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Coordination of Directional Over Current Relays (DOCR) is an important issue in the protection of power systems. In this paper, DOCR coordination, which has the problem of nonlinear and high constraints, is discussed The object function, reported in the literature, has been re-written by adding relay setting constraints multiplied by a weight factor to ensure optimum coordination of DOCRs. At first, the Evaporation Rate Controlled Water Cycle Algorithm (ER-WCA) and Harris Hawk Optimization (HHO) algorithms were used to compute the optimum coordination of the DOCR problem. The proposed algorithms are applied to the 9-bus test system. In addition, the results obtained using ER-WCA and HHO were compared with those obtained using other algorithms in the literature. Then, a new adaptive protection method, which adapts to changing power system conditions in power grids with Distributed Generation (DG) system, is proposed. In this new adaptive protection method, the HHO algorithm has been used to ensure optimum coordination of DOCRs. Also, in this new adaptive protection method, a structure with Fault Current Limiting (FCL) mechanism, which determines the critical fault point based on the both of the current and voltage index, is proposed in power systems. Then, by applying this new adaptive protection method to 10 bus Turkey distribution system, the effectiveness of the study was discussed. [ABSTRACT FROM AUTHOR]

The Global Multidimensional Poverty Index (MPI), included in the annual report published by the United Nations (UN) and the Oxford Poverty and Human Development Initiative (OPHI), is an international measure of multidimensional poverty that covers many developing countries. The MPI is a measure of poverty that can be adapted to the conditions of each country and basically includes the dimensions of health, education and living conditions, but also supports different dimensions. In this study; between the years 2010-2018, requested from Turkey Statistical Institute (TSI) 'Income and Living Conditions Survey' using micro data sets, Multidimensional Poverty Index is designed for Turkey. The aforementioned index calculation was created using the Alkire-Foster method (2011). Additionally, some countries covered in the report issued by the UN and OPHI with Turkey using multidimensional poverty index, it is aimed to be tested with System GMM Estimator to reveal the relationship between multidimensional poverty and economic growth. [ABSTRACT FROM AUTHOR]

The economic dispatch problem (EDP) is a complex, constrained, and nonlinear optimization problem. In the EDP, the active power bus should operate between the minimum and maximum bus limits to minimize the fuel cost. In this study, a fast, efficient, and reliable hybrid gravitational search algorithm-teaching learning based optimization (GSA-TLBO) method was proposed for the purpose of solving the EDP in power systems. The proposed method separates the search space into two sections as global and local searching. In the first part, searching was carried out by GSA method effectively to form the second search space. In the second part, the optimum solution was sought in the local search space by the TLBO method. The proposed method was implemented to a constrained benchmark G01 problem. The proposed hybrid method was then applied to the constrained EDP in IEEE 30-bus and IEEE 57-bus test systems and Turkey's 22-bus power system to minimize the fuel cost. Obtained results were compared with other methods. Experimental results show that the proposed method results in shorter, more reliable, and efficient lowest fuel cost solutions. It has been found that the proposed method can be used to solve constrained optimization problems. [ABSTRACT FROM AUTHOR]

Premise and consequent parameters of ANFIS are optimized by an optimization algorithm in its training process. A successful optimization algorithm should be utilized for an effective training process. In this study, an adaptive and hybrid artificial bee colony (aABC) algorithm, which is one of the variants of ABC algorithm, is employed in ANFIS training. aABC algorithm uses arithmetic crossover and adaptive neighborhood radius in the solution generating mechanism. aABC algorithm has gained the ability to obtain fast convergence and quality solution with these two control parameters. ANFIS is trained using aABC algorithm to obtain better solutions according to standard ABC algorithm. Firstly, five nonlinear static test systems are utilized for performance analysis of aABC algorithm. With aABC algorithm, performance increases up to about 16% compared to standard ABC algorithm. At the same time, better convergence is obtained in all examples. Wilcoxon signed rank test is applied to determine significance of the results. In addition, the results reached by aABC algorithm are compared with GA, PSO, HS algorithms and more effective results are found with aABC algorithm. As a result, it is seen that aABC algorithm is more successful than ABC, GA, PSO and HS in ANFIS training for identification of nonlinear static systems. Secondly, ANFIS is also trained by utilizing aABC algorithm for solving a real-world problem. Estimating number of foreign visitors coming to Turkey is selected as a real-world problem. The results obtained are compared standard with standard ABC algorithm, and more successful results are found by aABC algorithm. [ABSTRACT FROM AUTHOR]

