Ahmet Deniz Yücekaya

Yücekaya, Ahmet Deniz

Name Variants

A. Yücekaya
YÜCEKAYA, AHMET DENIZ
Yücekaya, A.
Yucekaya A.
Yücekaya, Ahmet Deniz
Yücekaya,A.D.
Ahmet Deniz, Yucekaya
Ahmet Deniz YÜCEKAYA
Yücekaya, A. D.
AHMET DENIZ YÜCEKAYA
Yucekaya,Ahmet Deniz
A. D. Yücekaya
Yucekaya,A.D.
Ahmet Deniz Yücekaya
Yucekaya, Ahmet Deniz
YÜCEKAYA, Ahmet Deniz
Y.,Ahmet Deniz
Yücekaya, AHMET DENIZ
Y., Ahmet Deniz
Yücekaya, Ahmet Çelebi
Yücekaya, Ahmet Deniz
Yucekaya, Ahmet
Yücekaya, Ahmet

Job Title

Prof. Dr.

Email Address

ahmety@khas.edu.tr

Main Affiliation

Industrial Engineering

Sustainable Development Goals Report Points

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Scholarly Output

35

Articles

19

Citation Count

10

Supervised Theses

10 Scholarly Output Search Results

Now showing 1 - 10 of 35

Citation - Scopus: 0
A Network Model for the Location-Routing Decisions of a Logistics Company
(Institute of Industrial Engineers, 2012) Sama, Funda; Samanlıoğlu, Funda; Yücekaya, Ahmet; Ayağ, Zeki; Ayağ, Zeki; Yücekaya, Ahmet Deniz; Industrial Engineering
In this paper, part of the logistics network of one of the leading logistics companies in Turkey is analyzed. Data related to the candidate warehouse locations, supplies and demands of customers are collected. A network model is developed in order to reconfigure the logistics network. The aim of the mathematical model is to help decision makers decide on the locations of warehouses, as well as routing products from suppliers to the distribution center; from distribution center to warehouses; and finally from warehouses to customers. The mathematical model is solved optimally with LINGO solver, and the comparison of the current network with the optimal solution revealed that the overall operating costs can be reduced by approximately 7%.
Sceheduling Pumped Hydro- Power Resources Under Price and Flow Uncertainty
(Kadir Has Üniversitesi, 2012) Yücekaya, Ahmet Deniz; Yücekaya, Ahmet Deniz; Industrial Engineering
Hydroelectric power plants should be preferred since they are environmentally friendly and they have low level of potential risks. Hydroelectric power plants are local resources that are environmentally compatible unpolluted capable of dealing with peak hour requirements highly efficient cost-free of fuel and playing a role as the insurance of energy prices. -- Abstract'dan.
Citation - WoS: 39
Citation - Scopus: 46
Hourly Electricity Demand Forecasting Using Fourier Analysis With Feedback
(Elsevıer, 2020) Yükseltan, Ergün; Bilge, Ayşe Hümeyra; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Bilge, Ayşe Humeyra; Industrial Engineering
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: 30
Citation - Scopus: 34
Scheduling a Log Transport System Using Simulated Annealing
(Elsevier Science, 2014) Haridass, Karunakaran; Yücekaya, Ahmet Deniz; Valenzuela, Jorge; Yücekaya, Ahmet; McDonald, Tim; Industrial Engineering
The log truck scheduling problem under capacity constraints and time window constraints is an NP-hard problem that involves the design of best possible routes for a set of trucks serving multiple loggers and mills. The objective is to minimize the total unloaded miles traveled by the trucks. In this paper a simulated annealing - a meta-heuristic optimization method - that interacts with a deterministic simulation model of the log transport system in which the precedence and temporal relations among activities are explicitly accounted for is proposed. The results obtained by solving a small size problem consisting of four trucks two mills three loggers and four truck trips showed that the best solution could be found in less than two minutes. In addition the solution method is tested using data provided by a log delivery trucking firm located in Mississippi. The firm operates sixty-eight trucks to deliver loads from twenty-two logging operations to thirteen mill destinations. The routes assigned by a supervisory person are used as a benchmark to compare the manual generated solution to the solution obtained using the proposed method. (C) 2013 Elsevier Inc. All rights reserved.
Citation - WoS: 7
Citation - Scopus: 12
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; Industrial Engineering
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: 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; Industrial Engineering
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.
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.; Industrial Engineering
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: 7
Citation - Scopus: 10
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; Industrial Engineering
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 - Scopus: 6
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.; Industrial Engineering
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: 9
Citation - Scopus: 11
Nutrient Dynamics in Flooded Wetlands. Ii: Model Application
(ASCE-AMER SOC CIVIL ENGINEERS, 2013) Kalın, Latif; Yücekaya, Ahmet Deniz; Hantush, Mohamed M.; Işık, Sabahattin; Yücekaya, Ahmet; Jordan, T.; Industrial Engineering
In this paper the authors applied and evaluated the wetland nutrient model that was described in Paper I. Hydrologic and water quality data from a small restored wetland located on Kent Island Maryland which is part of the Delmarva Peninsula on the eastern shores of the Chesapeake Bay was used for this purpose. The model was assessed through various methods against the observed data in simulating nitrogen (N) phosphorus (P) and total suspended sediment (TSS) dynamics. Time series plots of observed and simulated concentrations and loads generally compared well