Browsing by Author "Yucekaya, Ahmet"

Now showing 1 - 5 of 5

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: 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: 11
Optimization of Wastewater Treatment Systems for Growing Industrial Parks
(Elsevier, 2023) Savun-Hekimoglu, Basak; Hekimoğlu, Mustafa; Isler, Zulal; Yücekaya, Ahmet Deniz; Hekimoglu, Mustafa; Ediger, Şevket Volkan; Burak, Selmin; Karli, Deniz; Yucekaya, Ahmet; Ediger, Volkan S.
Wastewater treatment is one of the crucial functions of industrial parks as wastewater from industrial facilities usually contains toxic compounds that can cause damage to the environment. To control their environmental loads, industrial parks make investment decisions for wastewater treatment plants. For this, they need to consider technical and economic factors as well as future growth projections as substantial construction and operational costs of wastewater treatment plants have to be shared by all companies in an industrial park. In this paper, we consider the long-term capacity planning problem for wastewater treatment facilities of a stochastically growing industrial park. By explicitly modeling randomness in the arrival of new tenants and their random wastewater discharges, our model calculates the future mean and variance of wastewater flow in the industrial park. Mean and variance are used in a Mixed Integer Programming Model to optimize wastewater treatment plant selection over a long planning horizon (30 years). By fitting our first model to empirical data from an industrial park in Turkey, we find that considering the variance of wastewater load is critical for long-term planning. Also, we quantify the economic significance of lowering wastewater discharges which can be achieved by water recycling or interplant water exchange.
A Probabilistic Model To Maximize Cross-Selling Revenues in Financial Institutions
(Kadir Has Üniversitesi, 2016) Altun, Yasin; Yücekaya, Ahmet Deniz; Yucekaya, Ahmet
Alongside earns transaction volume and transaction number goals banks also have cross selling rate aims in recent years. Also again many banks of our day have studies on transaction cost and calculate costs for every single transaction without missing any and take this information into account while calculating the actual profitability of customer. We searched which product could be sold to customer in this process. While doing this we took the cost of offer into consideration and try to maximize yield/cost ratio. This is calculated by taking the owning ratio of customers in every segment for this specific product and average profit for every customer. The results are believed to be in a level to apply. The results show that decision support system works well.