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International Journal of Smart Grid and Sustainable Energy Technologies
Published by Institut Teknologi Nasional Malang
ISSN : 25809121     EISSN : 2580779X     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy
International Journal of Smart Grid and Sustainable Energy Technologies (IJSGSET) is an international journal dedicated to the latest research advancements in the area of electrical engineering. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of Electrical Engineering.
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Articles 5 Documents
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Search results for , issue " Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL" : 5 Documents clear
Sizing and Evaluation of Battery Energy Storage Integrated with Photovoltaic Systems A. V. Vieira, Paulo; P. G. Silva, Felipe; F. Pinheiro, Bruna; C. Bortoni, Edson
International Journal of Smart Grid and Sustainable Energy Technologies Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL
Publisher : Department of Electrical Engineering, National Institute of Technology Malang - INDONESIA

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Abstract

This paper provides a review of the most common energy storage technologies and analysis of the impact of battery energy storage (BES) in a distribution network with penetration of photovoltaic. In order to reduce the intermittence impacts caused by solar panels (PV), is proposed the use an energy storage elements to stabilize the energy produced, dependent of the irradiation and temperature. Different storage technologies were considered as a function of the costs. A 100 kW PV system with integration of an energy storage was used for the simulated and analysis.
Investigation of The impact of Unbalanced and Non-sinusoidal Supply Voltages on Converters Hartungi, Rusdy
International Journal of Smart Grid and Sustainable Energy Technologies Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL
Publisher : Department of Electrical Engineering, National Institute of Technology Malang - INDONESIA

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Abstract

In this paper two input, current modulation strategies for matrix converters are experimentally analyzed under two different supply conditions: sinusoidal unbalanced voltages and non-sinusoidal balanced voltages. Both strategies use the Space Vector Modulation (SVM) technique in order to control the matrix converter accordingly to the input and output constraints. Strategy A modulates the input currents keeping the corresponding space vector in phase with the input voltage vector. Strategy B operates in order to keep the input current vector in phase with the positive sequence fundamental component of the input voltage vector. A comparison between the two strategies is made in terms of the reduction of the input current disturbances due to the unbalanced and non-sinusoidal voltage on the grid. It is found that a dynamic current modulation strategy, independent of the voltage disturbances such as Strategy B, is more effective for the reduction of the RMS value of input current disturbances. The validity of the theoretical investigation i.e. the effectiveness of the current modulation strategy conforms to experimental tests result carried out on a matrix converter prototype.
Intelligent Load Frequency Control considering Large Scale Photovoltaic Generation Uji Krismanto, Awan; Setiadi, Herlambang
International Journal of Smart Grid and Sustainable Energy Technologies Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL
Publisher : Department of Electrical Engineering, National Institute of Technology Malang - INDONESIA

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Abstract

Large-scale renewable energy integration involving large scale PV plant is becoming popular in the last decade due to global warming and climate change. PV plant offers clean and environmentally friendly electricity. However, PV plant also provides unwanted impact in term of frequency stability. Hence appropriate, load frequency control due to the integration of PV plant is inevitable. This paper proposed an intelligent approach based on a differential evolutional algorithm (DEA) to optimize the control parameters of load frequency control (LFC) device. Time domain simulation was carried out to analyses, the frequency nadir of the system. The simulation results suggested that a significant enhancement of system dynamic behavior was monitored when the control parameters of LFC were optimized using the proposed DEA. Moreover, the proposed algorithm provided a promising result to improve system dynamic response in the system with high penetration of PV power plant.
Emission Constrained Optimal Allocation of Generation using AWDO Technique Banerjee, Swaraj; Sarkar, Dipu
International Journal of Smart Grid and Sustainable Energy Technologies Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL
Publisher : Department of Electrical Engineering, National Institute of Technology Malang - INDONESIA

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Abstract

The current work introduces a meta-heuristic solution of an emission constrained optimal generation scheduling problem on the Distributed Energy Resources (DERs). The Combined Economic Emission Dispatch (CEED) problem reflects the environmental effects from the gaseous pollutants from fossil-fueled power generating plants. The CEED is a method for scheduling the generation considering both emission and generation cost meeting the needs of satisfying all operational constraints and load demand as well. The CEED problem has been formulated as a multi-objective problem and that later has been converted into a single objective function using price penalty factor. A comparatively new meta-heuristic nature-inspired global optimization method, Adaptive Wind Driven Optimization (AWDO), has been proposed to solve the CEED problem solution. The key objective is to solve the CEED problem with the proposed algorithm and analyze its effectiveness of with the help of the simulation results which later have been compared with other existing algorithms for two test systems (10 thermal units and 40 thermal units) and AWDO has proved to be the best and most powerful amongst them.
Risk Assessment of Power Generated from a Wind Turbine in Different Climate Cities in Indonesia Lumban Gaol, Irvan; O. P. Marpaung, Charles
International Journal of Smart Grid and Sustainable Energy Technologies Vol 2 No 1 (2018): IJSGSET TRANSACTIONS ON POWER, ELECTRONICS, TELECOMMUNICATION, AND CONTROL
Publisher : Department of Electrical Engineering, National Institute of Technology Malang - INDONESIA

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Abstract

In this paper, a risk analysis based on Monte Carlo Simulation has been used to examine the power generated from a wind turbine. There are five cities are selected based on the wind speed to be examined the power density generated from the wind turbine. The cities are Kupang, Tanjung Pinang, Krinci, Kotabaru, and Pontianak. Among the five cities, Kupang has the highest wind speed, while Pontianak has the lowest wind speed. In this study, the wind speed is assumed to be an unspecified parameter or a random variable. The Monte Carlo Simulation is run by using a software @RISK. The results show that the mean of power density generated from the wind turbine is found 171.23, 113.97, 71.28, 28.67, and 12.49 W/m2 for Kupang, Tanjung Pinang, Krinci, Kotabaru, and Pontianak respectively. The width of the confidence interval with the level of probability 90% is 110.30, 75.00, 69.10, 19.64, and 7.34 W/m2 for Kupang, Tanjung Pinang, Krinci, Kotabaru, and Pontianak respectively. The upper bound of the confidence intervals are 230.1, 154.7, 113.3, 39.27, and 16.30 W/m2 for Kupang, Tanjung Pinang, Krinci, Kotabaru, and Pontianak respectively, while the lower bounds are 119.8, 79.7, 44.2, and 19.63 W/m2 for Kupang, Tanjung Pinang, Krinci, Kotabaru, and Pontianak respectively. The probability of the power density will exceed the upper bound or will below the lower bound is 5%.

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