Browsing by Author "Yücekaya, Ahmet Deniz"

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2050 Yılına Kadar Sıfır Karbon Emisyon Hedefi: Türkiye'de %100 Temiz Elektriğin Uygulanabilirliği
(Kadir Has Üniversitesi, 2021) Yalçın, Yasemin Yağmur; Yücekaya, Ahmet Deniz; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet Deniz
The aim of this study is to make projections about how much resources Turkey needs to meet its electricity demand within the framework of zero carbon emissions by 2050, and to make evaluations about renewable energy capacity to meet this need. The data used in this study were obtained through World Bank, Turkish Electricity Transmission Corporation and Energy Exchange İstanbul. In the first part, electricity supply sources, capacities and potentials in Turkey are discussed. In the second part, the current state of electricity consumption is examined; analyzes on the effects of population, national income and technology on electricity consumption are evaluated. In the third part, the level that the electricity demand will reach in 2050 depending on national income, population and technology has been estimated in various scenarios and the predicted demand is compared with the renewable energy potential. In the fourth and last part, evaluations have been made on the potential renewable electricity capacity and projected energy demand scenarios. Keywords: Electricity demand projection based on population, national income and technology, Zero carbon emissions
Citation - WoS: 4
Citation - Scopus: 6
Agent-Based Optimization To Estimate Nash Equilibrium in Power Markets
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Valenzuela, Jorge
In most deregulated power markets firms bid daily into a day-ahead power market. The auction mechanism supply and demand determine the equilibrium at each hour. In this environment firms aim to maximize their revenues by carefully determining their bids. This requires the development of effective computational methods that help them estimate their competitors' behaviors under incomplete information. In this article an agent-based method that uses particle swarm optimization is described to simulate the behavior of market participants. Particle swarm optimization is used in the bidding process and an agent-based model is applied to find a Nash equilibrium. Different stopping conditions are used to determine the equilibrium. Experimental results are presented for two power systems.
An Analysis of Development Indicators for Turkey Based on the Historical Development of 500 Largest Industrial Organizations
(Kadir Has Üniversitesi, 2015) Otnar, Ferhan; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet Deniz
Economies live rapid changes in terms of size direction and intention due to globalization population increase of countries and technological developments. These changes seemed clearer in developing countries because of fast progress and demand increases. Especially in last 10 year period Turkey gained economical acceleration along with growth and development. Parallel to these developments diversification in industrial areas and evolvement in remained areas used as an answer. in this aspect istanbul Chamber of industry announced Turkey's top 500 industrial enterprises each year. in this study Turkey's developing economy was analyzed with iSO Top 500 List for 2002-2012 periods in order to identify vector sectors and economical variance. According to analysis changes in industrial effects on Turkey's economy were investigated.
Citation - WoS: 6
Citation - Scopus: 11
An Analysis of Price Spikes and Deviations in the Deregulated Turkish Power Market
(Elsevier, 2019) Gayretli, Gizem; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Bilge, Ayşe Hümeyra
The successful operation of a real time market is related to the planning in the day ahead market. We analyze the day ahead and real time market data for the Turkish power market for the period 2012-2015 to classify price spikes and their causes. We also focus on the levels of deviation between the day ahead market values and the real time market values. We define price deviation and load deviation ratios to measure the level of deviation both in price and demand. The analysis for the load is based on load shedding and cycling values. We analyze the mean and standard deviation in market prices and we determine the price spike as a two sigma deviation from the mean value. It is shown that 60% of the price deviation ratios are in the range of ( +/- 20%), while 44% are in the range of ( +/- 10%) and 35% are in the range of (+/- 5%). We also show that 56.9% of the spikes are due to problems in the generation of natural gas based power plants which affect the day ahead and real time prices. A total of 29.2% of the spikes are due to power plant and system failures that affect only real time prices. The share of high temperature based spikes is 13.9% which is a result of air conditioner usage.
Citation - WoS: 11
Citation - Scopus: 15
Bidding of Price Taker Power Generators in the Deregulated Turkish Power Market
(Pergamon-Elsevier Science Ltd, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet
In deregulated power markets power firms bid into the day-ahead power market either with buy offers or sell offers. The auction mechanism and competition determine the equilibrium price and quantity for each hour. If the bid price of a company is below the market clearing price then the offer of the company is accepted and rewarded with the market price. A company can be a price maker or price taker depending on the capacity it offers to the market. A price-taker unit must determine the right offer that will maximize their profit given price uncertainty and blind auction rules. This paper first examines power supply in the Turkish electricity market and bidding process. Then a marginal cost-based Monte Carlo method is developed to determine hourly and block bidding strategies of price taker units. Historical market prices are then implemented in a normal distribution to generate hourly price scenarios. A solution methodology is developed that maximizes the expected profit of each hourly and block bidding strategy over price scenarios. The generator is able to both evaluate the hourly bidding and block bidding strategies and find the best bidding strategy that will be submitted to the market using the proposed methodology. The model is illustrated for two coal units in Turkish power market and the results are presented. (C) 2013 Elsevier Ltd. All rights reserved.
