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Article Citation - WoS: 8Citation - Scopus: 10Computing Reliability Indices of a Wind Power System Via Markov Chain Modelling of Wind Speed(Sage Publications Ltd, 2024) Eryilmaz, Serkan; Bulanik, Irem; Devrim, YilserStatistical modelling of wind speed is of great importance in the evaluation of wind farm performance and power production. Various models have been proposed in the literature depending on the corresponding time scale. For hourly observed wind speed data, the dependence among successive wind speed values is inevitable. Such a dependence has been well modelled by Markov chains. In this paper, the use of Markov chains for modelling wind speed data is discussed in the context of the previously proposed likelihood ratio test. The main steps for Markov chain based modelling methodology of wind speed are presented and the limiting distribution of the Markov chain is utilized to compute wind speed probabilities. The computational formulas for reliability indices of a wind farm consisting of a specified number of wind turbines are presented through the limiting distribution of a Markov chain. A case study that is based on real data set is also presented.Article Citation - WoS: 13Citation - Scopus: 16An Analytic Network Process Based Risk Assessment Model for Ppp Hydropower Investments(Vilnius Gediminas Tech Univ, 2021) Akcay, Emre CanerThe number of public-private partnership (PPP) projects has gone up especially in developing countries. The risk assessment of PPP projects is essential in ensuring project success. The objective of this study is to develop an Analytic Network Process (ANP) based risk assessment model for hydropower investments, and a tool to facilitate quantification of risk ratings based on this model. The results show that the three most important risk factors that affect the overall risk rating of a PPP hydropower investment are legal risks, contractor/subcontractor risks, and operator risks. In addition, the three most important risk clusters were identified as stakeholders, government requirements, and resources, whereas market was the least important cluster. The tool that measures the risk rating of a PPP of hydropower project was tested on ten real cases, and satisfactory results were obtained in terms of its predictive capability. The contributions of this research include (1) identification of the risk factors and clusters of factors associated with PPP hydropower investments; (2) determination of the priority of each risk factor and cluster; (3) development a tool that guides the investors through the risk assessment of PPP hydropower investments.Article Citation - WoS: 16Citation - Scopus: 17Pei Modifiednatural Sands of Florida as Catalysts for Hydrogen Production From Sodium Borohydride Dehydrogenation in Methanol(Wiley-hindawi, 2021) Inger, Erk; Demirci, Sahin; Can, Mehmet; Sunol, Aydin K.; Philippidis, George; Sahiner, NurettinSand samples from Tampa (T) and Panama (P) City beaches in Florida were used as catalysts for dehydrogenation of NaBH4 in methanol. T and P sand samples were sieved to <250, 250 to 500, and >500 mu m sizes, and the smallest fractions resulted in faster hydrogen generation rates (HGR), 565 +/- 18 and 482 +/- 24 mL H-2 (min.g of catalyst)(-1), respectively. After various base/acid treatments, HGR values of 705 +/- 51 and 690 +/- 47 mL H-2 (min g of catalyst)(-1) for HCl-treated T and P sand samples were attained, respectively. Next, T and P sand samples were modified with polyethyleneimine (PEI) that doubled the HGR values, 1344 +/- 103, and 1190 +/- 87 mL H-2 (min.g of catalyst)(-1) and increased similar to 8-fold, 4408 +/- 187, and 3879 +/- 169 mL H-2 (min g of catalyst)(-1), correspondingly after protonation (PEI+). The Ea values of T and P sand samples were calculated as 24.6 and 25.9 kJ/mol, and increased to 36.1, and 36.6 kJ/mol for T-PEI(+)and P-PEI(+)samples, respectively.Article Citation - WoS: 14Citation - Scopus: 16Bioethanol Production and Potential of Turkey(Gazi Univ, Fac Engineering Architecture, 2011) Melikoglu, Mehmet; Albostan, Ayhan; Energy Systems EngineeringThe ever increasing demand in global energy consumption makes it inevitable for the development of new energy resources. Turkey imports nearly all of its petroleum and this causes major economical problems. In Turkey, a major cereal producer, production of energy crops will decrease the dependence of petroleum and greenhouse gas emissions. In this context, bioethanol production in Turkey becomes a major alternative to