of heat pumps and widespread development of district heating infrastructure. Estimation of the spatially disaggregated heat demand is needed for both electrical distribution network with electrified heating and for the development of district heating. The temporal variation of heat demand is important when considering the operation of district heating, thermal energy storage and electrical grid storage. The difference between the national and urban heat demands profiles will vary due to the type and occupancy of buildings leading to temporal variations which have not been widely surveyed. This paper develops a high-resolution spatiotemporal heat load model for Great Britain (GB: England, Scotland a Wales) by identifying the appropriate datasets, archetype segmentation and characterisation for the domestic and nondomestic building stock. This is applied to a thermal model and calibrated on the local scale using gas consumption statistics. The annual GB heat demand was in close agreement with other estimates and the peak demand was 219 GWth. The urban heat demand was found to have a lower peak to trough ratio than the average national demand profile. This will have important implications for the uptake of heating technologies and design of district heating. [ABSTRACT FROM AUTHOR]

In this work, we have designed, developed and deployed the world's first optical wireless communication (OWC) system using off-the-shelf lasers and solar photovoltaics. Four bidirectional OWC prototypes have been installed on the Orkney Islands of Scotland at a 30 m link distance for the provision of high-speed internet access to two residential properties. The silicon-made solar panels can harvest power up to 5 W from sunlight and they offer data rates as high as 8 Mb/s. Using additional analogue processing, data rates higher than the existing landline broadband connection are achieved. This breakthrough opens the development path to low cost, self-powered and plug-and-play free-space optical (FSO) systems. [ABSTRACT FROM AUTHOR]