A
Akin Tascikaraoglu
Researcher at Muğla University
Publications - 57
Citations - 2004
Akin Tascikaraoglu is an academic researcher from Muğla University. The author has contributed to research in topics: Demand response & Electric power system. The author has an hindex of 19, co-authored 49 publications receiving 1498 citations. Previous affiliations of Akin Tascikaraoglu include Yıldız Technical University & University of California, Berkeley.
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A review of combined approaches for prediction of short-term wind speed and power
TL;DR: In this article, a comprehensive research about the combined models is called on for how these models are constructed and affect the forecasting performance, and an up-to-date annotated bibliography of the wind forecasting literature is presented.
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A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey
TL;DR: In this article, the authors investigated an experimental smart home with various renewable energy sources and storage systems in terms of several aspects such as in-home energy management, appliances control and power flow.
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Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform
TL;DR: A novel wind speed forecasting method which first utilizes Wavelet Transform for decomposition of the wind speed data into more stationary components and then uses a spatio-temporal model on each sub-series for incorporating both temporal and spatial information.
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End-User Comfort Oriented Day-Ahead Planning for Responsive Residential HVAC Demand Aggregation Considering Weather Forecasts
TL;DR: The proposed approach manipulates the temperature set-point of HVAC thermostats aiming to minimize the average discomfort among end-users enrolled in a DR program, while satisfying the DR event related requirements of the load serving entity.
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Comprehensive Optimization Model for Sizing and Siting of DG Units, EV Charging Stations, and Energy Storage Systems
Ozan Erdinc,Akin Tascikaraoglu,Nikolaos G. Paterakis,Ilker Dursun,Murat Can Sinim,Joao P. S. Catalao +5 more
TL;DR: The proposed optimization model is formulated as a second order conic programming problem, considering also the time-varying nature of DG generation and load consumption, in contrast with the majority of the relevant studies that have been based on static values.