Decarbonization Pathways For Turkish Power System Using The Leap Model Leap Modeli Kullanılarak Türkiye Elektrik Sistemi için Dekarbonizasyon Yolları
(Kadir Has Üniversitesi, 2021) Özer, Fatma Ece; Yücekaya, Ahmet Deniz; Kirkil, Gökhan; Yücekaya, Ahmet Deniz
The negative impact of GHG released into the atmosphere on global warming cannot be ignored. Fossil-fueled power plants constitute a large part of Turkey's electricity production, as every country has a growing economy. Therefore, the electricity generation sector accounts for a significant portion of GHG emissions in Turkey. In addition to national bindings such as the Paris Agreement and the Kyoto Protocol, it is known that the Republic of Turkey aims to make not only electricity but also energy production greener in the coming years, in line with its own efforts. For this purpose, there are different modeling studies in the literature. This thesis aims to model Turkey's electricity generation sector in 2017, reveal the current situation, and then analyze how a greener and sustainable energy transformation will be possible with different scenarios and different main factors. In this direction, Turkey's electricity generation sector was modeled using the LEAP tool, then the decarbonization scenarios created within the openENTRANCE project were adapted to Turkey's data, and the numerical results of the scenarios were compared. As a result, it has been revealed that social awareness, adaptation to new technologies, and incentives of decision-makers are all critical factors in this regard.
A Decision Support System for Assembly Line Balancing Problem
(Kadir Has Üniversitesi, 2015) Ringim, İbrahim Uba; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet Deniz
Assembly line balancing problems are generally considered to be complicated in real life. Like most complicated real life assembly line balancing problems obtaining a good solution is much easier than finding an optimal solution especially with big size problems. As a result, many heuristic approaches have been developed to find good optimal solutions to those problems. In this study, we develop a decision support system that solves a deterministic assembly line balancing problem using three heuristic approaches. The objectives considered are: minimizing the number of workstations, maximization of line efficiency and minimization of balance delay. Our aim is using the decision support system created; user can enter any value into the system and obtain 3 different results. The results obtained are feasible enough which shows that the decision support system works and can be able to solve even larger problems if the correct formula is applied
Economic and Operational Analysis of Compressed Air Energy Storage Systems
(Kadir Has Üniversitesi, 2011) Kara, Esma Sedef; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet Deniz
A Compressed Air Energy Storage System (CAES) is a way to store energy to be used when the demand for energy is high. in this system the air is pumped into a cavern when the power price is low and the air is used in a natural gas fired turbine to generate power when the price is high aiming to make profit from this price difference. The system can pump or generate or do both. Typically the power price is low at nights and high during the daytime. However the power and natural gas price along with the heat rate of the turbine should be included to the model to determine when the air should be pumped and when the power should be generated to maximize the revenue. in this research a mixed integer programming method is developed to determine a pumping-generation schedule for the CAES given that market and natural gas price for each hour can be forecasted. Appropriate forecasting methods are used to simulate the power and natural gas prices for the analysis. The model is coded in General Algebraic Modeling System (GAMS) and a case study is presented to validate the model. in addition to scheduling of the CAES another important contribution of this research is to develop a framework for investor companies who wish to build a CAES system. We develop 30-years long market price and natural gas price scenarios and we find annual profits through optimum scheduling of the CAES plant given that market price and natural gas prices are variable. Then we use appropriate engineering economics tools to estimate a Net Present Worth value of each different scenario for the decision makers of the investment companies.
Citation - Scopus: 0
Electric Power Bid Determination and Evaluation for Price Taker Units Under Price Uncertainty
(Econjournals, 2021) Yucekaya, Ahmet; Yücekaya, Ahmet Deniz; Valenzuela, J.
Power companies aim to maximize their profit which is highly related to the bidding strategies used. In order to sell electricity at high prices and maximize their profit, power companies need suitable bidding models that consider power operating constraints and price uncertainty within the market. Price taker units have no power to affect the prices but need to determine their best bidding strategy to maximize their profit assuming a quadratic cost function and uncertain market prices. Price taker units also need to evaluate their bidding strategy under different price scenarios. In this paper, we first model the bidding problem for a price taker unit and then propose quadratic programming, nonlinear programming and marginal cost based bidding models under price uncertainty. We use case studies to study the computation burden and limitation to reach a solution. We also propose a simulation methodology to evaluate the performance of each bidding strategy for different market prices in an effort to help decision makers to assess their bidding decisions. © 2021, Econjournals. All rights reserved.
