Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 1Citation - Scopus: 1PSO Supported Ensemble Algorithm for Bad Data Detection Against Intelligent Hacking Algorithm(Frontiers Media S.A., 2021-07-23) Yavuz, Levent; Soran, Ahmet; Onen, Ahmet; Muyeen, S. M.Power system cybersecurity has recently become important due to cyber-attacks. Due to advanced computer science and machine learning (ML) applications being used by malicious attackers, cybersecurity is becoming crucial to creating sustainable, reliable, efficient, and well-protected cyber-systems. Power system operators are needed to develop sophisticated detection mechanisms. In this study, a novel machine-learning-based detection algorithm that combines the five most popular ML algorithms with Particle Swarm Optimizer (PSO) is developed and tested by using an intelligent hacking algorithm that is specially developed to measure the effectiveness of this study. The hacking algorithm provides three different types of injections: random, continuous random, and slow injections by adaptive manner. This would make detection harder. Results shows that recall values with the proposed algorithm for each different type of attack have been increased.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.Article Citation - WoS: 4Citation - Scopus: 8Model-Centric Distribution Automation: Capacity, Reliability, and Efficiency(Taylor & Francis inc, 2016-02-26) Onen, Ahmet; Jung, Jaesung; Dilek, Murat; Cheng, Danling; Broadwater, Robert P.; Scirbona, Charlie; Wang, XiaoyuA series of analyses along with field validations that evaluate efficiency, reliability, and capacity improvements of model-centric distribution automation are presented. With model-centric distribution automation, the same model is used from design to real-time control calculations. A 14-feeder system with 7 substations is considered. The analyses involve hourly time-varying loads and annual load growth factors. Phase balancing and capacitor redesign modifications are used to better prepare the system for distribution automation, where the designs are performed considering time-varying loads. Coordinated control of load tap changing transformers, line regulators, and switched capacitor banks is considered. In evaluating distribution automation versus traditional system design and operation, quasi-steady-state power flow analysis is used. In evaluating distribution automation performance for substation transformer failures, reconfiguration for restoration analysis is performed. In evaluating distribution automation for storm conditions, Monte Carlo simulations coupled with reconfiguration for restoration calculations are used. The evaluations demonstrate that model-centric distribution automation has positive effects on system efficiency, capacity, and reliability.Article Citation - WoS: 3Citation - Scopus: 3Investigation of Distributed Series Reactors in Power System Applications and Its Economic Implementation(Wiley, 2016-08-18) Onen, AhmetThe transmission system expansion planning process requires lots of calculations looking many years into the future, and the results are based on assumed load growth. If the load growth assumed in the planning process is not correct and unexpected load growth occurs for some load points, the transmission system could face serious congestion and even overloading problems. In this paper, transmission line impedance adjustment techniques using distributed series reactance (DSR) is considered. The DSRs can be used to control power flow and alleviate overloading problems. A new term, DSR congestion relief factor, is introduced. The DSR congestion relief factor measures the increase of transmission line capacity with the application of DSRs. Parametric studies run on the IEEE 39-bus system are presented. These studies investigate the economic benefits of DSRs and the use of DSRs for single contingencies and compare DSRs with existing technologies for expanding the transmission system.Article Implementation of Capital Deferral Algorithm in Real Distribution Systems Considering Reliability by Managing Major Faults(Springer, 2019-10-15) Yoldas, Yeliz; Onen, Ahmet; Broadwater, Robert; Alan, IrfanDistribution automation technology plays a key role on power system reliability by providing faster detection, isolating the faulted area and restoring the fault. In this paper, the impacts of distribution automation are considered on radial distribution system in the event of substation transformer bank malfunction at maximum load level with the aim of deferring the big capital investments. The aim of the proposed method is not only to increase physical impact such as the reliability but also to monetize physical measures into significant economic benefits by deferring the overall investment costs. The proposed algorithm is tested with the real distribution system data, and it is shown that it can obtain remarkable economic benefits by deferring the larger capital equipment investments by making smaller investments in distribution automation.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.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: 6Citation - Scopus: 6Economic Evaluation of Distribution System Smart Grid Investments(Taylor & Francis inc, 2014-12-31) Onen, Ahmet; Cheng, Danling; Broadwater, Robert P.; Scirbona, Charlie; Cocks, George; Hamilton, Stephanie; Roark, JeffreyThis article investigates the economic benefits of smart grid automation investments. A system consisting of 7 substations and 14 feeders is used in the evaluation. Here benefits that can be quantified in terms of dollar savings are considered, termed "hard dollar" benefits. Smart grid investment evaluations to be considered include investments in improved efficiency, more cost effective use of existing system capacity with automated switches, and coordinated control of capacitor banks and voltage regulators. These smart grid evaluations are sequentially ordered, resulting in a series of incremental hard dollar benefits. Hard dollar benefits come from improved efficiency, delaying large capital equipment investments, shortened storm restoration times, and reduced customer energy use. Analyses used in the evaluation involve hourly power flow analysis over multiple years and Monte Carlo simulations of switching operations during storms using a reconfiguration for a restoration algorithm. The economic analysis uses the time-varying value of the locational marginal price. Algorithms used include reconfiguration for restoration involving either manual or automated switches and coordinated control involving two modes of control. Field validations of phase balancing and capacitor design results are presented. The evaluation shows that investments in automation can improve performance while simultaneously lowering costs.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.