Centre for Marine and Renewable Energy (MaREI) - Journal Articles
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Item Mutation based improved dragonfly optimization algorithm for a neuro-fuzzy system in short term wind speed forecasting(Elsevier B.V., 2023-03-20) Parmaksiz, Huseyin; Yuzgec, Ugur; Dokur, Emrah; Erdogan, Nuh; Türkiye Bilimsel ve Teknolojik Araştırma KurumuThe Dragonfly algorithm (DA) is a heuristic optimization algorithm that is commonly used for complex optimization problems. Despite its widespread application, the abundance of social behaviors in its construct can lead to poor accuracy in solutions and an imbalance between exploration and exploitation phases. To overcome these issues, this paper proposes a mutation-based Dragonfly optimization algorithm (MIDA). In order to increase the solution accuracy of the original DA and reduce its handicaps, the proposed model includes three procedures, namely, mutation operation, boundary control, and greedy selection mechanisms. The mutation operator helps to find global optima by avoiding getting stuck at the local optimum point, while the boundary control and greedy selection mechanisms update the dragonflies at each iteration and thus use the better fitness value of the updated ones. The performance of the proposed MIDA is tested and shown to be superior to the original DA using several analyses such as convergence, search history, trajectory, average distance, computational complexity, diversity and balance. To validate the MIDA algorithm, it is tested on the 10, 30, 50 and 100 dimensions of the CEC2014 benchmark functions. Furthermore, a comparison against twelve state-of-the-art (SOTA) meta-heuristic optimization algorithms is performed. The performance of the proposed MIDA is also compared with the performances of some improved dragonfly algorithms taken from the literature. The statistical results obtained by the original DA and MIDA for ten minimization problems with 5, 10, 15 and 20 dimensions from the CEC2020 test suite are presented. Finally, the proposed algorithm is applied to optimize the ANFIS model parameters in order to be used for short-term wind forecasting as a real-world problem. The results obtained for the different dimensions of CEC2014 and CEC2020 test problems in the study show that the search performance of proposed MIDA is better than that of the original DA. MIDA outperformed the original DA by 91.33% for CEC2014 benchmarks and 94.25% for CEC2020 benchmarks. In addition, MIDA came first in comparison with twelve different SOTAs from the literature. In comparisons with different DA versions, MIDA took the second place in terms of statistical performance. Computational complexity was examined in the CEC2020 benchmarks and it was seen that MIDA has a more effective run time than DA. Finally, the short-term wind speed forecasting results of the ANFIS-DA hybrid model according to four different error metrics are more successful than those of the ANFIS-DA hybrid model.Item Modelling the installation of next generation floating offshore wind farms(Elsevier Ltd., 2024-07-26) Devoy McAuliffe, Fiona; Judge, Frances M.; Murphy, JimmyThe offshore wind industry is advancing with larger turbines (10 MW+) into sites in deeper waters (>60 m), necessitating innovative floating substructures. However, Floating Offshore Wind (FOW) must still be proven to be cost-efficient, with special attention paid to developing installation, Operations and Maintenance (O&M) and decommissioning strategies that will ensure FOW is competitive. Simulation is an efficient way to assess the viability of new technologies and the innovative operations required to install and maintain them. This paper presents a novel tool that simulates the installation of fixed/floating offshore wind farms across an hourly time-series of Metocean data, producing a total estimation of costs as part of the total capital expenditure (CAPEX). The paper validates the model by simulating installation of Hywind Scotland, the FOW farm, and comparing results with published data. Given the lack of real-world cost data and experience, this paper then seeks to provide a well-defined case-study for future researchers to develop further in other regions and with different technologies. The tool is applied to a theoretical large commercial 1GW FOW farm commissioned in 2035 at a representative site in the Celtic Sea. This considers a promising location for FOW development outside the existing demonstration/early commercial FOW projects, which are primarily focused on the North Sea. Results indicate a CAPEX (including installation) of €3492/kW, which is in line with industry expectations. Sensitivity analysis applies a learning rate to reduce platform costs, and varies farm capacity, demonstrating the potential economies of scale when increasing farm size. Simulation identifies weather operational limits and cable installation duration as key contributors to installation time and costs. This quantifies where cost-savings can be found and optimisation should focus. Further modelling considers the scale of their impact on results. A final Levelised Cost of Energy assessment estimating an LCoE range of €52.3–64.59/MWh, placing the FOW farm in the context of global economic targets.Item Integrating short term variations of the power system into integrated energy system models: A methodological review(Elsevier Ltd., 2017-03-27) Collins, Seán; Deane, John Paul; Poncelet, Kris; Panos, Evangelos; Pietzcker, Robert C.; Delarue, Erik; Ó Gallachóir, Brian Pádraig; SFI Research Centre for Energy, Climate and Marine; Vlaamse Instelling voor