Browsing by Author "Yoldas, Yeliz"

Now showing 1 - 7 of 7

Citation - WoS: 111
Citation - Scopus: 147
Mitigation of Power Quality Problems Using Distribution Static Synchronous Compensator: A Comprehensive Review
(Inst Engineering Technology-IET, 2015) Latran, Mohammed Barghi; Teke, Ahmet; Yoldas, Yeliz
Electric power quality (PQ) in distribution system has become increasingly significant subject both for end users and power suppliers with the deregulation of the electric power market. The inadequate performance of conventional compensation devices to mitigate PQ problems has revealed the use of advanced power electronics based compensation devices. Distribution static synchronous compensator (DSTATCOM) is one of the shunt connected custom power devices used to improve PQ, voltage and reactive power support and to increase the capability of the auxiliary service for utility grid. This study presents a comprehensive review of the various DSTATCOM configurations for single-phase (two-wire) and three-phase (three or four-wire) systems and control strategies for the compensation of different PQ problems in distribution systems. In addition, comprehensive explanation, comparison and discussion on DSTATCOM technology are performed. Furthermore, latest trends, practical consideration and some future research fields on DSTATCOMs are discussed in detail. This is intended to present a broad perspective on the status of DSTATCOM technology to researchers dealing with compensation of PQ problems in distribution systems.
Citation - WoS: 23
Citation - Scopus: 29
Optimal 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, Ahmet
This 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.
Citation - WoS: 13
Citation - Scopus: 15
Dynamic Rolling Horizon Control Approach for a University Campus
(Elsevier, 2022) Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet; Ustun, Taha Selim
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. (c) 2021 The Author(s). Published by Elsevier Ltd.
Citation - WoS: 23
Citation - Scopus: 28
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
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.
Citation - WoS: 366
Citation - Scopus: 467
Enhancing Smart Grid With Microgrids: Challenges and Opportunities
(Pergamon-Elsevier Science Ltd, 2017) Yoldas, Yeliz; Onen, Ahmet; Muyeen, S. M.; Vasilakos, Athanasios V.; Alan, Irfan
The 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.
Implementation of Capital Deferral Algorithm in Real Distribution Systems Considering Reliability by Managing Major Faults
(Springer, 2019) Yoldas, Yeliz; Onen, Ahmet; Broadwater, Robert; Alan, Irfan
Distribution 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.
Citation - WoS: 10
Citation - Scopus: 12
Implementation of Cost Benefit Analysis of Vehicle to Grid Coupled Real Micro-Grid by Considering Battery Energy Wear: Practical Study Case
(Sage Publications Ltd, 2021) Koubaa, Rayhane; Yoldas, Yeliz; Goren, Selcuk; Krichen, Lotfi; Onen, Ahmet
The proposed research represents a spin-off of the Malta College of Arts, Science and Technology (MCAST) Micro-Grid (MG) project. Particularly, economic impact of Electric Vehicles (EV) integration into the MG is investigated in this paper. The MCAST MG consists of photovoltaic generation unit, a diesel generator and a battery storage system. In this paper, a Vehicle-to grid (V2G) concept is considered where utilities can profit from controlled energy trading operations according to EVs availability. EVs are categorized under different profiles considering energy and time availability of owners typical work hours. V2G energy cost is estimated based on battery energy wear due V2G extra cycling and refunded to EVs owners. As most of developed V2G studies don't consider real world input data or/and EV battery aging cost in system modeling and evaluation, the present paper presents a reliable study as it considers a real life MG with in field measurement input data and appropriate battery degradation model. The adopted model represents a linear approximation with a minimum error value to make a suitable tradeoff of computational complexity and accuracy of obtained results. Economic assessment of the system according to the proposed energy management is performed, where results indicate that the V2G system assisted the MG operation during high electricity price period and achieved economic profit to EVs owners. According to numerical results, V2G energy trading achieved 29.90 EUR of gross selling revenues with only 4.46 EUR as battery degradation cost which makes a 16.41% average cost reduction of daily MG operation cost.