Citation - WoS: 19
Citation - Scopus: 21
Electricity trading for coal-fired power plants in Turkish power market considering uncertainty in spot, derivatives and bilateral contract market
(Pergamon-Elsevier Science Ltd, 2022) Yücekaya, Ahmet Deniz
In deregulated power markets, electricity suppliers have the option to trade in the spot market, derivatives market, and bilateral contract market. The spot market is always available and open to competition, but the variability and risk incurred need to be carefully handled. The suppliers might allocate their capacity in the derivatives and bilateral contract market if these alternatives are more viable. The strike price, bilateral contract price, and spot market prices need to be used to decide the capacity allocation problem considering the generation cost of the supplier. This paper first examines the market design and electricity trading in the Turkish electricity market. Then three problems were proposed for a coal-fired coal unit that aims to allocate its capacity to spot, derivative, and bilateral contract markets to maximize its expected profit. A Monte Carlo method is used for allocated electricity capacities, spot market, strike, and bilateral contract price scenarios. A simulation methodology is then proposed that includes capacities allocated to each market and price scenarios. The best capacity allocation strategy is determined that return the highest expected profits for all market price samples. The model is illustrated for a coal unit in the Turkish electricity market. The results are presented for the case, including 100 spot price samples, 100 capacity scenarios, 3 scenarios for the strike, and bilateral contract prices. The sensitivity analysis for spot price volatility on the profit is also presented with 20% volatility increase. It is shown that allocating the capacity to more than one market can increase the total expected profit for a power supplier and the rate of increase varies depending on the scenario set.
Citation - WoS: 0
Energy Storage With Pumped Hydrostorage Systems Under Uncertainty
(Springer International Publishing Ag, 2015) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz
Energy storage is becoming an important problem as the difference between supply and demand becomes sharper and the availability of energy resources is not possible all the time. A pumped hydrostorage system (PHSS) which is a special type of hydroelectric power plant can be used to store energy and to use the water more efficiently. When the energy demand and the energy price are high (peak hours) the water at upper reservoir is used to generate electricity and the water is stored in the lower reservoir. Revenue is gained from the power sale to the market. When the demand and the energy price are low (off-peak hours) the water at lower reservoir is pumped back to the upper reservoir. Cheap electricity is used to pump the water. The hourly market price and water inflow are uncertain. The main objective of a company is to find an operation schedule that will maximize its revenue. The hourly electricity prices and the water inflow to the reservoir are important parameters that determine the operation of the system. In this research we present the working mechanism of the PHSS to store energy and to balance the load changes due to demand.
An Evaluation of Energy and Electricity in Pakistan
(Kadir Has Üniversitesi, 2016) Humaiyun, Muhammad Jasim; Yücekaya, Ahmet Deniz; Yücekaya, Ahmet Deniz
Pakistan is a developing country and it can only move forward once the energy sector is secure and self sufficient. Right from the beginning the country has constantly faced energy shortages in all sectors due to incompetent policies and governence. This study frames the analysis of the current energy situation with main focus on electricity. All the factors which are hampering the growth of the energy sector are identified and potential solutions are discussed. Matching the electricity supply and demand is the ultimate goal therefore a forecast analysis (multiple regression model) based on seasonal variation in temperature is performed in order to predict the future electric consumption and help authorities take necessary actions for fulfilment. Finally a comprehensive detail is provided on the causes and problems of the energy crisis and potential solutions and reforms are provided.
Citation - WoS: 75
Citation - Scopus: 89
Forecasting Electricity Demand for Turkey: Modeling Periodic Variations and Demand Segregation
(Elsevier, 2017) Yükseltan, Ergün; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Bilge, Ayşe Hümeyra
In deregulated electricity markets the independent system operator (ISO) oversees the power system and manages the supply and demand balancing process. In a typical day the ISO announces the electricity demand forecast for the next day and gives participants an option to prepare offers to meet the demand. In order to have a reliable power system and successful market operation it is crucial to estimate the electricity demand accurately. In this paper we develop an hourly demand forecasting method on annual weekly and daily horizons using a linear model that takes into account the harmonics of these variations and the modulation of diurnal periodic variations by seasonal variations. The electricity demand exhibits cyclic behavior with different seasonal characteristics. Our model is based solely on sinusoidal variations and predicts hourly variations without using any climatic or econometric information. The method is applied to the Turkish power market on data for the period 2012-2014 and predicts the demand over daily and weekly horizons within a 3% error margin in the Mean Absolute Percentage Error (MAPE) norm. We also discuss the week day/weekend/holiday consumption profiles to infer the proportion of industrial and domestic electricity consumption. (C) 2017 Elsevier Ltd. All rights reserved.
