Article
Green & Sustainable Science & Technology
Huai-Wei Lo, Chao-Che Hsu, Bo-Cheng Chen, James J. H. Liou
Summary: Choosing suitable sites is crucial for offshore wind power development. This study proposes a hybrid model using grey DANP and P-GRA methods to select the optimal alternative. The model optimizes traditional methods and demonstrates feasibility through a case study in Taiwan.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Engineering, Marine
Eray Caceoglu, Hatice Kubra Yildiz, Elif Oguz, Nejan Huvaj, Josep M. Guerrero
Summary: This study presents a quantitative methodology using GIS and AHP for offshore wind power plant site selection in Northwest Turkey. Multiple criteria decision-making methods were employed to evaluate the site selection criteria and identify the most suitable alternative sites.
Article
Energy & Fuels
Muhammet Deveci, Dragan Pamucar, Umit Cali, Emre Kantar, Konstanze Kolle, John O. Tande
Summary: Unlocking the high energy generation potential of offshore wind farms requires a comprehensive analysis in various disciplines, including technical, economic, logistical, and environmental aspects. Ranking alternative offshore wind energy projects based on different scenarios and circumstances helps prioritize investment decisions. This study aims to find the best site for a floating offshore wind farm in Norway, presenting a hybrid decision-making model that determines decision criteria weights using a new methodology. The proposed model concludes that Utsira Nord is the optimal site among the four alternatives, with stability verified through sensitivity analysis.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Muhammet Deveci, Ender Ozcan, Robert John, Dragan Pamucar, Himmet Karaman
Summary: The development of offshore wind farms has become increasingly important over the past 20 years due to higher average wind speeds at sea. A new hybrid approach integrating Interval Rough Numbers into Best-Worst Method and Measurement of Alternatives and Ranking according to Compromise Solution was introduced in this study for intelligent decision support in choosing the best offshore wind farm site. The results demonstrated the feasibility of the proposed approach and identified Bozcaada as the most suitable site.
APPLIED SOFT COMPUTING
(2021)
Article
Green & Sustainable Science & Technology
Zifeng Li, Guohua Tian, A. S. El-Shafay
Summary: This study is a statistical-analytical analysis of the development of offshore wind energy plants. It classifies countries based on their activity level in offshore wind energy production capacity and proposes a method for selecting suitable locations for offshore wind farms. The study identifies specific areas in the United Kingdom that are the best for installing offshore wind farms based on various criteria.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Zifeng Li, Guohua Tian, A. S. El-Shafay
Summary: The present study analyzed the development trend of offshore wind energy production capacity in the top 10 pioneering countries over the past 20 years and introduced a new index for ranking countries based on offshore wind energy per capita. The study found that the Great Britain (GB) is the most active country in terms of production capacity development, but Denmark, Belgium, Sweden, and Netherlands have better per capita energy production. Multi criteria decision analysis (MCDA) and GIS software were used to identify the best geographical coordinates for offshore wind farm siting, with northern, north western, north eastern, and some parts of western waters around GB identified as the most suitable areas for installation based on various criteria and altitudes.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Sung-ho Hur
Summary: A new control strategy of sharing controllers/converters for wind turbines is proposed to improve reliability and energy yield, especially for offshore wind turbines. The Matlab/Simulink model is utilized for simulation of each turbine, as well as for simulating clusters of multiple turbines.
Article
Chemistry, Multidisciplinary
Piotr Olczak, Tomasz Surma
Summary: Wind power is the leading technology for electricity production in Poland and globally. This study examined the impact of offshore wind energy on the Polish power system's ability to meet electricity demands. Statistical analysis methods were used to determine the productivity of wind turbines based on wind speed data. The capacity factor for onshore wind turbines in Poland was 25.5% in 2021 and 30.1% in 2022, while the planned offshore wind farms were projected to have a capacity factor of 55.6% in 2022. The study also analyzed the peak load demands and the quantitative impact of installing 6 GW of offshore wind turbine capacity on the national power system.
APPLIED SCIENCES-BASEL
(2023)
Article
Green & Sustainable Science & Technology
Shamsan Alsubal, Wesam Salah Alaloul, Eu Lim Shawn, M. S. Liew, Pavitirakumar Palaniappan, Muhammad Ali Musarat
Summary: The Malaysian government aims to increase the usage of renewable energy to 20% by 2025, with hydropower and biomass being the main sources. Studies have shown that wind energy has economic potential in Malaysia, especially in locations like Kudat, Mersing, and Kuala Terengganu.
Article
Green & Sustainable Science & Technology
Sara Porchetta, Domingo Munoz-Esparza, Wim Munters, Jeroen van Beeck, Nicole van Lipzig
Summary: Offshore wind energy has been steadily increasing as an ideal alternative energy source. This study shows the power production and wake lengths of 1250 offshore wind turbines in the German Bight, highlighting the significant impact of waves on wind farm power production and wake lengths in the offshore wind environment.
