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Article Citation - WoS: 20Citation - Scopus: 23A New Generalized Δ-Shock Model and Its Application To 1-out-of-(m+1):g Cold Standby System(Elsevier Sci Ltd, 2023) Eryilmaz, Serkan; Unlu, Kamil DemirberkAccording to the classical delta-shock model, the system failure occurs upon the occurrence of a new shock that arrives in a time length less than delta, a given positive value. In this paper, a new generalized version of the delta-shock model is introduced. Under the proposed model, the system fails if there are m shocks that arrive in a time length less than delta after a previous shock, m >= 1. The mean time to failure of the system is approximated for both discretely and continuously distributed intershock time distributions. The usefulness of the model is also shown to study 1-out-of-(m + 1):G cold standby system. Illustrative numerical results are presented for geometric, exponential, discrete and continuous phase-type intershock time distributions.Article Citation - WoS: 23Citation - Scopus: 26A Univariate Time Series Methodology Based on Sequence-To Learning for Short To Midterm Wind Power Production(Pergamon-elsevier Science Ltd, 2022) Akbal, Yildirim; Unlu, Kamil DemirberkThe biggest wind farm of Turkey is placed at Manisa which is located in the Aegean Region. Electricity is a nonstorable commodity for that reason, it is very important to have a strong forecast and model of the potential electricity production to plan the electricity loads. In this study, the aim is to model and forecast electricity production of the wind farms located at Manisa by using a univariate model based on sequence-to-sequence learning. The forecasting range of the study is from short term to midterm. The strength of the proposed model is that; it only needs its own lagged value to make forecasts. The empirical evidences show that the model has high coefficient of variation (R-2) in short term and moderate R-2 in the midterm forecast. Although in the midrange forecasts R-2 slightly decreases mean squared error and mean absolute error shows that the model is accurate also in the midterm forecasts. The proposed model is not only strong in hourly electricity production forecasts but with a slight modification also in forecasting the minimum, maximum and average electricity production for a fixed range. This study concludes with two fresh and intriguing future research ideas.Article Citation - WoS: 5Citation - Scopus: 6Strategic Electricity Production Planning of Turkey Via Mixed Integer Programming Based on Time Series Forecasting(Mdpi, 2023) Yoruk, Gokay; Bac, Ugur; Yerlikaya-Ozkurt, Fatma; Unlu, Kamil DemirberkThis study examines Turkey's energy planning in terms of strategic planning, energy policy, electricity production planning, technology selection, and environmental policies. A mixed integer optimization model is proposed for strategic electricity planning in Turkey. A set of energy resources is considered simultaneously in this research, and in addition to cost minimization, different strategic level policies, such as CO2 emission reduction policies, energy resource import/export restriction policies, and renewable energy promotion policies, are also considered. To forecast electricity demand over the planning horizon, a variety of forecasting techniques, including regression methods, exponential smoothing, Winter's method, and Autoregressive Integrated Moving Average methods, are used, and the best method is chosen using various error measures. The optimization model constructed for Turkey's Strategic Electricity Planning is obtained for two different planning intervals. The findings indicate that the use of renewable energy generation options, such as solar, wind, and hydroelectric alternatives, will increase significantly, while the use of fossil fuels in energy generation will decrease sharply. The findings of this study suggest a gradual increase in investments in renewable energy-based electricity production strategies are required to eventually replace fossil fuel alternatives. This change not only reduces investment, operation, and maintenance costs, but also reduces emissions in the long term.
