Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 16Citation - Scopus: 23Review on Energy Application Using Blockchain Technology With an Introductions in the Pricing Infrastructure(IEEE-Inst Electrical Electronics Engineers Inc, 2022) Al-Abri, Tariq; Onen, Ahmet; Al-Abri, Rashid; Hossen, Abdulnasir; Al-Hinai, Amer; Jung, Jaesung; Ustun, Taha SelimWith the rapid transformation of the energy sector towards modern power systems represented by smart grids (SGs), microgrids (MG), and distributed generation, blockchain (BC) technology has shown the capability for solving security, privacy, and reliability challenges that hinder progress. Currently, the energy structure is forming a decentralized system that prioritizes customer satisfaction. BC technology undertakes power network stockholders in a secure energy market, transparent transactions, and fair competition and offers promising energy solutions. This paper is a comprehensive review of energy applications using BC integration. Firstly, we introduce the drivers of BC leverage that make it a potentially important component of the power network. Following that, we provide background information on BC and its application in areas other than the energy sector. Subsequently, we discuss studies and sort potential energy applications from various recent papers and surveys that have already adopted BC technology in the energy sector. Then, we summarize the pricing infrastructure for applying BC in the energy sector and identify the requirements to build it. Finally, energy security and privacy challenges based on BC are highlighted, along with potential drawbacks and concerns related to the pricing infrastructure.Article Citation - WoS: 23Citation - Scopus: 26Optimal Location and Sizing of Electric Bus Battery Swapping Station in Microgrid Systems by Considering Revenue Maximization(IEEE-Inst Electrical Electronics Engineers Inc, 2023) Kocer, Mustafa Cagatay; Onen, Ahmet; Jung, Jaesung; Gultekin, Hakan; Albayrak, SahinThe radical increase in the popularity of electric vehicles (EVs) has in turn increased the number of associated problems. Long waiting times at charging stations are a major barrier to the widespread adoption of EVs. Therefore, battery swapping stations (BSSs) are an efficient solution that considers short waiting times and healthy recharging cycles for battery systems. Moreover, swapping stations have emerged as a great opportunity not only for EVs, but also for power systems, with regulation services that can be provided to the grid particularly for small networks, such as microgrid (MG) systems. In this study, the optimum location and size that maximize the revenue of a swap station in an MG system are investigated. To the best of our knowledge, this study is first to solve the placing and sizing problem in the MG from the perspective of a BSS. The results indicate that bus 23 is the BSS's optimal location and is crucial for maximizing revenue and addressing issues like the provision of ancillary services in microgrid system. Finally, the swap demand profile of the station serving electric bus public transportation system was obtained using an analytical model based on public transportation data collected in Berlin, Germany.Article Citation - WoS: 23Citation - Scopus: 29Optimal Control of Microgrids With Multi-Stage Mixed-Integer Nonlinear Programming Guided Q-Learning Algorithm(State Grid Electric Power Research inst, 2020) Yoldas, Yeliz; Goren, Selcuk; Onen, AhmetThis paper proposes an energy management system (EMS) for the real-time operation of a pilot stochastic and dynamic microgrid on a university campus in Malta consisting of a diesel generator, photovoltaic panels, and batteries. The objective is to minimize the total daily operation costs, which include the degradation cost of batteries, the cost of energy bought from the main grid, the fuel cost of the diesel generator, and the emission cost. The optimization problem is modeled as a finite Markov decision process (MDP) by combining network and technical constraints, and Q-learning algorithm is adopted to solve the sequential decision subproblems. The proposed algorithm decomposes a multi-stage mixed-integer nonlinear programming (MINLP) problem into a series of single-stage problems so that each subproblem can be solved by using Bellman's equation. To prove the effectiveness of the proposed algorithm, three case studies are taken into consideration: (1) minimizing the daily energy cost; (2) minimizing the emission cost; (3) minimizing the daily energy cost and emission cost simultaneously. Moreover, each case is operated under different battery operation conditions to investigate the battery lifetime. Finally, performance comparisons are carried out with a conventional Q-learning algorithm.Article Citation - WoS: 55Citation - Scopus: 65Neuro-Fuzzy Model Predictive Energy Management for Grid Connected Microgrids(MDPI, 2020-05-28) Ulutas, Ahsen; Altas, Ismail Hakki; Onen, Ahmet; Ustun, Taha SelimWith constant population growth and the rise in technology use, the demand for electrical energy has increased significantly. Increasing fossil-fuel-based electricity generation has serious impacts on environment. As a result, interest in renewable resources has risen, as they are environmentally friendly and may prove to be economical in the long run. However, the intermittent character of renewable energy sources is a major disadvantage. It is important to integrate them with the rest of the grid so that their benefits can be reaped while their negative impacts can be mitigated. In this article, an energy management algorithm is recommended for a grid-connected microgrid consisting of loads, a photovoltaic (PV) system and a battery for efficient use of energy. A model predictive control-inspired approach for energy management is developed using the PV power and consumption estimation obtained from daylight solar irradiation and temperature estimation of the same area. An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system. The proposed system is compared with a rule-based control strategy. Results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.Article Citation - Scopus: 5Modeling and Real Time Digital Simulation of Microgrids for Campuses Malta and Jordan Based on Multiple Distributed Energy Resources(Institute of Advanced Engineering and Science, 2021-02-01) Khiat, Sidahmed; Chaker, Abdelkader El Kader; Zacharia, Lazaros; Onen, AhmetThis paper presents the modeling and real-time digital simulation of two microgrids: The malta college of arts, science and technology (MCAST) and the German jordan university (GJU). The aim is to provide an overview of future microgrid situation and capabilities with the benefits of integrating renewable energy sources (RES), such as photovoltaic panels, diesel generators and energy storage systems for