Bio: Ahmet Kucuker is an academic researcher from Sakarya University. The author has contributed to research in topics: Induction motor & Stand-alone power system. The author has an hindex of 3, co-authored 6 publications receiving 39 citations.
02 Mar 2017
TL;DR: In this paper, the design and control of a micro-grid, including various alternative energy resources (photovoltaic and wind) and battery energy storage system which operates in stand-alone as well as in grid-connected mode, is discussed.
Abstract: This paper deals with the design and control of a micro-grid, including various alternative energy resources (photovoltaic and wind) and battery energy storage system which operates in stand-alone as well as in grid-connected mode. The proposed micro-grid is controlled via various non-isolated converters while an energy management is performed through switching based algorithm. According to the strategy, the wind is used as the primary power source while the Photovoltaic (PV) is added to improve the reliability of system under different weather conditions. The battery module is utilized as an energy storage system during surplus power and/or backup device during demand. The proposed system used real record of weather pattern and load conditions for a small community at Islamabad, Pakistan. This city is gifted with several natural resources that can generate a significant amount of power energy for the region. MATLAB simulation results show the effectiveness of proposed system in terms of grid stability, power sharing, load tracking and power quality.
TL;DR: In this paper, the authors examined the effect of mechanical imbalances to induction machine electrical parameters and proposed an Instantaneous Power Signature Analysis (IPSA) technique used to detect these faults.
Abstract: Mechanical imbalances are common mechanical faults in induction motors. Vibration monitoring techniques have been widely used for the diagnosis of mechanical faults in induction motors, but electrical detection methods have been preferred in recent years. For many years, researchers have concentrated on the Motor Current Signature Analysis (MCSA). This paper examines the effect of mechanical imbalances to induction machine electrical parameters. Instantaneous Power Signature Analysis (IPSA) technique used to detect these faults. In the paper, a full analysis of the proposed technique is presented, and experimental results for healthy and faulty motors have been shown and discussed.
TL;DR: The instantaneous power signature analysis technique is used to detect interturn interturn faults, and experimental results for healthy and faulty motors are shown and discussed.
Abstract: Stator interturn faults are one of the most common faults occurring in induction motors. Early detection of interturn short circuit is important to reduce repair costs. Axial leakage monitoring, zero-sequence components, negative sequence current, and motor current signature analysis have been used for fault detection in early states. In the paper, the instantaneous power signature analysis technique is used to detect these faults, and experimental results for healthy and faulty motors are shown and discussed.
•01 Sep 2010
TL;DR: In this paper, a new method for the detection of rotor bar corrosion in squirrel-cage asynchronous motor is introduced, which is based on instantaneous power analysis to detect rotor bars corrosion.
Abstract: In this paper a new method for the detection of rotor bar corrosion in squirrel-cage asynchronous motor is introduced. Because of costly machinery repair, extended process down time, and health and safety problems, it is very important to focus on fault detection strategies for industrial plant. Detection of cage motor broken rotor bars has long been an important but difficult job in the detection area of motor faults. It is known that about 9% of induction motor failures are caused by failure of the rotor faults. Rotor bar corrosion causes cracked rotor bars. Most recent efforts are focusing on current spectrum analysis for detecting rotor bar faults. This paper represents instantaneous power analysis to detect rotor bar corrosion.
06 Sep 2016
TL;DR: Hava kirliligine olan etkisinin yok denecek kadar az olmasi nedeniyle dunyada yeni elektrik enerjisi uretimi kaynaklarindan ruzgar energyjisi en hizli gelisenkaynak cesidi olmustur.
Abstract: Hava kirliligine olan etkisinin yok denecek kadar az olmasi nedeniyle dunyada yeni elektrik enerjisi uretimi kaynaklarindan ruzgar enerjisi en hizli gelisen kaynak cesidi olmustur. Ruzgar turbinlerinin kapasitelerinin artmasi sonucunda isletme sirasinda ortaya cikan arizalardaki bakim maliyetlerini ve durma zamanlarini azaltmak, turbinlerin guvenilirligi ile performansini artirmak amaciyla bir izleme sisteminin kullanilmasi zorunlu hale gelmistir. Arizanin giderilmesi ve ulasim zorlugundan dolayi kiyidan uzak turbinlerde bakim masraflari ile durma zamanlari daha yuksek olmaktadir. Ruzgar turbinlerinin durum izleme sistemlerinde titresim verileri ile yag analizi verileri yaygin olarak kullanilmaktadir. Bu sistemlerin kurulus maliyetlerinin yuksek olmasinin yaninda, durum izleme sistemlerinde olusan sorunlara bu yontemler tam olarak cozum sunamamaktadir. Ayrica, gelistirilen bu ariza tespit sistemleri turbine bagli generatorler ile sebekede olusabilecek anormal calisma durumlari ve arizalari algilayamamaktadir. Ruzgar turbini izleme sistemlerindeki bu tur sorunlari azaltmak icin bu calismada elektriksel olcumlere dayanan ve mekanik dengesizlik durumlarini algilayan yeni bir algoritma gelistirilmistir. Gelistirilen durum izleme sistemi uc fazli akim ve gerilim verilerini kullanarak generator cikis ani gucunu hesaplamaktadir. Mekanik dengesizlik durumunda generatorun kutup sayisina bagli olarak cikis ani gucunde ilave frekans bilesenleri ortaya cikmakta olup, bu da gelistirilen algoritmanin temelini olusturmaktadir.
