Browsing by Author "Goren, Selcuk"

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Cloud Induced PV Impact on Voltage Profiles for Real Microgrids
(IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2018) Kocer, Mustafa Catagatay; Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet; Alan, Irfan; Al-Agtash, Salem; Azzopardi, Brain; Martensen, Nis; Martinez-Ramos, Jose L.; Tzovaras, Dimitrios; Hadjidemetriou, Lenos; Khiat, Mounir; Camilleri, Tim; Borg, Nicholas; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü
Integration of renewable energy sources (RESs) into power systems has been a popular topic for a long time. Due to government policies and incentives, it will be more popular in the future since it is a free and environment-friendly nature. Besides its advantages, photovoltaic (PV) generation causes some serious problems to the grid. Since PV generation directly depends on the solar irradiance, cloud movements can cause sudden changes on the output of PV power and this results in some power issues in the system such as voltage violations, reverse power flow, voltage fluctuations. These types of issues complicate to maintain voltage within compulsory levels at customer sides. Thus, cloud-induced transients in PV power are seen as a potential handicap for the future expansion of renewable energy resources. This study investigates effects of instantaneous changes in PV power on the customer side voltage levels. Daily PV power output and voltage profiles were simulated using a real-world microgrid design that will be implemented in the Malta College of Arts Science and Technology(MCAST) Campus.
Dynamic rolling horizon control approach for a university campus
(Elsevier Ltd, 2022) Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet; Ustun, Taha Selim; 0000-0002-5320-4213; 0000-0001-7086-5112; 0000-0002-2413-8421; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Yoldaş, Yeliz; Gören, Selçuk; Önen, Ahmet
An energy management system based on the rolling horizon control approach has been proposed for the grid-connected dynamic and stochastic microgrid of a university campus in Malta. The aims of the study are to minimize the fuel cost of the diesel generator, minimize the cost of power transfer between the main grid and the micro grid, and minimize the cost of deterioration of the battery to be able to provide optimum economic operation. Since uncertainty in renewable energy sources and load is inevitable, rolling horizon control in the stochastic framework is used to manage uncertainties in the energy management system problem. Both the deterministic and stochastic processes were studied to approve the effectiveness of the algorithm. Also, the results are compared with the Myopic and Mixed Integer Linear Programming algorithms. The results show that the life span of the battery and the associated economic savings are correlated with the SOC values.
A Framework to Incorporate Decision-Maker Preferences Into Simulation Optimization to Support Collaborative Design
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2017) Goren, Selcuk; Baccouche, Ahlem; Pierreval, Henri; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Goren, Selcuk
In this paper, we are concerned with the use of simulation optimization to handle collaborative design problems where more than one decision-maker is involved. We assume that the designers cannot enumerate all their considerations in closed-form, precise mathematical expressions but they can examine the merits of solutions with respect to their preferences and can compare candidate solutions with one another. We propose a three-stage framework to take the decision-makers' such considerations into account. The first step is to obtain a diverse set of designs that can all be considered efficient in terms of a performance metric ( i.e.,the objective function values of the simulation optimization model). These solutions are then passed on to the decision-makers to be analyzed in terms of their preferences that could not have been previously considered. Finally, the most appropriate solution is chosen. We address the problem encountered in the first step as a multimodal optimization problem. We address the second and the third subproblems as a preference aggregation problem in the social choice theory. We also illustrate the effectiveness of the proposed approach through a supply chain design problem inspired from the literature. We use the crowding clustering genetic algorithm as an example to demonstrate the first step. We use a multiplicative variant of the popular analytic hierarchy process to illustrate how the second and the third steps can be handled.
Implementation of cost benefit analysis of vehicle to grid coupled real Micro-Grid by considering battery energy wear: Practical study case
(SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND, 2020) Koubaa, Rayhane; Yoldas, Yeliz; Goren, Selcuk; Krichen, Lotfi; Onen, Ahmet; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü
The proposed research represents a spin-off of the Malta College of Arts, Science and Technology (MCAST) Micro-Grid (MG) project. Particularly, economic impact of Electric Vehicles (EV) integration into the MG is investigated in this paper. The MCAST MG consists of photovoltaic generation unit, a diesel generator and a battery storage system. In this paper, a Vehicle-to grid (V2G) concept is considered where utilities can profit from controlled energy trading operations according to EVs availability. EVs are categorized under different profiles considering energy and time availability of owners typical work hours. V2G energy cost is estimated based on battery energy wear due V2G extra cycling and refunded to EVs owners. As most of developed V2G studies don't consider real world input data or/and EV battery aging cost in system modeling and evaluation, the present paper presents a reliable study as it considers a real life MG with in field measurement input data and appropriate battery degradation model. The adopted model represents a linear approximation with a minimum error value to make a suitable tradeoff of computational complexity and accuracy of obtained results. Economic assessment of the system according to the proposed energy management is performed, where results indicate that the V2G system assisted the MG operation during high electricity price period and achieved economic profit to EVs owners. According to numerical results, V2G energy trading achieved 29.90 EUR of gross selling revenues with only 4.46 EUR as battery degradation cost which makes a 16.41% average cost reduction of daily MG operation cost.