projects on both campuses. The significance of this work starts with the fact that real measurements were used from the two pilots, obtained by measuring the real physical systems. These measures were used to plan different solutions regarding RES and energy storage system (ESS) topologies and sizes. Also, the demand curves for the real microgrids of MCAST and GJU have been parameterized, which may serve as a test bed for other studies in this area. Based on actual data collected from the two pilots, a real-time digital simulation is performed using an RT-LAB platform. The results obtained by this tool allow the microgrid manager to have a very accurate vision of the facility operation, in terms of power flow and default responses. Several scenarios are studied, extracting valuable insight for implementing both projects in the future. Eventually, the proposed models would be a blueprint for training and research purposes in the microgrid field. © 2020 Elsevier B.V., All rights reserved.Article Citation - WoS: 376Citation - Scopus: 481Enhancing Smart Grid With Microgrids: Challenges and Opportunities(Pergamon-Elsevier Science Ltd, 2017-05) Yoldas, Yeliz; Onen, Ahmet; Muyeen, S. M.; Vasilakos, Athanasios V.; Alan, IrfanThe modern electric power systems are going through a revolutionary change because of increasing demand of electric power worldwide, developing political pressure and public awareness of reducing carbon emission, incorporating large scale renewable power penetration, and blending information and communication technologies with power system operation. These issues initiated in establishing microgrid concept which has gone through major development and changes in last decade, and recently got a boost in its growth after being blessed by smart grid technologies. The objective of this paper is to presents a detailed technical overview of microgrid and smart grid in light of present development and future trend. First, it discusses microgrid architecture and functions. Then, smart features are added to the microgrid to demonstrate the recent architecture of smart grid. Finally, existing technical challenges, communication features, policies and regulation, etc. are discussed from where the future smart grid architecture can be visualized.Conference Object Citation - WoS: 13Citation - Scopus: 15Dynamic Rolling Horizon Control Approach for a University Campus(Elsevier, 2022-04) Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet; Ustun, Taha SelimAn 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. (c) 2021 The Author(s). Published by Elsevier Ltd.Conference Object Citation - WoS: 3Citation - Scopus: 8Cloud Induced PV Impact on Voltage Profiles for Real Microgrids(Institute of Electrical and Electronics Engineers Inc., 2018-09) Kocer, Mustafa Cagatay; Yoldaş, Yeliz; Gören, Selçuk; Onen, Ahmet; Alan, İrfan; Al-Agtash, Salem Y.; Tzovaras, Dimitrios K.; Borg, NicholasIntegration 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. © 2023 Elsevier B.V., All rights reserved.Article Citation - WoS: 21Citation - Scopus: 27Blockchain-Based Energy Applications: The DSO Perspective(IEEE-Inst Electrical Electronics Engineers Inc, 2021) Yagmur, Ahmet; Dedeturk, Beyhan Adanur; Soran, Ahmet; Jung, Jaesung; Onen, AhmetThis paper discusses blockchain-based energy applications from the distribution system operator (DSO) perspective. Blockchain has a potential impact on newly emergent actors, such as electric vehicles (EVs) and the charging facility units (CFUs) of the electricity grid. Although Blockchain offers magnificent decentralized solutions, the central management of DSOs still plays a significant, non-negligible role, owing to the reality of the existing grid structure. Numerous related studies of proposed blockchain-based EV systems have investigated the energy costs of EVs, fast and efficient charging, privacy and security, P2P energy trading, sharing economy, the selection of appropriate CFUs location, and scheduling. However, cooperation with DSO organizations has not been adequately addressed. Blockchain-based solutions mainly suggest an entirely distributed and decentralized approach for energy trading; however, converting the entire power system infrastructure is considerably expensive. Building a thoroughly decentralized electricity network in a short time is nearly impossible, particularly at the national grid level. In this regard, the applicability of the solutions is as significant as their appropriateness, especially from the DSO perspective, and must be examined closely. We searched and analyzed the blockchain literature related to EVs, CFUs, DERs, microgrids, marketing, and DSOs to define the DSO-based requirements for potential blockchain applications in the energy sector, specifically EV evolution.Article Citation - WoS: 12Citation - Scopus: 23Artificial Neural Networks Based Harmonics Estimation for Real University Microgrids Using Hourly Solar Irradiation and Temperature Data(Elsevier, 2023-03) Yarar, Nurcan; Yagci, Mustafa; Bahceci, Serkan; Onen, Ahmet; Ustun, Taha SelimThe need for renewable energy is increasing day by day due to different factors such as increasing energy demand, environmental considerations as well as the will to decrease the share of fossil fuel-based generation. Due to their relative low-cost and ease of installation, PV systems are leading the way for renewable energy deployments around the globe. However, there are meticulous studies that need to be undertaken for realization of such projects. Studying local weather and load patterns for proper panel sizing or considering grid components to determine cable and transformer sizing can be named as some examples for pre-installation studies. In addition to these, post-installation impact studies, e.g. accurate harmonic analysis contribution, is more important to ensure safe and secure operation of the overall system. These steps need to be taken for all PV installation projects. The aim of this study is to show a step-by-step analysis of the effect of a real PV system on the network and to improve the prediction and give a new perspective to the harmonic estimation by using the hourly temperature and radiation data together. At the first phase of the study, a detail real-time 250 kW PV system was modeled for real university campus, and then harmonic estimation based on hourly solar irradiation and hourly temperature was performed with artificial neural networks (ANN) and nonlinear autoregressive exogenous (NARX). The accuracy of the prediction made with ANN was 0.98, and the accuracy of the prediction made with NARX was 0.96.Researchers in PV sizing and control field as well as engineers in power quality area would find these findings beneficial and useful. Use of ANNs and NARX for such analysis indicates the trend in this field that can be targeted by new research projects.