Article
Green & Sustainable Science & Technology
Lorenz Winkler, Onur A. Kilic, Jasper Veldman
Summary: This study aims to explore how actors in the offshore wind farm decommissioning supply chain collaborate to manage collective uncertainties. Semi-structured expert interviews were conducted with ten companies in the Netherlands, Germany, and Belgium. The findings suggest that businesses currently utilize collaborative communication, information sharing, and joint knowledge creation to mitigate the adverse effects of collective uncertainties. However, barriers such as intellectual property or the lack of resources severely impede collaboration.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Green & Sustainable Science & Technology
Isabel C. Gil-Garcia, Adela Ramos-Escudero, M. S. Garcia-Cascales, Habib Dagher, A. Molina-Garcia
Summary: This paper presents a multi-criterion decision-making approach for optimal off-shore wind location assessment by integrating fuzzy geographical information systems. The methodology involves prioritizing different locations and alternatives through an analytic hierarchy process and comparing with a fuzzy geographical information system solution. A case study in the Gulf of Maine includes a statistical evaluation of wind resources and a design proposal for a 1 GW offshore wind power plant using a variable speed wind turbine prototype.
Article
Green & Sustainable Science & Technology
Gaia Brussa, Mario Grosso, Lucia Rigamonti
Summary: Mitigation of climate change can be achieved through consistent actions to reduce emissions from the energy sector. The use of renewable energy technologies, such as offshore wind power, has become a cost-effective option for transitioning to low emission power generation systems. This study presents a life cycle assessment of a floating offshore wind farm, demonstrating its promising potential and competitiveness compared to other renewable energy generation technologies.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2023)
Article
Environmental Sciences
Alper Yildirim, Mehmet Bilgili, Hakan Akgun, Saban Unal
Summary: Turkey has become a major market for onshore wind energy, with a significant increase in onshore wind power installation to 10 GW in the last 10 years. Despite the absence of offshore wind farms, research shows untapped potential for wind energy in Turkey. A comprehensive techno-economic analysis of the Samandag Offshore Wind Farm project reveals its economic viability based on different Feed-in Tariffs and discount rates, with specific prerequisites needing to be met.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Alper Yildirim
Summary: A large part of Turkey's electricity generation comes from imported fossil fuels, making the country heavily dependent on them. To decrease this dependency, Turkey aims to increase the use of renewable energy resources. Among these resources, wind energy potential is high in the country. However, the focus on offshore wind energy has been lacking despite Turkey being surrounded by seas. To address this, the Turkish government accelerated the installation of the first offshore wind farm by opening a tender in 2018. This paper provides a comprehensive techno-economic analysis of potential offshore wind farm projects in three identified regions, and identifies the Saros OWF region as the most suitable for development.
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2023)
Article
Energy & Fuels
Said Mirza Tercan, Onur Elma, Erdin Gokalp, Umit Cali
Summary: A new method is proposed in the study to extend the lifespan of distributed energy systems with an energy storage system and reduce line upgrade costs. The results show that the proposed method can reduce total costs, decrease power losses, and improve voltage profiles.
ENERGY EXPLORATION & EXPLOITATION
(2022)
Article
Computer Science, Information Systems
Nuh Erdogan, Sadik Kucuksari, Umit Cali
Summary: This paper presents a co-simulation of optimal EVSE and techno-economic system design models to investigate the behaviors of various EVSE configurations. The study shows that investing in grid-tied renewable energy technologies can lower charging costs and DCFC EVSEs are more sensitive to fleet size.
Article
Thermodynamics
Emrah Dokur, Nuh Erdogan, Mahdi Ebrahimi Salari, Cihan Karakuzu, Jimmy Murphy
Summary: This study proposes a novel hybrid offshore wind forecasting model combining SWD and Meta-ELM, which outperforms conventional models in comparative experiments and can enhance the performance of the Meta-ELM model.
Article
Green & Sustainable Science & Technology
Brian P. Hand, Nuh Erdogan, Donal Murray, Patrick Cronin, John Doran, Jimmy Murphy
Summary: The research showed that shaft misalignment has an impact on rotary seals, resulting in increased temperature and wear. Therefore, it is necessary to strengthen the testing of mechanical components of tidal turbines.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Thermodynamics
Nuh Erdogan, Sadik Kucuksari, Jimmy Murphy
Summary: This study proposes a multi-objective optimization model to determine the optimal charging infrastructure for a transition to plug-in electric vehicles (PEVs) at workplaces. The model considers all cost aspects of a workplace charging station and incorporates smart charging strategies and a charging behavior model. Through testing and sensitivity analysis, it is shown that the proposed model can achieve significant cost savings compared to single-objective optimal models and current charging practices.