The control strategy insures the efficiency, increased production and safety in new and complicated energy conversion systems. To this end, a thermodynamic model that simulates a real geothermal power plant is developed, and a new and optimal control strategy to increase exergy efficiency is presented on this model. In this study, real average daily data obtained during 2016 are used to verify the thermodynamic model of Sinem geothermal power plant in Turkey (S-GPP) and its control strategy. Thus, exergy efficiency of the system is maximized even under different and changed conditions by controlling flow rate, pressure and NCG percent content parameters in certain locations of S-GPP. Consequently, a new control strategy based on PID is developed. At the same time, different working conditions are provided by assigning disruptive values to these parameters. The thermodynamic model of S-GPP is used as a test system to demonstrate the efficiency of the proposed control strategy under various operating conditions. The results of the study prove that the model has a good statistical performance in terms of maximum exergy efficiency values. In addition, the proposed PID controller has a better performance compared to manual control, even in the presence of S-GPP. The effectiveness of the proposed control strategy is demonstrated by this case study, in which exergy efficiency of the system increased by 25% and power generation by 23%. Therefore, the proposed control strategy has the potential to create more reliable and controlled systems for geothermal and other power plants. • A thermodynamic model has been developed that can simulate an existing operating GPP in real time. • An exergy-based PID control strategy is used for the first time in the GPP under various operating conditions. • Maximum exergy efficiency of the GPP is ensured with control of flow rate, pressure and percent content. • The strategy has better control performance compared to the uncontrolled one in the GPP. • With the proposed strategy, its exergy efficiency and power rate can be increased by 25% and 23%, respectively. [ABSTRACT FROM AUTHOR]

• Phytochemistry and biological activity of Onosma sieheana and O. stenoloba were studied. • Onosma sieheana exhibited higher antioxidant and α-amylase inhibitory activity than the other. • Tyrosinase inhibitory activity test resulted in the superiority of O. stenoloba. • The binding energies of most of the main components to enzymes was quite high. There are convincing evidences that species belonging to the Onosma genus have been used in the treatment of various diseases for centuries. In this study, antioxidant and tyrosinase and α-amylase inhibitory activities of the methanol (MeOH) extracts of two endemic Onosma species (O. sieheana Hayek and O. stenoloba Hausskn. ex Riedl), which are endemic to the flora of Turkey, were compared. Phosphomolybdenum, reducing power [Cupric reducing antioxidant capacity (CUPRAC) and ferric reducing antioxidant power (FRAP)], radical scavenging [on '2,2-diphenyl-1-picrylhydrazyl' (DPPH) and 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS)] and ferrous ion chelating assays were used to determine the antioxidant activities of the extracts. All test systems except for the ferrous ion chelating assay resulted in O. sieheana 's superiority. The antioxidant activity of O. sieheana in the test systems mentioned above was found to be 2.11, 1.57, 1.01, 3.54 and 3.19 mg/mL, respectively. However, in ferrous ion chelating activity assay, O. stenoloba showed higher activity with an IC 50 value of 2.98 mg/mL. In the tyrosinase inhibitor activity test, O. stenoloba extract showed higher activity (1.89 mg/mL), while in the α-amylase inhibitory activity assay, O. sieheana was found to be more effective (3.02 mg/mL). As a result of total phenolic and flavonoid compound analysis, O. sieheana was found to be richer than the other in terms of both groups. LC–ESI–MS/MS analysis revealed that rosmarinic acid, apigenin 7-glucoside, luteolin 7-glucoside, chlorogenic acid, hesperidin, pinoresinol, hyperoside and 4-hydroxybenzoic are the main compounds of the extracts. According to the results of docking analysis performed to reveal the interactions of the main components with tyrosinase, it is thought that pinoresinol, hesperidin, luteolin 7-glucoside, apigenin 7-glucoside, and hyperoside may be phytochemicals responsible for the inhibitory activity. Additionally, the binding energies of pinorecinol, apigenin 7-glucoside, luteolin 7-glucoside, hyperoside, chlorogenic acid, and rosmarinic acid to α-amylase were found to be quite high. [ABSTRACT FROM AUTHOR]