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

ORCID ID

0000-0002-3271-8418

Scopus Author ID

24823628300

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Scholarly Output Search Results

Now showing 1 - 10 of 35

Citation Count: 28
Hourly Electricity Demand Forecasting Using Fourier Analysis With Feedback
(Elsevıer, 2020) Yükseltan, Ergün; Yücekaya, Ahmet; 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.
Sceheduling Pumped Hydro- Power Resources Under Price and Flow Uncertainty
(Kadir Has Üniversitesi, 2012) Metin, Seda Sibel; Yücekaya, Ahmet Deniz
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 Count: 4
Agent-Based Optimization To Estimate Nash Equilibrium in Power Markets
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; 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.
Citation Count: 0
Electric Power Bid Determination and Evaluation for Price Taker Units Under Price Uncertainty
(Econjournals, 2021) Yucekaya, Ahmet; 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 Count: 0
A Network Model for the Location-Routing Decisions of a Logistics Company
(Institute of Industrial Engineers, 2012) Sama, Funda; Yücekaya, Ahmet; Ayağ, Zeki
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%.
Citation Count: 30
Scheduling a Log Transport System Using Simulated Annealing
(Elsevier Science, 2014) Haridass, Karunakaran; Valenzuela, Jorge; Yücekaya, Ahmet; McDonald, Tim
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 Count: 5
An Analysis of Price Spikes and Deviations in the Deregulated Turkish Power Market
(Elsevier, 2019) Gayretli, Gizem; Yücekaya, Ahmet; 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 Count: 10
A Fuzzy Anp-Based Gra Approach To Evaluate Erp Packages
(IGI Global, 2019) Ayağ, Zeki; Yücekaya, Ahmet
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.
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; 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.
Citation Count: 12
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) Yucekaya, Ahmet
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.