Yazar "Yesilbudak, Mehmet" seçeneğine göre listele

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    Multi-time series and-time scale modeling for wind speed and wind power forecasting part I: Statistical methods, very short-term and short-term applications
    (Institute of Electrical and Electronics Engineers Inc., 2015) Colak, Ilhami; Sagiroglu, Seref; Yesilbudak, Mehmet; Kabalci, Ersan; Ibrahim Bulbul, H.
    This study concentrates on multi-time series and-time scale modeling in wind speed and wind power forecasting. Different statistical models along with different time horizons are analyzed and evaluated broadly and comprehensively. For this reason, the entire study is divided into two main scientific parts. In case of making a general overview of the entire study, moving average (MA), weighted moving average (WMA), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) methods are employed for multi-time series modeling. Very short-term, short-term, medium-term and long-term scales are utilized for multi-time scale modeling. Specifically, in this part of the entire study, the mentioned statistical models are presented in detail and 10-min and 1-h time series forecasting models are created for the purpose of achieving 10-min and 2-h ahead forecasting, respectively. Many useful outcomes are accomplished for very short-term and short-term wind speed and wind power forecasting. © 2015 IEEE.
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    Multi-time series and-time scale modeling for wind speed and wind power forecasting part II: Medium-term and long-term applications
    (Institute of Electrical and Electronics Engineers Inc., 2015) Colak, Ilhami; Sagiroglu, Seref; Yesilbudak, Mehmet; Kabalci, Ersan; Ibrahim Bulbul, H.
    This paper represents the second part of an entire study which focuses on multi-time series and-time scale modeling in wind speed and wind power forecasting. In the first part of the entire study [1], firstly, moving average (MA), weighted moving average (WMA), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models are introduced in-depth. Afterwards, the mentioned models are analyzed for very short-term and short-term forecasting scales, comprehensively. In this second part of the entire study, we address the medium-term and long-term prediction performance of MA, WMA, ARMA and ARIMA models in wind speed and wind power forecasting. Particularly, 3-h and 6-h time series forecasting models are constructed in order to carry out 9-h and 24-h ahead forecasting, respectively. Many valuable assessments are made for the employed statistical models in terms of medium-term and long-terms forecasting scales. Finally, many valuable achievements are discussed considering a detailed comparison chart of the entire study. © 2015 IEEE.
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    A novel intelligent approach for yaw position forecasting in wind energy systems
    (Elsevier Sci Ltd, 2015) Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami
    Yaw control systems orientate the rotor of a wind turbine into the wind direction, optimize the wind power generated by wind turbines and alleviate the mechanical stresses on a wind turbine. Regarding the advantages of yaw control systems, a k-nearest neighbor classifier (k-NN) has been developed in order to forecast the yaw position parameter at 10-min intervals in this study. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters are used in 2, 3, 4, 5 and 6-dimensional input spaces. The forecasting model using Manhattan distance metric for k= 3 uncovered the roost accurate performance for atmosphere pressure, wind direction, wind speed and rotor speed inputs. However, the forecasting model using Euclidean distance metric for k= 1 brought out the most inconsistent results for atmosphere pressure and wind speed inputs. As a result of multi-tupled analyses, many feasible inferences were achieved for yaw position control systems. In addition, the yaw position forecasting model developed was compared with the persistence model and it surpassed the persistence model significantly in terms of the improvement percent. (C) 2015 Elsevier Ltd. All rights reserved.
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    Smart grid projects in Europe: Current status, maturity and future scenarios
    (Elsevier Sci Ltd, 2015) Colak, Ilhami; Fulli, Gianluca; Sagiroglu, Seref; Yesilbudak, Mehmet; Covrig, Catalin-Felix
    The attention on the smart grids and smart grid technologies has grown significantly over the last few years. The analysis made in this study is grounded on the smart grid projects database of the Joint Research Centre (European Commission). The European smart grid projects are analyzed among others in terms of: number, countries, duration and collaboration. Additionally, an analysis is done regarding the annual number of starting and concluded/planned to be concluded projects, the total number of participants per year, the distribution of smart grid applications per stage of development, year and EU country and an overview of the investments in the European smart grid projects is provided. Afterwards a forecast is done regarding the number of projects. As a result of graphical and predictive analyses, many essential inferences are achieved related to the current status and the anticipated short-term trends of smart grid projects. (C) 2015 Elsevier Ltd. All rights reserved.
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    A survey on the critical issues in smart grid technologies
    (Pergamon-Elsevier Science Ltd, 2016) Colak, Ilhami; Sagiroglu, Seref; Fulli, Gianluca; Yesilbudak, Mehmet; Covrig, Catalin-Felix
    The hierarchical and the centrally-controlled grid topology of existing electrical power systems has remained unchanged over the 20th century. On the other hand, there is a rapid increase in the cost of fossil fuels coupled with the inability of utility companies to expand their generation capacity in line with the rising electricity demand, without modernizing the grid. For these reasons, it is needed to modernize the existing power grids and consequently smart power grids have emerged. Unlike the benefits and features ensured by smart grids, this paper provides a detailed survey of the critical challenges in smart grids in terms of information and communication technologies, sensing, measurement, control and automation technologies, power electronics and energy storage technologies. It is expected that this paper will lead to the better understanding of potential constraints in smart grid technologies. (c) 2015 Elsevier Ltd. All rights reserved.