Önen, Ahmet
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Onen, Ahmet Onen, A.
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Main Affiliation
01. Abdullah Gül University
Mühendislik Fakültesi
Elektrik-Elektronik Mühendisliği
Mühendislik Fakültesi
Elektrik-Elektronik Mühendisliği
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Former Staff
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No research topics data found.
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
Research Products
3GOOD HEALTH AND WELL-BEING
0
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4QUALITY EDUCATION
1
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5GENDER EQUALITY
0
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6CLEAN WATER AND SANITATION
0
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7AFFORDABLE AND CLEAN ENERGY
23
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8DECENT WORK AND ECONOMIC GROWTH
0
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9INDUSTRY, INNOVATION AND INFRASTRUCTURE
3
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10REDUCED INEQUALITIES
0
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11SUSTAINABLE CITIES AND COMMUNITIES
3
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12RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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13CLIMATE ACTION
2
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14LIFE BELOW WATER
0
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15LIFE ON LAND
1
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16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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17PARTNERSHIPS FOR THE GOALS
1
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Scholarly Output
45
Articles
33
Views / Downloads
330/354
Supervised MSc Theses
1
Supervised PhD Theses
2
WoS Citation Count
1235
Scopus Citation Count
1626
Patents
0
Projects
0
WoS Citations per Publication
27.44
Scopus Citations per Publication
36.13
Open Access Source
32
Supervised Theses
3
| Journal | Count |
|---|---|
| IEEE Access | 5 |
| Frontiers in Energy Research | 4 |
| Sustainability | 3 |
| Electronics | 2 |
| Electric Power Components and Systems | 2 |
Current Page: 1 / 6
Scopus Quartile Distribution
Competency Cloud
45 results
Scholarly Output Search Results
Now showing 1 - 10 of 45
Conference Object Citation - WoS: 16Citation - Scopus: 23Provision of Ancillary Services by a Smart Microgrid: An OPF Approach(Institute of Electrical and Electronics Engineers Inc., 2018-09) Martinez-Ramos, J. L.; Marcolini, Alejandro Marano; García-López, Francisco De Paula; Almagro-Yravedra, Fernando; Onen, Ahmet; Yoldaş, Yeliz; Fragale, Nunziatina; Marano-Marcolini, AlejandroAncillary services are all services required by the transmission (TSO) or distribution system operator (DSO) to maintain the integrity and stability of the transmission or distribution system as well as the power quality. Ancillary services that can be provided by a microgrid in grid-connected operation are frequency control support, voltage control support, congestion management, reduction of grid losses, and improvement of power quality. This paper presents the optimization problems used in the 3DMicroGrid project to determine the set-points of the different resources present in the microgrid to provide ancillary services to the power system in grid-connected operation: Frequency control, voltage control and load curtailment. Results of the optimization of the pilot microgrid used in 3DMicroGrid are presented. © 2018 Elsevier B.V., All rights reserved.Article Citation - WoS: 6Citation - Scopus: 6A Reinforcement Learning-Based Demand Response Strategy Designed From the Aggregator's Perspective(Frontiers Media S.A., 2022-09-15) Oh, Seongmun; Jung, Jaesung; Onen, Ahmet; Lee, Chul-HoThe demand response (DR) program is a promising way to increase the ability to balance both supply and demand, optimizing the economic efficiency of the overall system. This study focuses on the DR participation strategy in terms of aggregators who offer appropriate DR programs to customers with flexible loads. DR aggregators engage in the electricity market according to customer behavior and must make decisions that increase the profits of both DR aggregators and customers. Customers use the DR program model, which sends its demand reduction capabilities to a DR aggregator that bids aggregate demand reduction to the electricity market. DR aggregators not only determine the optimal rate of incentives to present to the customers but can also serve customers and formulate an optimal energy storage system (ESS) operation to reduce their demands. This study formalized the problem as a Markov decision process (MDP) and used the reinforcement learning (RL) framework. In the RL framework, the DR aggregator and each customer are allocated to each agent, and the agents interact with the environment and are trained to make an optimal decision. The proposed method was validated using actual industrial and commercial customer demand profiles and market price profiles in South Korea. Simulation results demonstrated that the proposed method could optimize decisions from the perspective of the DR aggregator.Article Citation - WoS: 37Citation - Scopus: 47Enhancing Cybersecurity in Smart Grids: False Data Injection and Its Mitigation(MDPI, 2021-05-06) Unsal, Derya Betul; Ustun, Taha Selim; Hussain, S. M. Suhail; Onen, Ahmet; Suhail Hussain, S.M.Integration of information technologies with power systems has unlocked unprecedented opportunities in optimization and control fields. Increased data collection and monitoring enable control systems to have a better understanding of the pseudo-real-time condition of power systems. In this fashion, more accurate and effective decisions can be made. This is the key towards mitigating negative impacts of novel technologies such as renewables and electric vehicles and increasing their share in the overall generation portfolio. However, such extensive information exchange has created cybersecurity vulnerabilities in power systems that were not encountered before. It is imperative that these vulnerabilities are understood well, and proper mitigation techniques are implemented. This paper presents an extensive study of cybersecurity concerns in Smart grids in line with latest developments. Relevant standardization and mitigation efforts are discussed in detail and then the classification of different cyber-attacks in smart grid domain with special focus on false data injection (FDI) attack, due to its high impact on different operations. Different uses of this attack as well as developed detection models and methods are analysed. Finally, impacts on smart grid operation and current challenges are presented for future research directions.