Primary energy sources are running out due to the increase in electrical energy consumption. Environmental problems caused by primary energy sources are also increasing. Using more renewable energy resources (RES) can be considered as one of the most powerful solutions to address these problems. Today, required photovoltaic power systems (PVPS) and wind energy systems (WES) are widely used as RES for addressing these problems. Because of their high costs, feasibility studies are required for locating large systems associated with these resources. In this study, various suggestions are determined about location selection, which is an important stage in the PVPS's establishment. Hence, the criteria for selecting the appropriate location are analyzed by the multicriteria decision making (MCDM) methods and the results are evaluated for 5 cities in the Central Anatolian Region of Turkey. In conclusion, it is determined which city is the most suitable place for installation of solar power plants.

Formations or groups of robots become essential in cases where a single robot is insufficient to satisfy a given task. With an increasingly automated world, studies on various topics related to robotics have been carried out in both the industrial and academic arenas. In this paper, the control of the formation of differential mobile robots based on the leader-follower approach is presented. The leader's movement is based on the least cost path obtained by the A-star algorithm, thus ensuring a safe and shortest possible route for the leader. Follower robots track the leader's position in real time. Based on this information and the desired distance and angle values, the leader robot is followed. To ensure that the followers do not collide with each other and with the obstacles in the environment, a controller based on Artificial Potential Fields is designed. Stability analysis using Lyapunov theory is performed on the linearized model of the system. To verify the implemented technique, a simulator was designed using the MATLAB programming language. Seven experiments are conducted under different conditions to show the performance of the approach. The distance and orientation errors are less than 0.1 meters and 0.1 radians, respectively. Overall, mobile robots are able to reach the goal position, maintaining the desired formation, in finite time.

Solar power prediction is an important problem that has gained significant attention in recent years due to the increasing demand for renewable energy sources. In this paper, we present the results of using four different regression models for solar power prediction: linear regression, logistic regression, Lasso regression, and elastic regression. Our results show that all four models are able to accurately predict solar power, but Lasso regression and elastic regression outperform linear and logistic regression in terms of predicting the maximum solar power output. We also discuss the advantages and disadvantages of each model in the context of solar power prediction.

Technology is developing day by day in the world. In addition, developing technologies bring innovations and conveniences to all areas of life. However, ensuring the continuity of these innovations brought by technology reveals different problems. Smart home approach, which increases the quality of human living areas, is one of the most popular working subjects of recent times. In a smart home, built with the Internet of Things technology products, it is very important that the sensors and control devices communicate in a safer way and work in a coordinated manner to ensure the ecosystem's continuity in a safer way. In this study, an IoT based smart home testbed was realized by using MQTT communication protocol which one of the most used IoT communication protocols. With the developed system, the control of the smart home and the operating performance of the system were controlled with the mobile application. The results obtained in the light of the data provided by the test show that the system developed with the MQTT communication protocol can successfully ensure data flow and control in Smart Home applications.

1 Özet -Bu çalışmada, Müsiad'ın Ahiler Ajansı ile ortak yürüttüğü proje kapsamında, Kırıkkale Üniversitesi kampüs alanında bulunan ve rüzgar hızı belirlenen bir bölgenin verileri kullanılarak, bölgenin rüzgar enerjisi potansiyeli analiz edilmiştir. Çalışmada ilk olarak rüzgar enerjisiyle alakalı kavramlar açıklanmış, daha sonra belirlenen rüzgar verisi yardımıyla bölgede kurulabilecek 800 kW'lık anma gücüne sahip Enercon-53 rüzgar türbinin farklı kule yükseklikleri için enerji analizi ve maliyet analizi yapılmıştır. Bu analiz yardımıyla kule yüksekliğinin enerji üretim miktarına, kapasite faktörüne ve yatırımın amorti edilebileceği süreye etkisi incelenmiştir.Anahtar Kelimeler: Rüzgar Enerjisi, Rayleigh, Enerji Analizi, Maliyet Analizi, Kırıkkale.Abstract -In this study, wind energy potential of the campus of Kırıkkale University is analyzed by using wind speed data which is obtained from the project within the scope of Müsiad and Ahiler Development Agency. Firstly, the concepts related to wind energy are explained, then energy and cost analyses are made through wind speed data for different hub heights of Enercon-53 wind turbine which has 800 kW rated power. The effect of hub height to the energy production amount, capacity factor, and repayment period of investment is examined by the means of analyses.