A multimodal, multicommodity, and multiperiod planning problem for coal distribution to poor families
(ELSEVIER SCIENCE INC, STE 800, 230 PARK AVE, NEW YORK, NY 10169 USA, 2020) Akgun, Ibrahim; Ozkil, Altan; Goren, Selcuk; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü
Tackling poverty has been one of the greatest global challenges and a prerequisite to sustainable development of countries. Countries implement nationally appropriate social protection systems and measures to address poverty. This paper addresses an aid system adopted by the government in Turkey where significant amounts of coal is distributed to poor families each year. The objective of the coal aid system is to complete the delivery of coal to poor families by the start of winter. However, an analysis of the data from previous years indicates that the distribution to many families cannot be completed on time. This results from the fact that planning is done manually and by trial-and-error as there is no system that can be used for distribution planning. This paper describes the planning problem encountered and develops a mathematical model to solve it. The proposed model is a multimodal, multicommodity, and multiperiod linear programming (LP) model. The model can be used to develop and update a distribution plan as well as to answer several what-if questions with regard to capacities, time constraints, and so forth. The model is solved using CPLEX for several problem instances obtained under different scenarios using data for the year 2012. The results show that at least 9% cost savings and about 40% decrease in distribution completion time can be achieved when the model is used. We analyze scenario results qualitatively and quantitatively and provide several insights to the decision makers. As a part of quantitative analysis, we develop regression models to predict optimal costs based on several factors. Our main contribution is to provide an efficient and effective tool to handle a large-scale real-world problem. The model has also helped to prove that the organization responsible for distribution planning may move from the current planning practice to an all-encompassing top-down approach.
Statistical Approach for Table Tennis Athletes' Success
(AMER INST PHYSICS, 2 HUNTINGTON QUADRANGLE, STE 1NO1, MELVILLE, NY 11747-4501 USA, 2018) Goren, Selcuk; Gulbahar, Ibrahim Tumay; Pinar, Muhammed Safak; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü
This report summarizes the statistical modeling and analysis results associated with the athletes' success and athletes' features. Main purpose of this report is to find any relation between athletes' success and their features. As a tool of creating correlation regression is used with SPSS.
Taking advantage of a diverse set of efficient production schedules: A two-step approach for scheduling with side concerns
(PERGAMON-ELSEVIER SCIENCE, 2013) Goren, Selcuk; Pierreval, Henri; 0000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Goren, Selcuk
In many practical scheduling problems, the concerns of the decision-maker may not be all known in advance and therefore may not be included in the initial problem definition as an objective function and/or as constraints. In such a case, the usual techniques of multi-objective optimization become inapplicable. To cope with this problem and to facilitate handling the concerns of the decision-maker, which can be implicit or qualitative, a dedicated methodological framework is needed. In this paper we propose a new two-step framework. First, we aim at obtaining a set of schedules that can be considered efficient with respect to a performance measure and at the same time different enough from one another to enable flexibility in the final choice. We formalize this new problem and suggest to address it with a multimodal optimization approach. Niching considerations are discussed for common scheduling problems. Through the flexibility induced with this approach, the additional considerations can be taken into account in a second step, which allows decision-makers to select an appropriate schedule among a set of sound schedules (in contrast to common optimization approaches, where usually a single solution is obtained and it is final). The proposed two-step approach can be used to handle a wide range of underlying scheduling problems. To show its potential and benefits we illustrate the framework on a set of hybrid flow shop instances that have been previously studied in the literature. We develop a multimodal genetic algorithm that employs an adapted version of the restricted tournament selection for niching purposes in the first step. The second step takes into account additional concerns of the decision-maker related to the ability of the schedules to absorb the negative effects due to random machine breakdowns. Our computational experiments indicate that the proposed framework is capable of generating numerous high-performance (mostly optimal) schedules. Additionally, our computational results demonstrate that the proposed framework provides the decision-maker a high flexibility in dealing with subsequent side concerns, since there are drastic differences in the capabilities of the efficient solutions found in Step 1 to absorb the negative impacts of machine breakdowns