TL;DR: In this paper, a full spectrum analysis is presented for vibration signal to reveal the fault specific whirl signatures in a rotor shaft system coupled with a three phase induction motor, and the results clearly indicate the potential and feasibility of the discussed approach.
Abstract: Rotor imbalance is the most common cause of machine vibration. In practice, rotors can never be balanced perfectly owing to manufacturing errors such as porosity in casting, non-uniform density of materials, manufacturing tolerances, and gain or loss of material during operation. Mass imbalance leads to the generation of a centrifugal force, which must be counteracted by bearings and support structures. A full spectrum analysis is presented for vibration signal to reveal the fault specific whirl signatures. The results clearly indicate the potential and feasibility of the discussed approach for the rotor imbalance diagnosis in a rotor shaft system coupled with a three phase induction motor. This paper presents a smart experimental method for vibration measurement and imbalance fault detection in rotating machinery.
01 Jan 1988
TL;DR: In this article, the authors introduced a new fault detection technique based on the use of the instantaneous power factor signature analysis as a tool for the diagnostics of mixed airgap eccentricity in operating three-phase squirrel cage induction motors.
Abstract: The aim of this paper is to introduce a new fault detection technique based on the use of the instantaneous power factor signature analysis as a tool for the diagnostics of mixed airgap eccentricity in operating three-phase squirrel cage induction motors. Firstly, a modelling and simulation study concerning the occurrence of airgap eccentricity in three-phase induction motors is presented. For that purpose, the winding function approach is considered. Then, both simulation and experimental results are presented to illustrate the effectiveness of this new proposed approach.
14 Jun 2018
TL;DR: Review of state of the art techniques for condition monitoring, evolving techniques and recent advancements are discussed along with some case studies.
Abstract: Induction motors are an indispensible commodity in modern manufacturing and service industries. These motors are reliable, rugged, and require negligible maintenance. However, due to undue thermal mechanical and electrical stresses, these may fail prematurely. An induction motor applied for critical application, if fails may cause loss of productivity and huge amount of capital loss to company. Over the last 20 years, a number of condition monitoring methods and systems have evolved to reduce their abrupt failure. This paper provides a comprehensive insight into various popularly known techniques for fault diagnosis of induction motors. Review of state of the art techniques for condition monitoring, evolving techniques and recent advancements are discussed along with some case studies.
TL;DR: The classification and review of architectures of Hybrid Renewable Energy Systems is presented and the energy management strategies for optimal flows of electrical energy between individual systems of considered hybrid renewable energy system are developed and described.
Abstract: The aim of the paper is the study of the Hybrid Renewable Energy System, which is consisted of two types of renewable energy systems (wind and sun) and is combined with storage energy system (battery). The paper presents the classification and review of architectures of Hybrid Renewable Energy Systems. The considered Hybrid Renewable Energy System was designed as a multi-converter system with gearless Wind Turbine driven Permanent Magnet Synchronous Generator and with a Photovoltaic Array and Battery Energy System. The mathematical models of individual elements of a complex Hybrid Renewable Energy System were described. In the control of both systems of Wind Turbine with Permanent Magnet Synchronous Generator and Photovoltaic array, the algorithms of Maximum Power Point Tracking have been implemented for higher efficiency of energy conversion. The energy storage in the battery has been managed by the control system of a bidirectional DC/DC converter. For the control of the Machine Side Converter and Wind Turbine with Permanent Magnet Synchronous Generator, the vector control method has been implemented. In the control system of the Grid Side Converter, the advanced method of Direct Power Control has been applied. The energy management strategies for optimal flows of electrical energy between individual systems of considered hybrid renewable energy system are developed and described. In order to determine the operation of proposed control systems, the simulation studies have been performed for different conditions of operation of individual elements of the complex hybrid system. The considered control methods and energy management strategies were tested thorough simulation studies for different wind speed variations, different sun irradiations, and different local load demands. The performed simulations are of practical importance in terms of proper operation requirements, design selection of components and energy management of Hybrid Renewable Energy Systems.
TL;DR: An energy management algorithm, which is based on a neuro-fuzzy inference system, is designed by determining the possible operating states of the system and results show that the developed control algorithm ensures that microgrid is supplied with reliable energy while the renewable energy use is maximized.
Abstract: 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.