Article
Computer Science, Information Systems
Alpaslan Demirci, Said Mirza Tercan, Umit Cali, Ismail Nakir
Summary: This article provides a framework for systematically evaluating EV driving and charging behaviors, improving charge management, and analyzing driving habits to provide a consistent and usable dataset. The potential of V2G is explored through evaluating individual and simultaneous charging demand characteristics. Managerial recommendations for EV charging management are offered, and the study emphasizes the importance of daily travel habits in defining charging demands.
Article
Computer Science, Artificial Intelligence
Huseyin Parmaksiz, Ugur Yuzgec, Emrah Dokur, Nuh Erdogan
Summary: This paper proposes a mutation-based Dragonfly optimization algorithm (MIDA) to improve the accuracy of the original Dragonfly algorithm (DA). Experimental results show that MIDA outperforms DA in terms of solution quality and search performance in CEC2014 and CEC2020 benchmarks. It also demonstrates better statistical performance and computational efficiency compared to other optimization algorithms.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Energy & Fuels
Muhammet Deveci, Nuh Erdogan, Dragan Pamucar, Sadik Kucuksari, Umit Cali
Summary: As the transition to electric mobility accelerates, the expansion of charging infrastructure, known as electric vehicle supply equipment (EVSE), is crucial for promoting the transition and alleviating charger access anxiety among electric vehicle (EV) users. This study introduces a multi-criteria decision-making (MCDM) framework that combines a new MCDM model with an optimal public charging station model to determine the best performing public EVSE type from multiple EV user perspectives. The proposed model is tested using real charging data and user evaluations, and it identifies DCFC EVSE as the best performing option.
Article
Computer Science, Information Systems
Sadik Kucuksari, Dragan Pamucar, Muhammet Deveci, Nuh Erdogan, Dursun Delen
Summary: This study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. The model employs an aggregated rough linguistic matrix and incorporates nonlinear aggregation functions to address uncertainties and accommodate decision makers' risk attitudes. A large-scale post-EV test drive survey is conducted to validate the model's efficacy, and sensitivity analysis confirms its robustness. The results highlight the importance of the reliability criterion and the dominance of vehicle-related characteristics in the decision-making process.
INFORMATION SCIENCES
(2023)
Article
Multidisciplinary Sciences
Salih Sarp, Ferhat Ozgur Catak, Murat Kuzlu, Umit Cali, Huseyin Kusetogullari, Yanxiao Zhao, Gungor Ates, Ozgur Guler
Summary: COVID-19 pandemic has caused severe challenges and increased the demand for chest X-ray scans. This paper proposes a model that uses Explainable Artificial Intelligence to detect and interpret COVID-19 positive CXR images, analyzing their impact using heatmaps.
Article
Energy & Fuels
Berhane Darsene Dimd, Steve Voller, Ole-Morten Midtgard, Umit Cali, Alexis Sevault
Summary: Building integrated photovoltaics (BIPVs) are popular in urban areas for their ability to provide zero-emission energy in buildings. However, designing a PV output power forecasting model for BIPVs can be complex due to multiple generation peaks. This article quantifies the impact of mixed orientations on the accuracy of a PV output prediction model and finds that mixed orientations result in a notable increase in forecast error.
IEEE JOURNAL OF PHOTOVOLTAICS
(2023)
Proceedings Paper
Engineering, Aerospace
Sadik Kucuksari, Nuh Erdogan
Summary: Electric vehicle fleets play a significant role in the transition to electric mobility. This study develops a charging behavior model based on real fleet data to predict the charging demand of any number of fleet vehicles. By using Gaussian Mixture Models and Kernel distribution, the limitations of traditional models are overcome, and the best fit behavior patterns are determined based on goodness-of-fit comparison.
2022 IEEE/AIAA TRANSPORTATION ELECTRIFICATION CONFERENCE AND ELECTRIC AIRCRAFT TECHNOLOGIES SYMPOSIUM (ITEC+EATS 2022)
(2022)
Article
Computer Science, Information Systems
Emrah Dokur, Nuh Erdogan, Sadik Kucuksari
Summary: This paper presents a hybrid forecasting model for predicting the charging load of electric vehicle (EV) fleets. The model incorporates Swarm Decomposition (SWD) and Complete Ensemble Empirical Mode Decomposition Adaptive Noise (CEEMDAN) methods to decompose the original signals and then utilizes artificial intelligence-based forecasting models. The performance of the proposed model is validated using real EV fleet charging data sets and compared to other models. The results show that the multiple decomposition approach improves the model performance.
