Browsing by Author "Jung, Jaesung"

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Blockchain-Based Energy Applications: The DSO Perspective
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2021) Yagmur, Ahmet; Dedeturk, Beyhan Adanur; Soran, Ahmet; Jung, Jaesung; Onen, Ahmet; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Yagmur, Ahmet; Dedeturk, Beyhan Adanur; Soran, Ahmet
This 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.
Configurable, Hierarchical, Model-based, Scheduling Control with photovoltaic generators in power distribution circuits
(PERGAMON-ELSEVIER SCIENCE LTD, 2015) Jung, Jaesung; Onen, Ahmet; Russell, Kevin; Broadwater, Robert P.; Steffel, Steve; Dinkel, Alex; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
Existing distribution systems and their associated controls have been around for decades. Most distribution circuits have capacity to accommodate some level of PV generation, but the question is how much can they handle without creating problems. This paper proposes a Configurable, Hierarchical, Modelbased, Scheduling Control (CHMSC) of automated utility control devices and photovoltaic (PV) generators. In the study here the automated control devices are assumed to be owned by the utility and the PV generators and PV generator controls by another party. The CHMSC, which exists in a hierarchical control architecture that is failure tolerant, strives to maintain the voltage level that existed before introducing the PV into the circuit while minimizing the circuit loss and reducing the motion of the automated control devices. This is accomplished using prioritized objectives. The CHMSC sends control signals to the local controllers of the automated control devices and PV controllers. To evaluate the performance of the CHMSC, increasing PV levels of adoption are analyzed in a model of an actual circuit that has significant existing PV penetration and automated voltage control devices. The CHMSC control performance is compared with that of existing, local control. Simulation results presented demonstrate that the CHMSC algorithm results in better voltage control, lower losses, and reduced automated control device motion, especially as the penetration level of PV increases.
Economic optimal operation of Community Energy Storage systems in competitive energy markets
(ELSEVIER SCI LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2014) Arghandeh, Reza; Woyak, Jeremy; Onen, Ahmet; Jung, Jaesung; Broadwater, Robert P; 0000-0002-0691-5426; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet; Broadwater, Robert P
Distributed, controllable energy storage devices offer several benefits to electric power system operation. Three such benefits include reducing peak load, providing standby power, and enhancing power quality. These benefits, however, are only realized during peak load or during an outage, events that are infrequent. This paper presents a means of realizing additional benefits by taking advantage of the fluctuating costs of energy in competitive energy markets. An algorithm for optimal charge/discharge scheduling of Community Energy Storage (CES) devices as well as an analysis of several of the key drivers of the optimization are discussed.
Editorial Market-based distributed energy resources operation for future power systems
(FRONTIERS MEDIA SA, 2022) Onen, Ahmet; Jung, Jaesung; Guerrero, Josep M. M; Lee, Chul-Ho; Hossain, Md Alamgir; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet
One of the biggest challenges in the current power system operation is caused by the large scale integration of distributed energy resources (DERs) that have high volatility generations (Uzum et al., 2021). Communication and control technologies are significantly improved to provide direct interaction between agents and customers, such as in peer-to-peer frameworks. In addition, the recent developments in monitoring, sensor networks, and advanced metering infrastructure (AMI) greatly enhance the variety, volume, and speed of measurement data in electricity transmission and distribution networks. By harnessing these technologies, the application of big data, artificial intelligence, and machine learning methods can be implemented to overcome the challenges from massive DERs integration in power systems. However, these technologies require a large amount of capital to operate, which can lead to financial loss if used without an appropriate strategy. In this context, the topics of interest of this Research Topic address market-based DER operations, regulation, and decision-making, and analyze the impact of market-based DER operation on power systems.
Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data
(IEEE-SGEPRI(State Grid Electric Power Research Institute), 2024) Philip, Joice G.; Jung, Jaesung; Onen, Ahmet; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
This paper proposes an empirical wavelet transform (EWT) based method for identification and analysis of sub-synchronous oscillation (SSO) modes in the power system using phasor measurement unit (PMU) data. The phasors from PMUs are preprocessed to check for the presence of oscillations. If the presence is established, the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida algorithm. The superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest China. Results show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.
