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Mohan Khedkar

Bio: Mohan Khedkar is an academic researcher from Visvesvaraya National Institute of Technology. The author has contributed to research in topics: Islanding & Inverter. The author has an hindex of 1, co-authored 4 publications receiving 4 citations.

Papers
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Proceedings ArticleDOI
01 Jan 2020
TL;DR: In this article, 36 passive parameters have been considered and among them the best parameter(s) for islanding detection are obtained by applying a suitable performance ranking algorithm under various islanding and non-islanding cases for three different scenarios which are single point of common coupling (PCC) -single inverter DG, single PCC -multiple inverter DGs and multiple PCCs-multiple inverters DGs.
Abstract: The occurrence of unintentional island is one of the serious concerns when a power system network is heavily penetrated with distributed generation (DG) sources like solar and wind energy sources. Many methods have been proposed in the literature for islanding detection but still, there are many potential candidates to be explored for this concern. In this paper 36 passive parameters have been considered and among them the best parameter(s) for islanding detection are obtained by applying a suitable performance ranking algorithm under various islanding and non-islanding cases for three different scenarios which are single point of common coupling (PCC) - single inverter DG, single PCC - multiple inverter DGs and multiple PCCs-multiple inverter DGs. MATLAB/SIMULINK results show that $\Delta \mathrm{V}/\Delta \mathrm{I}$ and $\Delta \mathrm{f}/\Delta \mathrm{Q}$ for single PCC – single inverter DG, $\Delta \theta_{\mathrm{DG}}/\Delta \mathrm{Q}$ and $\Delta \mathrm{P}/\Delta \mathrm{I}$ for single PCC – multiple inverter DGs and $\Delta \mathrm{V}/\Delta \mathrm{I}, \Delta \mathrm{I}/\Delta \mathrm{V}, \Delta\theta_{\mathrm{DG}}/\Delta \mathrm{T}, \Delta\theta_{\mathrm{DG}}/\Delta \mathrm{Q}$ and $\Delta \mathrm{P}/\Delta \mathrm{V}$ for multiple PCCs – multiple inverter DGs scenarios are the best suitable candidates for islanding detection. The major contribution of this paper is it provides potential passive islanding detection indicators especially for a situation of multi-inverter islands formed at multiple PCC points.

6 citations

Journal ArticleDOI
TL;DR: This review provides an insight into passive parameters (which are islanding detection indicators) considered by various researchers and their performance with respect to detection time, non-detection zone, performance in a noisy environment exclusively for passive schemes employing signal processing techniques, difficulty level and process of selecting threshold value(s).
Abstract: Unintentional islanding is one of the serious concerns to be addressed when interfacing a distributed generation source, as it causes damage to the equipment and personnel. Many algorithms have been proposed for islanding detection in the literature which are classified into local methods (passive, active and hybrid), communication-based methods, and methods employing signal processing and classifiers techniques. Out of which, passive islanding detection methods have been mostly adopted in practice since they have an edge over other islanding detection methods (IDMs) such as there is no degradation of power quality as in active methods and are simple to implement and cheap as compared to communication-based methods. Therefore, in this paper, an attempt has been made to systematically put forward a detailed review of islanding detection methods exclusively with a passive approach. This review provides an insight into passive parameters (which are islanding detection indicators) considered by various researchers and their performance with respect to detection time (also known as run-on-time), non-detection zone, performance in a noisy environment exclusively for passive schemes employing signal processing techniques, difficulty level and process of selecting threshold value(s). Additionally, this review provides a brief account on the future role of passive schemes and also passive IDMs incorporating ride-through requirements in compliance with recent interconnection standards.

6 citations

Proceedings ArticleDOI
22 Mar 2019
TL;DR: The studies have been carried out in MATLAB SIMULINK environment and the results show that all the three passive islanding detection methods are prone to the possibility of false trips.
Abstract: This paper studies the performance of three prominent passive islanding detection methods which are Over/Under Voltage (OUV), Over/Under Frequency(OUF) and Total Harmonic Distortion (THD) for different islanding and non islanding events like switching on/off a capacitor bank, switching on/off a inductor bank , tripping of a single phase (analogous to 1-phase fault) and tripping of two phases (analogous to 2-phase fault) for three different scenarios which are single point of common (PCC) coupling-single inverter distributed generation (DG) source, single point of common coupling-multiple inverter distributed generation sources and multiple point of common coupling-multiple inverter distributed generation sources. The studies have been carried out in MATLAB SIMULINK environment and the results show that all the three passive islanding detection methods are prone to the possibility of false trips.