petroleum. According to the results find in this study, with the current agricultural output, none of the crops can be adequate for bioethanol production even 100% of crop harvests were utilized. However, with 4% and 7% of current wheat harvest bioethanol required for the production of E5 and E10 can be achieved. In addition, by utilizing the unused land available for agriculture and planting potato, sugar beet, and wheat (each 100%), 5.8, 8.7 and 13.7 billion litres of bioethanol can be produced and this production will be more than enough to supply Turkey's current demand for gasoline.Article Citation - WoS: 4Citation - Scopus: 6Statistics and Probability Theory in Renewable Energy: Teaching and Research(Wiley, 2023) Eryilmaz, Serkan; Kateri, Maria; Devrim, YilserIn this paper, the key-role and utility of statistics and probability theory in the field of renewable energy are emphasized and illustrated via specific examples. It is demonstrated that renewable energy is a very suitable field to effectively teach and implement many statistical and probabilistic concepts and techniques. From a research point of view, statistical and probabilistic methods have been successfully employed in evaluating renewable energy systems. These methods will continue to be of core interest for the renewable energy sector in the future, as new and more complex renewable energy systems are developed and installed. In this context, some future research directions in relation to the evaluation of renewable energy systems are also presented.Article Citation - WoS: 9Citation - Scopus: 9A Hybrid Deep Learning Methodology for Wind Power Forecasting Based on Attention(Taylor & Francis inc, 2024) Akbal, Yildirim; Unlu, Kamil DemirberkWind energy, as a sustainable energy source, poses challenges in terms of storage. Therefore, careful planning is crucial to utilize it efficiently. Deep learning algorithms are gaining popularity for analyzing complex time series data. However, as the "no free lunch" theorem suggests, the trade-off is: they need a lot of data to achieve the benefits. This even brings up a severe challenge for time series analysis, as the availability of historical data is often limited. This study aims to address this issue by proposing a novel shallow deep learning approach for wind power forecasting. The proposed model utilizes a fusion of transformers, convolutional and recurrent neural networks to efficiently handle several time series simultaneously. The empirical evidence demonstrates that the suggested innovative method exhibits exceptional forecasting performance, as indicated by a coefficient of determination (R2) of 0.99. When the forecasting horizon reaches 48, the model's performance declines significantly. However, when dealing with long ranges, utilizing the mean as a metric rather than individual point estimates would yield superior results. Even when forecasting up to 96 hrs in advance, obtaining an R2 value of 0.50 is considered a noteworthy accomplishment in the context of average forecasting.Article Citation - WoS: 7Citation - Scopus: 15Impact Analysis of Renewable Energy Based Generation in West Africa - a Case Study of Nigeria(Politechnika Lubelska, 2021) Adeyemi-Kayode, Temitope M.; Misra, Sanjay; Damasevicius, RobertasThe limited supply of fossil fuels, constant rise in the demand of energy and the importance of reducing greenhouse emissions has brought about the adoption of renewable energy sources for generation of electrical power. In this paper, the impact of renewable energy generation in Nigeria is explored. A review of renewable deposits in Nigeria with a focus on Solar, Biomass, Hydropower, Pumped Storage Hydro and Ocean energy is detailed. The impact of renewable energy-based generation is assessed from three different dimensions: Economic Impact, Social Impact and Environmental Impact. In accessing economic impact; the conditions are employment and job creation, gross domestic product (GDP) growth and increase in local research and development. To analyze the social impact; renewable energy education, renewable energy businesses, ministries and institutes, renewable energy projects and investments as well as specific solar and wind projects across Nigeria were considered. Also, environmental issues were discussed. Similarly, policy imperatives for renewable energy generation in Nigeria was provided. This paper would be useful in accessing the successes Nigeria has experienced so far in the area of sustainable development and the next steps to achieving universal energy for all in Nigeria in 2030.
