Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Citation - Scopus: 40
    Determination of the Most Appropriate Site Selection of Wind Power Plants Based Geographic Information System and Multi-Criteria Decision-Making Approach in Develi, Turkey
    (Aalborg University Press, 2021) Karipoğlu, Fatih; Genç, Mustafa Serdar; Koca, Kemal
    Wind power has major benefits including providing for an increasing energy demand while tackling climate change problems. Detailed planning processes such as technical, social, environmental, various agents, and political concerns are essential for the development of wind energy projects. The objective of the present study is to develop a visualization that combines Geographic Information System (GIS) and Multi-Criteria Decision Making (MCDM) and implementation for Kayseri, Develi in Turkey as a case study. For the analyzes, CORINE CLC 2000 and other data sources were employed for data acquisition to unlock fragmented and hidden onshore data resources and to facilitate investment in sustainable coastal and inland activities. Several factors were determined in the wind power plant installations such as wind potential, roads, water sources, and these factors were analyzed based on their buffer zones. After detailed analyses, sites near the Havadan (7.87 MW) and Kulpak (9.22 MW) villages were found to be the most suitable locations for the installation of a potential onshore wind farm. The method suggested in this study can be used to analyze the suitability of any region at the regional level for onshore wind power plant and the results of the study can be used to develop based on public perception, renewable energy policies, energy political rules. © 2021, Aalborg University press. All rights reserved.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 7
    Inertia Dependent Droop Based Frequency Containment Process
    (MDPI Multidisciplinary Digital Publishing Institute, 2019) Das, Kaushik; Altın, Müfit; Hansen, Anca D.; Sorensen, Poul E.
    Presently, there is a large need for a better understanding and extensive quantification of grid stability for different grid conditions and controller settings. This article therefore proposes and develops a novel mathematical model to study and perform sensitivity studies for the capabilities of different technologies to provide Frequency Containment Process (FCP) in different grid conditions. A detailed mathematical analytical approach for designing inertia-dependent droop-based FCP is developed and presented in this article. Impacts of different droop settings for generation technologies operating with different inertia of power system can be analyzed through this mathematical approach resulting in proper design of droop settings. In contrast to the simulation-based model, the proposed novel mathematical model allows mathematical quantification of frequency characteristics such as nadir, settling time, ROCOF, time to reach the nadir with respect to controller parameters such as gain, droop, or system parameters such as inertia, volume, of imbalance. Comparative studies between cases of frequency containment reserves (FCR) provision from conventional generators and wind turbines (WTs) are performed. Observations from these simulations are analyzed and explained with the help of an analytical approach which provides the feasible range of droop settings for different values of system inertia. The proposed mathematical approach is validated on simulated Continental Europe (CE) network. The results show that the proposed methodology can be used to design the droop for different technology providing FCP in a power system operating within a certain range of inertia.
  • Article
    Citation - WoS: 103
    Citation - Scopus: 122
    One-Day Ahead Wind Speed/Power Prediction Based on Polynomial Autoregressive Model
    (Institution of Engineering and Technology, 2017) Karakuş, Oktay; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa Aziz
    Wind has been one of the popular renewable energy generation methods in the last decades. Foreknowledge of power to be generated from wind is crucial especially for planning and storing the power. It is evident in various experimental data that wind speed time series has non-linear characteristics. It has been reported in the literature that nonlinear prediction methods such as artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) perform better than linear autoregressive (AR) and AR moving average models. Polynomial AR (PAR) models, despite being non-linear, are simpler to implement when compared with other non-linear AR models due to their linear-in-the-parameters property. In this study, a PAR model is used for one-day ahead wind speed prediction by using the past hourly average wind speed measurements of Ceşme and Bandon and performance comparison studies between PAR and ANN-ANFIS models are performed. In addition, wind power data which was published for Global Energy Forecasting Competition 2012 has been used to make power predictions. Despite having lower number of model parameters, PAR models outperform all other models for both of the locations in speed predictions as well as in power predictions when the prediction horizon is longer than 12 h.