4 citations

Proceedings ArticleDOI
02 Apr 2021
TL;DR: In this paper, the potential passive islanding detection candidates are obtained by suitably ranking 40 different passive parameters out of which 36 are extracted from a basic point of common coupling (PCC) voltage, inverter DG output current, phase angle, active and reactive power outputs of the source and remaining 4 are harmonic based voltage and current parameters.
Abstract: Large grid integration of distributed power generation (DG) sources presents few protection challenges like the formation of a sustained unintentional island which is hazardous to both equipment and personnel. Here potential passive islanding detection candidates are obtained by suitably ranking 40 different passive parameters out of which 36 are extracted from a basic point of common coupling (PCC) voltage, inverter DG output current, phase angle, active and reactive power outputs of inverter DG source and remaining 4 are harmonic based voltage and current parameters. These 40 parameters are ranked for their performance under different islanding and non-islanding events on a standard IEEE 13 bus distribution system by employing a suitable performance ranking technique for three different scenarios. MATLAB/SIMULINK results show that for single inverter-single PCC and multi-inverter multi-PCC unintentional island scenarios different passive parameters among 40 have shown comparatively best performance under various conditions. This paper most crucially gives a set of best passive candidates that can promise detection of unintentional islands especially for the challenging scenario of multi-inverter islands formation at different DG locations (PCC points) in a given power distribution network.

3 citations


Cited by
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Proceedings ArticleDOI
17 Jun 2020
TL;DR: The use of alternative energy sources is increasing in daily life to meet the world energy demand, and the Distribution Generation (DG) sources place an import role in the smart grid.
Abstract: The use of alternative energy sources is increasing in daily life to meet the world energy demand. The Distribution Generation (DG) sources place an import role in the smart grid. They are mainly suffering with islanding detection problem. This paper presents the review of various islanding detection methods and parameters for efficient islanding detection in smart grids. The islanding detection methods are majorly classified as passive, active and hybrid islanding detection methods. The advantages, disadvantages and applications of available methods are presented. The best islanding detection parameters are suggested for future islanding detection in smart grids.

26 citations

Proceedings ArticleDOI
19 Apr 2021
TL;DR: In this article, a logistic regression algorithm is implemented for the islanding monitoring, which covers different possible island conditions, minimum observable parameters, multiple inverter-based distributed power supplies and then applies.
Abstract: Islanding will damage the protection and reliability of the power system; it must be detected by the control system within a particular time. Here, a logistic regression algorithm is implemented for the islanding monitoring. Firstly, an inverter-based distributed power generation system model is defined in MATLAB/ SIMULINK. The model covers different possible island conditions, minimum observable parameters, multiple inverter-based distributed power supplies and then applies. The data extracted from the above island conditions are trained in the proposed data-driven algorithm. Finally, the proposed trained model is applied to detect the islanding status. The results do achieve the feasibility of the method.

4 citations

Proceedings ArticleDOI
02 Apr 2021
TL;DR: In this paper, the potential passive islanding detection candidates are obtained by suitably ranking 40 different passive parameters out of which 36 are extracted from a basic point of common coupling (PCC) voltage, inverter DG output current, phase angle, active and reactive power outputs of the source and remaining 4 are harmonic based voltage and current parameters.
Abstract: Large grid integration of distributed power generation (DG) sources presents few protection challenges like the formation of a sustained unintentional island which is hazardous to both equipment and personnel. Here potential passive islanding detection candidates are obtained by suitably ranking 40 different passive parameters out of which 36 are extracted from a basic point of common coupling (PCC) voltage, inverter DG output current, phase angle, active and reactive power outputs of inverter DG source and remaining 4 are harmonic based voltage and current parameters. These 40 parameters are ranked for their performance under different islanding and non-islanding events on a standard IEEE 13 bus distribution system by employing a suitable performance ranking technique for three different scenarios. MATLAB/SIMULINK results show that for single inverter-single PCC and multi-inverter multi-PCC unintentional island scenarios different passive parameters among 40 have shown comparatively best performance under various conditions. This paper most crucially gives a set of best passive candidates that can promise detection of unintentional islands especially for the challenging scenario of multi-inverter islands formation at different DG locations (PCC points) in a given power distribution network.

3 citations

Proceedings ArticleDOI
21 May 2021
TL;DR: The objective function of minimizing operating cost is used for scheduling of different type of generators for renewable energy systems like Cluster of Renewables, Distribution Storage, Photo Voltaic Systems and Compensation.
Abstract: With high penetration of Renewable energy systems especially in countries like India, Power System Restructuring in terms of planning has become an important and immediate objective. Superior components like FACTS devices and systems like distribution storage for electric vehicles has made the grid complex. In this Paper the objective function of minimizing operating cost is used for scheduling of different type of generators. like Cluster of Renewables, Distribution Storage, Photo Voltaic Systems and Compensation. Finally, day ahead market power is scheduled using YALMIP and solved using GUROBI on MATLAB platform. The scheduling avoids congestion in market planning and helps the distribution system operator to operate optimally. A Case Study on IEEE 33 bus system is done to validate the proposed algorithm.

2 citations