Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/202

Browse

Now showing 1 - 20 of 21

Artificial neural networks based harmonics estimation for real university microgrids using hourly solar irradiation and temperature data
(ELSEVIER, 2023) Yarar, Nurcan; Yagci, Mustafa; Bahceci, Serkan; Onen, Ahmet; Ustun, Taha Selim; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
The 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.
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.
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.
Economic evaluation of distribution system smart grid investments
(Taylor and Francis Inc., 2015) Önen, Ahmet; Cheng, Danling; Broadwater, Robert P.; Scirbona, Charlie; Cocks, George; Hamilton, Stephanie; Wang, Xiaoyu; Roark, Jeffrey; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet; Broadwater, Robert P.
This 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.
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.
Efficiency and Cost Evaluation of Distribution Systems based on Multiple Time Points
(IEEE, 2015) Onen, Ahmet; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
Phase balancing can offer planning engineers a low-cost means of reducing operating costs, improving efficiency in electric power systems. In general, utilities make phase balancing based on peak load by thinking that is the worst case scenario, but every time is not the case. In this paper, time varying phase balancing algorithm is proposed to investigate the effect of hourly phase balancing for all year (8760 hour for a year) and also evaluate system efficiency and cost saving for all hours. Additionally, it is important for the planning engineers to estimate losses accurately to make phase moves, and the peak load does not always provide the most efficient phase moves among the hours in year. In this paper, there different scenarios will be compared; base case, phase balancing based on peak load, and hourly time varying phase balancing. These scenarios will be compared based on loss reduction, and cost saving with Locational Marginal Price (LMP) to provide the planning engineers ideas about effective power system planning.
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.
A hybrid agent-based secondary control for microgrids with increased fault-tolerance needs
(Institution of Engineering and Technology, 2018) Bintoudi, Angelina D.; Zyglakis, Lampros; Apostolos C. Tsolakis; Ioannidis, Dimosthenis; Al-Agtash S.; Martinez-Ramos, Jose L.; Onen, Ahmet; Azzopardi, Brian; Hadjidemetriou, Lenos; Martensen, Nis; Mounir, Khiat; Borg, Nicholas; Fragale, Nunziatina; Demoulias, Charis; Tzovaras, Dimitrios; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
This paper proposes a hybrid secondary control architecture for microgrids with AC-coupled droop-controlled units, based on both centralised and distributed control principles. The proposed secondary control is based on a multi-agent system (MAS), complemented by a microgrid centralised controller (MGCC). The system is able to adjust the droop curves dynamically in order to achieve voltage/frequency restoration as well as active/reactive power optimal allocation, based on the actual status of the controllable units, in particular, the state-of-charge of batteries and maximum power point of photovoltaics. The distributed nature of the agents is also fully exploited because the proposed framework retains operability even under fault on secondary MGCC. To evaluate the proposed framework, a scenario-based performance analysis has been tested over a simulated AC islanded microgrid, where communication from the MGCC is suddenly interrupted and the MAS is required to reconfigure in order to maintain the same control objectives. MATLAB/Simulink simulations have been realised using detailed physical form models for a small-scale microgrid, while the implementation of the MGCC and MAS is accomplished through Java Agent Development (JADE) framework.
Is the Smart Grid A Good Investment?
(IEEE, 2015) Onen, Ahmet; Broadwater, Robert; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Onen, Ahmet
Electric distribution design and operational goals include meeting customer reliability requirements at the lowest cost. Smart Grid investments have the potential for helping meet these goals, and this paper presents a series of analyses that evaluate the incremental economic benefits of smart grid automation investments. Smart Grid investments provide a number of benefits to customers. Here only benefits that can be objectively quantified in terms of economic savings are considered. Smart Grid automation investments in this work include investments in feeder efficiency, automated switches, and coordinated control of capacitor banks, voltage regulators and load tab changers. Benefits that come from these investments are improved efficiency, reduced demand, shortened storm restoration time, and improved performance during reconfiguration events. The analyses used in the evaluation are very detailed, involving hourly, quasi-steady state power flow analysis over a ten year period for calculating energy consumption and costs, and Monte Carlo simulations for six different storm types. The evaluation shows that similar to other industries, an investment in automation can be justified in terms of hard dollars.
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.
Mikro Şebeke Dizaynı, Geliştirilmesi Ve Gösterilmesi
(TUBİTAK, 2020) Önen, Ahmet; Alan, İrfan; Alboyacı, Bora; 0000-0001-7086-5112; 0000-0001-7995-0540; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet; Alan, Irfan
Bu projede Malta da bulunan MCAST (ve daha sonra eklenen Yunanistan da bulunan CERTH araştırma merkezi kampüsünün) üniversitesinin elektrik şebekesini mikro şebeke olarak çalıştırılması konusunda yapılan simülasyonlar ve bu simülasyonların şebekede ki sonuçları gösterilmektedir. Proje de sekonder ve tersiyer kontrol metotları geliştirilerek mikro şebeke optimum işletilmesi amaçlanmıştır. Bu metotlar şebeke bağlantı modundan ada moda geçişlerin başarılı bir şekilde yapılmasından, işletme maliyetini minimuma indirilmesine ve yan hizmetlere sunulan faydaları içermektedir. Bu metodlar geliştirilirken mikro şebekenin davranışı analiz edilmiş ve kesikli ve belirsiz PV entegrasyonuna göre adepte edilerek güncellenmiştir. Pv lerin kesikli ve belirsiz davranışı depolama sistemlerinin durumu, dizel jeneretörlerin varlığı, yüklerin kontrol edilibilir/edilemez olması gibi birçok değişken de dikkate alınarak reel zamanda cevap veren kontrolcülerin geliştirildiği bir çalışma olmuştur. Reel zaman da çalışabilen kontrolcü tasarımında hem MATLAB araçları geliştirilmiş hemde GAMS ortamında da optimizasyon sonuçları ile karşılaştırılmıştır. Bu projenin gerek ülkemiz için gerekse tüm mikro şebeke geliştiricilere örnek olacağı düşünülmektedir. Proje kapsamında bir yüksek lisans tezi, bir tam ve bir de kısmi doktora öğrencisi destklemesi ve birde post-doc araştırmacı için ise temel teşkil etmesi açısından da akademik boyutta istenilen hedeflere ulaşılmıştır.
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.
Neuro-Fuzzy-Based Model Predictive Energy Management for Grid Connected Microgrids
(MDPI, ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND, 2020) Ulutas, Ahsen; Altas, Ismail Hakki; Onen, Ahmet; Ustun, Taha Selim; 0000-0001-7086-5112; 000-0002-7715-3246; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü
With 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.
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.
Optimization of multiple battery swapping stations with mobile support for ancillary services
(FRONTIERS MEDIA SA, 2022) Kocer, Mustafa Cagatay; Onen, Ahmet; Ustun, Taha Selim; Albayrak, Sahin; 0000-0001-7086-5112; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Önen, Ahmet
The 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.
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.

Browse

Browsing Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu by Author "0000-0001-7086-5112"