WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 100Citation - Scopus: 138Transformation of Microgrid to Virtual Power Plant – A Comprehensive Review(Inst Engineering Technology-IET, 2019-02-28) Yavuz, Levent; Onen, Ahmet; Muyeen, S. M.; Kamwa, InnocentTo provide continuity of balancing demand and generation, renewable sources will be more active than today in near future due to the tendency of massive investment on renewable energy sources (RESs) by countries. However, due to the uncertain and intermittent nature of RESs, RESs would create problems on power system operations such as power quality, efficiency, stability and reliability. Owing to having problems with RESs integration, virtual power plant (VPP) has introduced to make this integration smooth without compromising the grid stability and reliability along with offering many other techno-economic benefits. This study reviews structures, types, architecture and operations of VPP along with the status of present implementations worldwide. The types of VPP are introduced in details with the optimisation algorithm used with each type. In addition, VPP is linked with the most of the components in power systems such as distributed generation, active prosumers, transmission system operator and distribution system operator, grid services such as fault ride through, reactive power control as well as with the help of technology such as communications, control and optimisations. This study gives a comprehensive outline of transforming microgrid to VPP that is useful for researchers, consumers, prosumers and utility operators.Article Citation - WoS: 66Citation - Scopus: 86Rooftop Solar PV Penetration Impacts on Distribution Network and Further Growth Factors-A Comprehensive Review(MDPI, 2020-12-31) Uzum, Busra; Onen, Ahmet; Hasanien, Hany M.; Muyeen, S. M.In order to meet the electricity needs of domestic or commercial buildings, solar energy is more attractive than other renewable energy sources in terms of its simplicity of installation, less dependence on the field and its economy. It is possible to extract solar energy from photovoltaic (PV) including rooftop, ground-mounted, and building integrated PV systems. Interest in rooftop PV system applications has increased in recent years due to simple installation and not occupying an external area. However, the negative effects of increased PV penetration on the distribution system are troublesome. The power loss, reverse power flow (RPF), voltage fluctuations, voltage unbalance, are causing voltage quality problems in the power network. On the other hand, variations in system frequency, power factor, and harmonics are affecting the power quality. The excessive PV penetration also the root cause of voltage stability and has an adverse effect on protection system. The aim of this article is to extensively examines the impacts of rooftop PV on distribution network and evaluate possible solution methods in terms of the voltage quality, power quality, system protection and system stability. Moreover, it is to present a comparison of the advantages/disadvantages of the solution methods discussed, and an examination of the solution methods in which artificial intelligence, deep learning and machine learning based optimization and techniques are discussed with common methods.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.