Citation - Scopus: 5
Forecasting Hourly Electricity Demand Under Covid-19 Restrictions
(Econjournals, 2022) Kök, A.; Yücekaya, Ahmet Deniz; Yükseltan, E.; Bilge, Ayşe Hümeyra; Hekimoğlu, M.; Hekimoğlu, Mustafa; Aktunc, E.A.; Yücekaya, A.; Bilge, A.
The rapid spread of the COVID-19 pandemic has severely impacted many sectors including the electricity sector. The restrictions such as lockdowns, remote-working, and-schooling significantly altered the consumers’ behaviors and demand structure especially due to a large number of people working at home. Accurate demand forecasts and detailed production plans are crucial for cost-efficient generation and transmission of electricity. In this research, the restrictions and their corresponding timing are classified and mapped with the Turkish electricity demand data to analyze the impact of the restrictions on total demand using a multiple linear regression model. In addition, the model is utilized to forecast the electricity demand in pandemic conditions and to analyze how different types of restrictions impact the total electricity demand. It is found that among three levels of COVID-19 restrictions, age-specific restrictions and the complete lockdown have different effects on the electricity demand on weekends and weekdays. In general, new scheduling approaches for daily and weekly loads are required to avoid supply-demand mismatches as COVID-19 significantly changed the consumer behavior, which appears as altered daily and weekly load profiles of the country. Long-term policy implications for the energy transition and lessons learned from the COVID-19 experience are also discussed. © 2022, Econjournals. All rights reserved.
Citation - WoS: 7
Citation - Scopus: 9
Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation
(Elsevier Ltd, 2020) Yükseltan, Ergün; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Ağca Aktunç, Esra; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet Deniz; Ağca Aktunç, Esra
Due to expensive infrastructure and the difficulties in storage, supply conditions of natural gas are different from those of other traditional energy sources like petroleum or coal. To overcome these challenges, supplier countries require take-or-pay agreements for requested natural gas quantities. These contracts have many pre-clauses; even if they are not met due to low/high consumption or other external factors, buyers must completely fulfill them. A similar contract is then imposed on distributors and wholesale consumers. It is, thus, important for all parties to forecast their daily, monthly, and annual natural gas demand to minimize their risk. In this paper, a model consisting of a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures as a regressor is proposed for the forecast of monthly and weekly consumption over a one-year horizon. This model is supplemented by a day-ahead feedback mechanism for the forecast of daily consumption. The method is applied to the study of natural gas consumption for major residential areas in Turkey, on a yearly, monthly, weekly, and daily basis. It is shown that residential heating dominates winter consumption and masks all other variations. On the other hand, weekend and holiday effects are visible in summer consumption and provide an estimate for residential and industrial use. The advantage of the proposed method is the capability of long term projections, reflecting causality, and providing accurate forecasts even with minimal information.
Citation - WoS: 10
Citation - Scopus: 16
A Fuzzy Anp-Based Gra Approach To Evaluate Erp Packages
(IGI Global, 2019) Ayağ, Zeki; Ayağ, Zeki; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz
One of the major problems that most companies face with during the implementation of an ERP system is to determine the best satisfying ERP software based on their needs and expectations. Because an improperly selected ERP software might lead to time loss and increased costs and in the long run a loss of market share. Therefore the ERP evaluation process for companies becomes to a vital point. On the other hand evaluating ERP software alternatives under a set of criteria leads us to a multiple-criteria decision making (MCDM) problem and needs to use proper MCDM methods. In the current literature a number of the MCDM methods have been proposed to solve these kinds of problems both of which are the analytic network process (ANP) of Saaty and grey relational analysis (GRA) which has been widely used in solving MCDM selection problems in various fields. Moreover in this article the authors used the fuzzy extension of the ANP method to reflect the uncertainty and ambiguity of decision maker(s) into problem in order to reach more reliable solution. As the fuzzy ANP method was used to calculate the priority weights of the evaluation criteria the GRA method with fuzzy interval-values was employed to rank a set of the possible ERP software alternatives. The proposed approach was also validated in a case study to show its applicability to potential readers and practitioners. Copyright © 2019 IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Citation - WoS: 0
Genesys-Mod Turkey: Quantitative Scenarios for Low Carbon Futures of the Turkish Energy System
(Ieee, 2022) Yücekaya, Ahmet Deniz; Kirkil, Gökhan; Yucekaya, Ahmet Deniz; Kirkil, Gokhan
This paper examines the quantitative scenarios for low-carbon futures of the Turkish energy system at aggregated (country level) and regionally disaggregated (NUTS-1 level) levels. We have employed four different storylines for the future European energy system. They are quantified and implemented for the European energy system (30 regions, mostly single countries, including Turkey) using the open-source global energy system model, GENeSYS-MOD v3.0. We have compared the results of all scenarios at aggregated and disaggregated levels and found that there are significant differences among them. Specifically, the hydrogen production (and its use) has increased considerably in the disaggregated model when compared to the aggregated level results. The major reason for these differences is found to be the better estimation of regional renewable capacity factors (wind and solar) in the disaggregated level compared to aggregated level.