Energy Trading on a Peer-to-Peer Basis between Virtual Power Plants Using Decentralized Finance Instruments
(MDPI, 2022) Seven, Serkan; Yoldas, Yeliz; Soran, Ahmet; Alkan,Gulay Yalcin; Jung, Jaesung; Ustun, Taha Selim; Onen, Ahmet; 0000-0003-2611-720X; 0000-0003-3929-8126; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Seven, Serkan; Yalçın Alkan, Gülay; Önen, Ahmet
Over time, distribution systems have begun to include increased distributed energy resources (DERs) due to the advancement of auxiliary power electronics, information and communication technologies (ICT), and cost reductions. Electric vehicles (EVs) will undoubtedly join the energy community alongside DERs, and energy transfers from vehicles to grids and vice versa will become more extensive in the future. Virtual power plants (VPPs) will also play a key role in integrating these systems and participating in wholesale markets. Energy trading on a peer-to-peer (P2P) basis is a promising business model for transactive energy that aids in balancing local supply and demand. Moreover, a market scheme between VPPs can help DER owners make more profit while reducing renewable energy waste. For this purpose, an inter-VPP P2P trading scheme is proposed. The scheme utilizes cutting-edge technologies of the Avalanche blockchain platform, developed from scratch with decentralized finance (DeFi), decentralized applications (DApps), and Web3 workflows in mind. Avalanche is more scalable and has faster transaction finality than its layer-1 predecessors. It provides interoperability abilities among other common blockchain networks, facilitating inter-VPP P2P trading between different blockchain-based VPPs. The merits of DeFi contribute significantly to the workflow in this type of energy trading scenario, as the price mechanism can be determined using open market-like instruments. A detailed case study was used to examine the effectiveness of the proposed scheme and flow, and important conclusions were drawn.
Local steady-state and quasi steady-state impact studies of high photovoltaic generation penetration in power distribution circuits
(ELSEVIER, 2015) Jung, Jaesung; Onen, Ahmet; Russell, Kevin; Broadwater, Robert P.; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
Both steady-state and quasi steady-state impact studies in high Photovoltaic (PV) penetration distribution circuits are presented. The steady-state analysis evaluates impacts on the distribution circuit by comparing conditions before and after extreme changes in PV generation at three extreme circuit conditions, maximum load, maximum PV generation, and when the difference between the PV generation and the circuit load is a maximum. The quasi steady-state study consists of a series of steady-state impact studies performed at evenly spaced time points for evaluating the spectrum of impacts between the extreme impacts. Results addressing the impacts of cloud cover and various power factor control strategies are presented. PV penetration levels are limited and depend upon PV generation control strategies. The steady state and quasi steady-state impact studies provide information that is helpful in evaluating the effect of PV generation on distribution circuits, including circuit problems that result from the PV generation.
Model-centric Distribution Automation: Capacity, Reliability, and Efficiency
(TAYLOR & FRANCIS INC530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106, 2016) Onen, Ahmet; Jung, Jaesung; Dilek, Murat; Cheng, Danling; Broadwater, Robert P.; Scirbona, Charlie; Cocks, George; Hamilton, Stephanie; Wang, Xiaoyu; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
A 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.
Network cost allocation methods for pay-as-bid peer-to-peer energy trading: A comparison
(ELSEVIER, 2022) Noorfatima N.; Choi, Yunjeong; Onen, Ahmet; Jung, Jaesung; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
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.
Optimal Location and Sizing of Electric Bus Battery Swapping Station in Microgrid Systems by Considering Revenue Maximization
(Institute of Electrical and Electronics Engineers Inc.(IEEE), 2023) Kocer, Mustafa Cagatay; Onen, Ahmet; Jung, Jaesung; Gultekin, Hakan; Albayrak, Sahin; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
The 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.
A reinforcement learning-based demand response strategy designed from the Aggregator's perspective
(FRONTIERS MEDIA SA, 2022) Oh, Seongmun; Jung, Jaesung; Onen, Ahmet; Lee, Chul-Ho; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet
The 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.
Review on Energy Application Using Blockchain Technology With an Introductions in the Pricing Infrastructure
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC445 HOES LANE, PISCATAWAY, NJ 08855-4141, 2022) Al-Abri, Tariq; Onen, Ahmet; Al-Abri, Rashid; Hossen, Abdulnasir; Al-Hinai, Amer; Jung, Jaesung; Ustun, Taha Selim; 0000-0001-9471-997X; 0000-0001-7086-5112; 0000-0002-7200-9974; 0000-0001-8762-637X; 0000-0002-2413-8421; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet
With 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.