A Novel Mathematical Analysis for Electrical Specifications of Step-up Converter

This study presents a unique comprehensive mathematical model for both transient and steady states of the step-up power converter in order to structure physical aspects evaluations. The main disadvantage of different existence mathematical models such as impedance, small signal analysis and steady space average models is that they use numerical analysis methods or simplification solutions that lead to approximate analysis. Therefore, the physical behaviours of the system such as inductor current, output voltage and physical effects of components will not be accurately predictable. This study presents very accurate equations and all aspects of the structure are predictable. In our research, this issue is investigated in Laplace and Z domains using the output-to-input transfer function calculations, and the effect of converter circuit elements is assessed using equations obtained. For extracting the transfer function, initial values are calculated in the Z domain and based on the final value theorem, converter output voltage and input current have been calculated. Effects of converter components on capacitor voltage and input current ripples have been analysed and reported. In the final step, results of the theoretical analysis were confirmed by simulation results obtained in MATLAB/SIMULINK environment and implementation on a prototype in laboratory scales

A Communication Based Islanding Detection Method for Photovoltaic Distributed Generation Systems

PV based distributed generation (DG) systems must have some electrical connection standards while they connected to an electrical grid. One of these electrical conditions and the most important one is unplanned islanding condition. Islanding is a very dangerous condition because it could damage the PV system and related electrical systems and also working people have been at risk in islanding condition. In this application study, a new communication based islanding detection method was introduced for grid tied PV systems. A real time controller was developed with Labview for detecting islanding condition. Developed method is a hybrid method which uses the effective ways of communication based and passive methods. The results obtained from the proposed real time islanding detection method show that proposed method is reliable, robust, and independent from load and inverter. Nondetection zone (NDZ) is almost zero and islanding detection time is approximately 1-2 cycles indicated in experimental results so this time has a significant short response time according to IEEE 929-2000 standard. The proposed method is effective and presents a realistic solution to islanding so it could be implemented easily to grid tied PV systems and could be used in real system applications

Implementation of a new remote islanding detection method for wind–solar hybrid power plants

The integration of the distributed generation (DG) systems into the power grid is a significant issue to provide a reliable operation of the power system. DG systems must meet some technical requirements to achieve a successful grid connection. Islanding is also a vital issue for a reliable integration of DG systems with the grid. There have been many islanding detection methods researched in the literature, but most of them have some boundaries related to the local load and the inverter. In this study, a new remote islanding detection method is introduced for a developed wind–solar hybrid power plant, and a practical solution is researched by classifying the current methods. The proposed method monitors and controls the grid, local load and the output of the PV inverter in real time with the communication of circuit breakers. The proposed remote control system detects the changes in the currents of the circuit breakers, frequency and the active powers by checking the defined threshold values at all electrical branches of the hybrid DG system. When the breaker current goes to zero, or they are under/over defined threshold values, the circuit breakers are tripped by using a real-time control system that is developed with Labview. The proposed method also checks the frequency, active powers, and reactive powers with the currents in real-time, so it is independent of the load, and it is not inverter resident. Islanding detection time is just a cycle, and it is a considerably short response time according to the current standards. Non-detection zone (NDZ) is also zero in the proposed method. The experimental results prove that the developed remote islanding detection method is easily implemented in wind–solar DG systems, and it is also suitable for real system applications

A Real-Time Energy Management System Design for a Developed PV-Based Distributed Generator Considering the Grid Code Requirements in Turkey

Each country must determine the Grid Code conditions and apply these criteria to integrate distributed generation (DG) systems into the existing electricity grid and to ensure a stable power system. Thus, experimental studies are required to provide an effective, national, and specific Grid Code. In this study, the Turkish Grid Code’s electrical criteria were examined, and the application of these criteria was carried out on a developed PV-based DG. A real-time energy management system (RTEMS) was proposed in the study. Electrical parameters on the developed DG were monitored in real-time by considering IEEE 1547, IEEE 929–2000, and Turkey’s electrical criteria. A practical grid code study was firstly investigated in detail about the Turkish Grid Code by a developed real-time monitoring-control and protection system. The proposed RTEMS method in the study is implemented as an inverter-resident system; thus, it provides advantages over many energy management systems embedded in the inverter. The degradation in power quality and non-detection zone (NDZ) problems encountered in active and passive island mode detection methods developed embedded in the inverter are eliminated in the proposed method. With the RTEMS method, where under and over-voltage, under and over voltage frequency, and unintentional island mode events can be detected in real-time, both the existing grid-code requirements are met, and the existing power quality and NDZ problem is eliminated with the recommended inverter-independent RTEMS method

An improved automated PQD classification method for distributed generators with hybrid SVM-based approach using un-decimated wavelet transform

Artificial intelligence (AI) approaches are usually coupled with the wavelet transform (WT) for feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a useful WT-based signal processing approach is required for a reliable classification, especially in real-time applications. In this study, a new hybrid, un-decimated wavelet-transform (UWT)-based feature extraction method using a support vector machine (SVM) with a “á trous” algorithm is proposed to classify PQDs in distributed generators (DGs). The proposed method was performed in a real-time application of a DG system to classify PQDs. The derived features were tested on five different machine learning (ML) models by determining the most appropriate classification technique for the proposed UWT-based feature extraction method. An experimental DG system is constituted in the laboratory using a LabVIEW environment, and the proposed method is tested under different grid conditions. Besides, other well-known and studied conventional ML methods were also tested under 25 dB, 30 dB, and 40 dB noise and compared to the developed method. The experimental and simulation results show that the features extracted with the proposed UWT-based method provide much more successful results in classification than the existing wavelet methods in the literature. Furthermore, the proposed method's noise sensitivity performance is much better than other conventional wavelet algorithms, especially in real-time applications.©2022 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed