Browsing by Author "Yücekaya, Ahmet"

Now showing 1 - 17 of 17

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.
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.
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.
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 - 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: 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: 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.
Citation - WoS: 5
Citation - Scopus: 9
Managing Fuel Coal Supply Chains With Multiple Objectives and Multimode Transportation
(AMER SOC ENGINEERING MANAGEMENT, 2013) Yücekaya, Ahmet Deniz; Yücekaya, Ahmet
Power companies require sophisticated tools to manage fuel-coal supply chains which include multiple suppliers coal contracts and multimode transportation routes. In this article a multi-objective model which is integrated with multi-attribute decision-making for the selection of suppliers transportation routes and coal orders is developed. The model simultaneously optimizes multiple objectives such as minimizing purchase costs transportation costs and ash output and it also presents a decision framework on the selection of suppliers transportation routes and coal products that will achieve these objectives. The network and capacity constraints of suppliers and transportation routes are included in the model. The study utilizes multi-objective linear programming and well-known decision rules such as minimax maximin and compromise programming and Analytic Hierarchy Process is employed to determine preferred solutions. The methodology for the solution is illustrated via a case study and an alternative evaluation process is presented. The study demonstrates that the model can be used by power companies to find desired solutions as it provides an opportunity for the inclusion of the preferences of decision-makers and adjustments of the weights for each objective.
Citation - WoS: 8
Citation - Scopus: 8
Managing Natural Gas Demand for Free Consumers Under Uncertainty and Limited Storage Capacity
(Elsevier, 2020) Aktunç, Esra Ağca; Bilge, Ayşe Hümeyra; Yükseltan, Ergün; Ağca Aktunç, Esra; Yücekaya, Ahmet; Yücekaya, Ahmet Deniz; Bilge, Ayşe Hümeyra
Demand for energy sources depends on several factors such as population growth, urbanization, industrialization, and climate. Among fundamental energy sources, natural gas is characterized by storage limitations and take-or-pay contracts, which makes it especially critical to forecast the demand accurately for cost management policies. Suppliers of natural gas require take-or-pay contracts to ensure that consumers pay for any unused amount up front; and if the demand exceeds the agreed amount, they pay for over-use as well. Consumers with a demand above the eligible consumer limit are categorized as free consumers; and they have to specify their daily, monthly, and annual demand in these take-or-pay contracts. In residential areas, natural gas is used predominantly for heating, hence its consumption has a strong seasonality. In winter, the variability in the atmospheric temperature leads to fluctuations in the demand, while in summer, weekend effects dominate. In order to take these features into account, a demand forecasting model based on a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures, is used in this study to determine the threshold value for the onset of natural gas usage for heating purposes. The upper and lower bounds for consumption are obtained as a function of temperature only, after analyzing the details of the temperature-consumption relationship using historical data. Moreover, a temperature-based simulation methodology is proposed and simulation results that provide guidelines to manage the costs of storage under uncertainty are presented by suggesting the minimum storage capacity required and showing the distribution of the costs.
Citation - WoS: 10
Citation - Scopus: 11
Multi-Objective Fuel Supply for Coal-Fired Power Plants Under Emission Transportation and Operational Constraints
(Taylor & Francis Inc, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz
Coal-fired power plants need to decrease their generation cost in deregulated power markets so as to be selected dispatched and compete with other cheaper resources. On the other hand coal prices have risen significantly and extra costs for SO2 and NOx emission outputs are imposed that force power companies to lower the costs for the fuel-coal supply process. In this article a multi-objective model for supplier transportation and coal order selection is developed for the coal supply of electric power plants in an environment where multiple suppliers coal contracts and multimode transportation routes exist. The model simultaneously optimizes multiple objectives such as minimizing purchase transportation sulfur dioxide and nitrogen oxides costs and carbon dioxide and ash outputs of coal. Multi-objective linear programming and analytic hierarchy process are employed to solve the problem. The solution methodology is applied in a case study in the Midwestern United States and the alternative evaluation process is presented. It is shown that the model can be used by the power companies to find a desired solution for their coal supply and hence generate power with coal of lower cost lower emission and ash.
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
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 - WoS: 26
Citation - Scopus: 30
Nutrient Dynamics in Flooded Wetlands. I: Model Development
(ASCE-AMER SOC CIVIL ENGINEERS, 2013) Hantush, Mohamed M.; Yücekaya, Ahmet Deniz; Kalın, Latif; Işık, Sabahattin; Yücekaya, Ahmet
Wetlands are rich ecosystems recognized for ameliorating floods improving water quality and providing other ecosystem benefits. This part of a two-paper series presents a relatively detailed process-based model for nitrogen and phosphorus retention cycling and removal in flooded wetlands. The model captures salient features of nutrient dynamics and accounts for complex interactions among various physical biogeochemical and physiological processes. The model simulates oxygen dynamics and the impact of oxidizing and reducing conditions on nitrogen transformation and removal and approximates phosphorus precipitation and releases into soluble forms under aerobic and anaerobic conditions respectively. Nitrogen loss pathways of volatilization and denitrification are explicitly accounted for on a physical basis. Processes in surface water and the bottom-active soil layer are described by a system of coupled ordinary differential equations. A finite-difference numerical scheme is implemented to solve the coupled system of ordinary differential equations for various multiphase constituents' concentrations in the water column and wetland soil. The numerical solution algorithm is verified against analytical solutions obtained for simplified transport and fate scenarios. Quantitative global sensitivity analysis revealed consistent model performance with respect to critical parameters and dominant nutrient processes. A hypothetical phosphorus loading scenario shows that the model is capable of capturing the phenomenon of phosphorus precipitation and release under oxic and anoxic conditions respectively.
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.
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
Citation - WoS: 38
Citation - Scopus: 46
The Operational Economics of Compressed Air Energy Storage Systems Under Uncertainty
(Pergamon-Elsevier Science Ltd, 2013) Yücekaya, Ahmet; Yücekaya, Ahmet Deniz
A Compressed Air Energy Storage System is a means of storing energy which can then be used when the demand for energy increases. In this system air is compressed in a cavern when power prices are low and this air is used to run a natural gas-fired turbine to generate power when prices go up with the aim of profiting from the price difference. This type of system can independently compress air generate electricity or do both. However the prices of electricity and natural gas fluctuate which directly impacts the amount of revenue that can be made and this requires the calculating of estimates to optimize operation strategies and maximize profit. For these reasons this is a crucial energy storage technology that requires economic analyses to justify investment decisions in power markets. In this paper a mixed integer programming method is developed to schedule the operation of the system for forward market prices that are estimated using a markov-based probabilistic model. Then an algorithm that includes two separate modules in a simulation is employed to optimize the annual operation of the system. The paper presents a case study for Turkey as well as economic analyses based on probabilistic forward prices and the profits obtained from the optimization module. (C) 2013 Elsevier Ltd. All rights reserved.
Citation - WoS: 30
Citation - Scopus: 33
Scheduling a Log Transport System Using Simulated Annealing
(Elsevier Science, 2014) Haridass, Karunakaran; Yücekaya, Ahmet Deniz; 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.