WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 4Citation - Scopus: 5A Smart Building Energy Management Incorporating Clustering-Based Tariffs in the Presence of Domestic Solar Energy, Battery, and Electric Vehicle(Pergamon-elsevier Science Ltd, 2024) Mohammadpourfard, Mousa; Mohammadi-ivatloo, Behnam; Mohammadpourfard, Mousa; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologySmart buildings play a crucial role in optimizing energy management within the power network. As end-users of the power network, they have the ability to not only reduce economic costs for householders but also modify the technical indices of the power network. To promote efficient device management in smart homes (SH), demand response programs are recommended for consumers. This research investigates the application of clusteringbased electricity pricing strategy aimed at effectively managing the energy devices of a residential smart home. The utilized method categorizes the electricity tariff into five rates according to the clustering of the realtime pricing program. Ward's clustering method is utilized to cluster and determine new electricity tariffs. The primary goal of the energy management program is to minimize the building's energy cost, which is accomplished through the utilization of the multi-verse optimizer. The smart home consists of essential and manageable appliances, a photovoltaic panel (PV), a sodium-sulfur (NaS) battery, and an electric vehicle (EV). The initial parameters of the PV and EV are modeled stochastically by their probability distribution functions and calculated using the Latin hypercube sampling algorithm. The smart building's performance is assessed by taking into account various demand response programs. The numerical results present that the application of the clusteringbased management method has resulted in a significant reduction of 23-43 % in the electricity cost of smart homes. Additionally, the smart home exhibits a more linear consumption pattern when considering the electricity tariffs based on the clustering approach.Article Citation - WoS: 17Citation - Scopus: 24A Gis-Based Fahp and Fedas Analysis Framework for Suitable Site Selection of a Hybrid Offshore Wind and Solar Power Plant(Elsevier B.V., 2023) Karipoğlu, Fatih; Karipoğlu, Fatih; Ozturk, S.; Efe, B.; 03.06. Department of Energy Systems Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyThis study presents a Geographic Information System (GIS) based suitable site selection methodology for a hybrid system that includes offshore wind and solar PV. The methodology utilizes open source databases about decision criteria and applies this data using GIS to determine suitable sites for offshore wind and solar PV systems. For the assessment of multi-criteria which affect the potential hybrid energy power plants and the determination of the best suitable areas, Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Evaluation based on Distance Average Solution (FEDAS) are used in the study. Results show that technical criteria has the priority weight of 0.60 while the weight of social criteria is about 0.07. Among sub-criteria, the wind speed has the highest priority weight while distance to port and visibility are the highest criteria of priority weight under economic and social main criteria, respectively. Among the alternatives, Area 2 (A-2) is determined as the best alternative for hybrid offshore power plants in the study area. This proposed methodology can be utilized by decision-makers to determine the best suitable locations for hybrid offshore wind and solar PV systems at any location. This paper suggests a new approach integrating GIS, fuzzy setbased AHP and EDAS as a novelty. © 2023 International Energy Initiative