Citation - WoS: 39
Citation - Scopus: 45
Hourly Electricity Demand Forecasting Using Fourier Analysis With Feedback
(Elsevıer, 2020) Yükseltan, Ergün; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Bilge, Ayşe Humeyra
Whether it be long-term, like year-ahead, or short-term, such as hour-ahead or day-ahead, forecasting of electricity demand is crucial for the success of deregulated electricity markets. The stochastic nature of the demand for electricity, along with parameters such as temperature, humidity, and work habits, eventually causes deviations from expected demand. In this paper, we propose a feedback-based forecasting methodology in which the hourly prediction by a Fourier series expansion is updated by using the error at the current hour for the forecast at the next hour. The proposed methodology is applied to the Turkish power market for the period 2012-2017 and provides a powerful tool to forecasts the demand in hourly, daily and yearly horizons using only the past demand data. The hourly forecasting errors in the demand, in the Mean Absolute Percentage Error (MAPE) norm, are 0.87% in hour-ahead, 2.90% in day-ahead, and 3.54% in year-ahead horizons, respectively. An autoregressive (AR) model is also applied to the predictions by the Fourier series expansion to obtain slightly better results. As predictions are updated on an hourly basis using the already realized data for the current hour, the model can be considered as reliable and practical in circumstances needed to make bidding and dispatching decisions.
Citation - WoS: 2
Citation - Scopus: 3
The Implementation of Smart Contract via Blockchain Technology in Supply Chain Management: A Case Study from The Automotive Industry in Turkey
(IEEE, 2021) Hekimoğlu, Mustafa; Yücekaya, Ahmet Deniz; Bozkurt, Hayreddin; Yucekaya, Ahmet; Hekimoglu, Mustafa
Blockchain Technology, underlined as the most revolutionizing innovation after the internet, is still in the growth phase and waits for the practitioners to enlighten its productivity promises. In the current environment, volatile profits require a more digitalized work experience and competitive advantages to get ahead in such a highly competitive automotive industry and innovative applications that lead to more simplified operation management. Accordingly, this paper aims to present a case study via use cases in which Blockchain has been used and smart contract as the sought-out innovation and its application for the digitized spare parts disposal legal process. Blockchain Technology in the automotive sector is discussed by focusing on the supply management process of an automotive company's processes in Turkey. Blockchain technology is expected to develop and simplify spare parts-related transactions in the automotive industry, which deals with more than 500K stock keeping units per company. Paper presents the current, future, and ideal states of spare parts transactions with Blockchain adoption. The implemented application enables the development of an enterprise-level blockchain platform with hyper-ledger fabric as an open-source. The distributed ledger technology provides a smart contract system between actors of the existed supply chain process. The study aims to show the potential of Blockchain Technology in delivering a high degree of competitive advantage especially for automotive service providers with regards to its features related to providing security, transparency, traceability, cost reduction, more efficient data storage in dense supply based industries.
Citation - WoS: 1
Landfill Gas To the Energy Potential of Turkey: a Scenario-Based Multi-Period Simulation
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz
Turkey is a developing country with increasing power demands and limited energy sources. Municipal solid waste processing landfilling and utilization of the gas to generate electric power and lower emissions has been used in developed countries for decades however it is relatively new in Turkey. The new regulations force municipalities in the country to build landfills to safely store the waste and secure the emission gases. The landfill gas can be utilized to produce energy and heat or if the quality is high it can be transported to a natural gas pipeline. In this article an overview of landfill gas-to-energy plants in the world is presented and the situation in Turkey is analyzed. A multi-period simulation methodology for municipalities is proposed to estimate the potential power generation and amount of methane that can be prevented. The municipalities in Turkey were classified into three categories and a scenario-based simulation is performed to estimate the energy generation and emission reduction that the country can gain if the landfill projects are activated according to the scenarios.