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: 6Citation - Scopus: 10Optimization of Multiple Battery Swapping Stations With Mobile Support for Ancillary Services(Frontiers Media S.A., 2022-09-26) Kocer, Mustafa Cagatay; Onen, Ahmet; Ustun, Taha Selim; Albayrak, SahinThe recent developments in electric vehicles (EVs) causes several issues that have not been satisfactorily addressed. One of the foremost problems is the charging-discharging processes of EV batteries with diverse characteristics. Although a charging station is the first choice in this regard, a battery swap station (BSS) is also a suitable alternative solution as it eliminates long waiting periods and battery degradation due to fast charging. BSS has the capability to ensure prompt and efficient service for electric vehicles. Since BSS has a large number of battery systems, optimum planning of the charging-discharging operations of the batteries is critical for both BSS and the grid. This study presents an optimal charging-discharging schedule for multiple BSSs based on the swap demand of privately owned EVs and electric bus (EB) public transportation system. In addition, BSSs reinforce the power grid by providing ancillary services such as peak shaving and valley filling with demand response programs. In order to increase the flexibility of the operation, the mobile swapping station (MSS) concept, an innovative and dynamic service, is introduced to the literature and added to the model. The results indicate that BSS is an essential agent in the ancillary services market and the MSS concept is a yielding solution for both BSSs and power networks. Last, the data utilized in the study for swap demand calculation and power grid analysis are real-world data from Berlin, Germany.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: 8Citation - Scopus: 11Network Cost Allocation Methods for Pay-As Peer-to-Peer Energy Trading: A Comparison(Elsevier, 2022-11) Noorfatima, N.; Choi, Y.; Onen, A.; Jung, J.In pay-as-bid peer-to-peer (P2P) energy trading, various types of prosumers and consumers can participate, regardless of their offers. Thus, various types of participants impact the network differently. However, very few pay-as-bid P2P energy trading studies have specifically discussed appropriate compensation for network usage, although the market is implemented in existing utility-owned grids. Therefore, to improve the performance of pay-as-bid P2P energy trading, it is important to determine the appropriate compensation to utilities for network usage. This study aims to obtain an appropriate network cost allocation method for pay-as-bid P2P energy trading. Hence, the authors present a review of pay-as-bid P2P market mechanisms and various network cost allocation (NCA) methods. Additionally, a comprehensive evaluation framework is proposed to determine the most appropriate NCA method for the pay-as-bid P2P energy trading system. A comparison was made between various NCA methods to investigate the outcomes of the implementation of different NCA methods to various market conditions. The study constructs a case study based on the operator-oriented P2P model to represent the pay-as-bid P2P energy trading system. The simulation of pay-as-bid P2P energy trading with large participant number is applied in the IEEE 69-bus distribution system. The study concluded that applying the appropriate NCA method would improve the performance of pay-as-bid P2P energy trading operation.Editorial Editorial Market-Based Distributed Energy Resources Operation for Future Power Systems(Frontiers Media S.A., 2022-12-13) Onen, Ahmet; Jung, Jaesung; Guerrero, Josep M. M.; Lee, Chul-Ho; Hossain, Md AlamgirArticle Citation - WoS: 115Citation - Scopus: 173Peer-to-Peer Energy Trading in Virtual Power Plant Based on Blockchain Smart Contracts(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Seven, Serkan; Yao, Gang; Soran, Ahmet; Onen, Ahmet; Muyeen, S. M.A novel Peer-to-peer (P2P) energy trading scheme for a Virtual Power Plant (VPP) is proposed by using Smart Contracts on Ethereum Blockchain Platform. The P2P energy trading is the recent trend the power society is keen to adopt carrying out several trial projects as it eases to generate and share the renewable energy sources in a distributed manner inside local community. Blockchain and smart contracts are the up-and-coming phenomena in the scene of the information technology used to be considered as the cutting-edge research topics in power systems. Earlier works on P2P energy trading including and excluding blockchain technology were focused mainly on the optimization algorithm, Information and Communication Technology, and Internet of Things. Therefore, the financial aspects of P2P trading in a VPP framework is focused and in that regard a P2P energy trading mechanism and bidding platform are developed. The proposed scheme is based on public blockchain network and auction is operated by smart contract addressing both cost and security concerns. The smart contract implementation and execution in a VPP framework including bidding, withdrawal, and control modules developments are the salient feature of this work. The proposed architecture is validated using realistic data with the Ethereum Virtual Machine (EVM) environment of Ropsten Test Network.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.