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    A CMOPSO based multi-objective optimization of renewable energy planning: case of Turkey
    (Pergamon-Elsevier Science Ltd, 2020) Deveci, Kaan; Güler, Önder
    In this paper, a two step multi-objective optimization framework of renewable energy planning is proposed for Turkey. In the first step, optimization process is performed and in the second step a multicriteria decision making based selection strategy is applied to select a solution from non-dominated solution set. The objectives are selected as minimization of levelized cost of electricity plan and maximization of short term electricity generation from renewable energy resources. The optimization model considers different cases of renewable energy investment expenditures and the optimal use of resource availability according to renewable energy related targets of the country and estimated cost reduction due to technological learning. For optimization purposes, a state-of-the-art metaheuristic Competitive Multi-Objective Particle Swarm Optimizer (CMOPSO) is used. Results reveal that the 2023 targets of Turkey for hydroelectric, and biomass power plants are not optimal with any of the renewable energy investment case. In addition, solar photovoltaics and onshore wind energy should be the most preferred renewable resources. The findings of this paper can help decision makers not only to set optimized and reliable energy-related goals for Turkey but also to estimate the most suitable time for diffusion of offshore wind energy technology which is not currently under operation. (C) 2020 Elsevier Ltd. All rights reserved.
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    A genetic algorithm based multi-objective optimization of squealer tip geometry in axial flow turbines: A constant tip gap approach
    (2020) Maral, Hıdır; Şenel, Cem Berk; Deveci, Kaan; Alpman, Emre; Kavurmacıoğlu, Levent Ali; Camci, Cengiz
    Tip clearance is a crucial aspect of turbomachines in terms of aerodynamic and thermal performance. A gap between the blade tip surface and the stationary casing must be maintained to allow the relative motion of the blade. The leakage flow through the tip gap measurably reduces turbine performance and causes high thermal loads near the blade tip region. Several studies focused on the tip leakage flow to clarify the flow-physics in the past. The “squealer” design is one of the most common designs to reduce the adverse effects of tip leakage flow. In this paper, a genetic-algorithm-based optimization approach was applied to the conventional squealer tip design to enhance aerothermal performance. A multi-objective optimization method integrated with a meta-model was utilized to determine the optimum squealer geometry. Squealer height and width represent the design parameters which are aimed to be optimized. The objective functions for the genetic-algorithm-based optimization are the total pressure loss coefficient and Nusselt number calculated over the blade tip surface. The initial database is then enlarged iteratively using a coarse-to-fine approach to improve the prediction capability of the meta-models used. The procedure ends once the prediction errors are smaller than a prescribed level. This study indicates that squealer height and width have complex effects on the aerothermal performance, and optimization study allows to determine the optimum squealer dimensions.
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    A modified interval valued intuitionistic fuzzy CODAS method and its application to multi-criteria selection among renewable energy alternatives in Turkey
    (Elsevier, 2020) Deveci, Kaan; Cin, Rabia; Kağızman, Ahmet
    Combinative Distance based ASsesment (CODAS) method aims to perform multi-criteria selection process according to the largest Euclidean and Taxicab distance with respect to negative ideal solutions. Recently, several CODAS methods have been applied to multi-criteria decision making problems with interval valued intuitionistic fuzzy sets. This paper demonstrates the weaknesses of using Euclidean and Taxicab distance on interval valued intuitionistic fuzzy sets and provides alternative strategies to model the vagueness and uncertainty in decision maker evaluations more effectively. The contribution of this paper is twofold. First, a new selection metric is defined in order to eliminate the disadvantages of using Euclidean and Taxicab distance in interval valued intuitionistic fuzzy CODAS. Second, a new fuzzy aggregation operator is proposed for aggregating decision maker evaluations by using fuzzy weights rather than using crisp weights. To show the effectiveness of the modified CODAS method, an application is given for multi-criteria selection of renewable energy alternatives in Turkey and the results are compared with two other interval valued intuitionistic fuzzy CODAS methods in the literature. (C) 2020 Elsevier B.V. All rights reserved.
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    Aerothermal optimizaiton of squealer geometry in axial flow turbines using genetic algorithm
    (2018) Deveci, Kaan; Maral, Hıdır; Şenel, Cem Berk; Alpman, Emre; Kavurmacıoğlu, Levent Ali
    In turbomachines, a tip gap is required in order to allow the relative motion of the blade and to prevent the blade tip surface from rubbing. This gap which lay out between the blade tip surface and the casing, results in fluid leakage due to the pressure difference between the pressure side and the suction side of the blade. The tip leakage flow causes almost one third of the aerodynamic loss and unsteady thermal loads over the blade tip. Previous experimental and numerical studies revealed that the squealer blade tip arrangements are one of the effective solutions in increasing the aerothermal performance of the axial flow turbines. In this paper the tip leakage flow is examined and optimized with the squealer geometry as a means to control those losses related with the tip clearance. The squealer height and width have been selected as design parameters and the corresponding computational domain was obtained parametrically. Numerical experiments with such parametrically generated multizone structured grid topologies paved the way for the aerothermal optimization of the high pressure turbine blade tip region. Flow within the linear cascade model has been numerically simulated by solving Reynolds Averaged Navier-Stokes (RANS) equations in order to produce a database. For the numerical validation a well-known test case, Durham cascade is investigated in end wall profiling studies has been used. Sixteen different squealer tip geometries have been modeled parametrically and their performance have been compared in terms of both aerodynamic loss and convective heat transfer coefficient at blade tip. Also, these two values have been introduced as objective functions in the optimization studies. A state of the art multi-objective optimization algorithm, NSGA-II, coupled with an Artificial Neural Network is used to obtain the optimized squealer blade tip geometries for reduced aerodynamic loss and minimum heat transfer coefficient. Optimization results are verified using CFD.