Technologisch OnderzoekIt is anticipated that the decarbonisation of the entire energy system will require the introduction of large shares of variable renewable electricity generation into the power system. Long term integrated energy systems models are useful in improving our understanding of decarbonisation but they struggle to take account of short term variations in the power system associated with increased variable renewable energy penetration. This can oversimplify the ability of power systems to accommodate variable renewables and result in mistaken signals regarding the levels of flexibility required in power systems. Capturing power system impacts of variability within integrated energy system models is challenging due to temporal and technical simplifying assumptions needed to make such models computationally manageable. This paper addresses a gap in the literature by reviewing prominent methodologies that have been applied to address this challenge and the advantages & limitations of each. The methods include soft linking between integrated energy systems models and power systems models and improving the temporal and technical representation of power systems within integrated energy systems models. Each methodology covered approaches the integration of short term variations and assesses the flexibility of the system differently. The strengths, limitations, and applicability of these different methodologies are analysed. This review allows users of integrated energy systems models to select a methodology (or combination of methodologies) to suit their needs. In addition, the analysis identifies remaining gaps and shortcomings.Item Marine protected areas show low overlap with projected distributions of seabird populations in Britain and Ireland(Elsevier Ltd., 2018-06-20) Critchley, Emma Jane; Grecian, W. James; Kane, Adam; Jessopp, Mark J.; Quinn, John L.; Science Foundation Ireland; Irish Research Council; Irish Petroleum Infrastructure Programme; INSITEMarine Protected Areas (MPAs) are an important tool for the conservation of seabirds. However, mapping seabird distributions using at-sea surveys or tracking data to inform the designation of MPAs is costly and time-consuming, particularly for far-ranging pelagic species. Here we explore the potential for using predictive distribution models to examine the effectiveness of current MPAs for the conservation of seabirds, using Britain and Ireland as a case study. A distance-weighted foraging radius approach was used to project distributions at sea for an entire seabird community during the breeding season, identifying hotspots of highest density and species richness. The percentage overlap between distributions at sea and MPAs was calculated at the level of individual species, family group, foraging range group (coastal or pelagic foragers), and conservation status. On average, 32.5% of coastal populations and 13.2% of pelagic populations overlapped with MPAs indicating that pelagic species, many of which are threatened, are likely to have significantly less coverage from protected areas. We suggest that a foraging radius approach provides a pragmatic and rapid method of assessing overlap with MPA networks for central place foragers. It can also act as an initial tool to identify important areas for potential designation. This would be particularly useful for regions throughout the world with limited data on seabird distributions at sea and limited resources to collect this data. Future assessment for marine conservation management should account for the disparity between coastal and pelagic foraging species to ensure that wider-ranging seabirds are afforded adequate levels of protection.Item Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations(Elsevier Ltd., 2018-03-21) Marzband, Mousa; Azarinejadian, Fatemeh; Savaghebi, Mehdi; Pouresmaeil, Edris; Guerrero, Josep M.; Lightbody, Gordon; Horizon 2020; Science Foundation Ireland; Energiteknologisk udviklings- og demonstrationsprogram; Ministry of Science and Technology of the People's Republic of ChinaThis paper presents a smart Transactive energy (TE) framework in which home microgrids (H-MGs) can collaborate with each other in a multiple H-MG system by forming coalitions for gaining competitiveness in the market. Profit allocation due to coalition between H-MGs is an important issue for ensuring the optimal use of installed resources in the whole multiple H-MG system. In addition, considering demand fluctuations, energy production based on renewable resources in the multiple H-MG can be accomplished by demand-side management strategies that try to establish mechanisms to allow for a flatter demand curve. In this regard, demand shifting potential can be tapped through shifting certain amounts of energy demand from some time periods to others with lower expected demand, typically to match price values and to ensure that existing generation will be economically sufficient. It is also possible to obtain the maximum profit with the coalition formation. In essence the impact of the consumption shifting in the multiple H-MG schedule can be considered while conducting both individual and coalition operations. A comprehensive simulation study is carried out to reveal the effectiveness of the proposed method in lowering the market clearing price (MCP) for about 15% of the time intervals, increasing H-MG responsive load consumption by a factor of 30%, and promoting local generation by a factor of three. The numerical results also show the capability of the proposed algorithm to encourage market participation and improve profit for all participants.