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Wimax teknolojisi fiziksel katman parametrelerinin performansa etkisinin Matlab kullanılarak incelenmesi
Sabit kablosuz geniş bant erişim son kullanıcı için yüksek hızda ses, video ve veri transferi sunan bir teknolojidir. İlk başta standart belirlenmemiştir. IEEE 802.16 WirelessMAN standartları geniş frekans aralıkların da sabit ve kablosuz geniş bant erişimi sunan MAC katmanı ve fiziksel katmanı belirlemektedir. WiMAX forum çoklu yol ortamlarında güçlü performanstan dolayı donanım üreticileri için IEEE 802.16 OFDM fiziksel katmanı kabul eder. Bu tezde Wimax ürünleri için standart belirlemede öneli yeri olan fiziksel katmanın uygulaması yapılmış ve performansları karşılaştırılmıştır. Kablosuz ortamlarda Stanford University tarafından belirlenen SUI kanal modelleri kullanılmıştır. Simülasyon Matlab ortamında gerçekleştirilmiştir.
İnsan ve makine arasında etkisel görsel-dokunsal iletişim için müzakere modeli
Humans communicate with each other through a number of affective cues. The recognition as well as synthesis of these affective cues using machines have been the interest of the affective computing community. In this paper, we show how haptic and audio-visual cues can be used to display negotiation related affective states. We show that the addition of haptic cues provides a statistically significant increase in the human-recognition of the machine-displayed affective cues. We also show that, as in game theory, certain negotiation strategies such as tit-for-tat generate maximum combined utility for the negotiating parties while providing an excellent balance between the work done by the user and the joint utility.
Akıllı mikro-şebekelerde kontrol stratejilerinin geliştirilmesi
This thesis concerns the transformation of aged power systems to modern power systems that include microgrids with renewable energy sources and energy storage systems. The integration of renewable energy sources brings excellent opportunities to provide better reliability and efficiency. However, the uncertainty and intermittent nature of renewable energy sources may potentially degrade the stability and quality of the electrical grid. Therefore, the aim of this dissertation is to maintain the supply-demand balance in microgrids while minimizing the cost in real time operation. A microgrid energy management system that can optimize the dispatch of the controllable distributed energy resources in grid-connected mode of a pilot microgrid on a university campus in Malta was developed to achieve this goal. Three different methods were used in this study: mixed integer linear programming (MILP), MILP based rolling horizon control and Q-learning, Designing intelligent method for the real-time energy management of the stochastic and dynamic microgrid is the primary goal of this research. Moreover, the detailed mathematical models of the network model and of the technical model are considered for the economic and environmental operation of the microgrid system to solve the optimization problem under more real-world conditions. The objective is to minimize the total daily operation costs, which include the degradation cost of batteries, the cost of energy bought from the main grid, the fuel cost of the diesel generator, and the emission cost. The optimization problem is modeled as a finite Markov decision process (MDP) by combining network and technical constraints, and a Q-learning algorithm is adopted to solve the sequential decision subproblems. The proposed algorithm decomposes a multi-stage mixed-integer nonlinear programming (MINLP) problem into a series of single-stage problems so that each subproblem can be solved using Bellman's equation. To prove the effectiveness of the proposed algorithm, three different case studies are taken into consideration. A predictive control framework is also proposed to provide optimal operation with minimum cost. This method allows the consideration of operational cost values, demand with uncertainty, generation units' profiles with uncertainty, and constraints related to the network model and technical model. The stochastic and deterministic cases are conducted to validate the efficiency of the approach.