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    An Assessment of Renewable Energy Resources for Electricity Generation in Turkey
    (Springer Science and Business Media Deutschland GmbH, 2024) Duman, A. Can; Gönül, Ömer; Deveci, Kaan; Güler, Önder
    In order to achieve emission mitigation targets and reduce dependency on imported energy, many countries moved toward renewable energy resources. Among them, Turkey has achieved a remarkable renewable energy capacity increase in recent years. Today, Turkey is at the forefront in Europe and MENA region in terms of installed capacity of geothermal (ranked 1st) and hydroelectric power (ranked second after Norway). The country accelerated its solar photovoltaic (PV) investments, particularly in the last few years, and ranked first in 2017 and second after Germany in 2018 in newly added PV capacity among European and MENA countries. By the end of 2019, Turkey has the tenth highest electricity generation from wind energy in the world. Turkey also speeds up its biomass energy investments in line with the country’s energy diversity policy. Turkey owes its accomplishments in renewable energy not only to its substantial resources but also to its efficient YEKDEM feed-in tariff (FiT) mechanism and YEKA auction mechanism for allocation of connection capacity. This study presents an overall assessment of renewable energy resources in Turkey and introduces the existing renewable energy incentive mechanisms. It carries out feasibility analyses of wind, solar PV, biomass, and geothermal power plants in Turkey and concludes with recommendations for renewable energy expansion in the country. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
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    An assessment of wind energy status, incentive mechanisms and market in Turkey
    (Elsevier, 2021) Gönül, Ömer; Duman, Anıl Can; Deveci, Kaan; Güler, Önder
    Turkey attaches great importance to energy diversification to reduce the energy dependence on fossil resources. In this regard, Turkey assigned energy targets by 2023 including 20 GW of installed wind capacity. Yet, despite the good efforts, the current wind installed capacity of 8 GW is far behind the assigned target. This study presents a comprehensive review of wind energy status in Turkey focusing on policies and incentives for improvement of wind energy progress in the country. To that end, the global wind energy market is evaluated and a set of recommendations is presented in the context of the importance of local employment and establishment of local wind energy industry. Then, a feasibility analysis is performed to discuss the current feed-in tariff scheme in Turkey. Lastly, Turkey's competitive position is evaluated over a SWOT analysis to give an overview of all positive and negative determinants, considering internal and external factors.
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    Electrical layout optimization of onshore wind farms based on a two-stage approach
    (Ieee-Inst Electrical Electronics Engineers Inc, 2020) Deveci, Kaan; Barutçu, Burak; Alpman, Emre; Tascıkaraoğlu, Akın; Erdinç, Ozan
    Electrical layouts have a significant impact on the investment cost and electrical losses of wind farms, and therefore, layouts should be optimized for reducing their share in the project budgets. In this study, a two-stage method for electrical layout optimization is given. In the first stage, the total trenching length between wind turbines and substation is minimized and in the second stage, the cabling process is performed. The contribution of this article with respect to earlier studies is twofold: First, a new theory for cabling is given and it has shown that determination of the best type of electrical cable is a priori. The suggested cabling theory reduces the complexity of the electrical layout problem since the cable related variables and constraints are avoided. Second, a new bi-objective problem is defined which allows parallel cabling over the previously defined paths. The cabling problem defined aims to minimize the net present cost of the electrical losses and initial investment costs over a known path. Moreover, a novel 3D methodology is introduced for calculating the total length of cables and trenching over the surface of the ground more accurately. All theoretical work is applied on a real onshore wind farm.
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    Ranking intuitionistic fuzzy sets with hypervolume-based approach: An application for multi-criteria assessment of energy alternatives
    (Elsevier, 2024) Deveci, Kaan; Guler, Onder
    Ranking Intuitionistic Fuzzy Sets (IFS) using distance-based methods involves calculating the distance between an IFS and a reference point which represents either maximum (positive ideal solution) or minimum (negative ideal solution) value. These methods assume that similarity of an IFSs to the reference point increases as its distance from it decreases. While it is a common practice to use nonlinear distance functions for ranking IFSs, this paper proves that no nonlinear IF distance function can be robust. In this study, the shortcomings of the conventional procedure are demonstrated by providing a mathematical proof and an alternative ranking method based on the hypervolume metric is proposed. In addition, the suggested ranking approach is extended as a new multi-criteria decision making method called Hypervolume-based Evaluation and Ranking Technique (HEART). HEART is applied for multi-criteria assessment of Turkey's energy alternatives. Results are compared with three distance based multi-criteria decision making methods: TOPSIS, VIKOR, and CODAS.