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Showing 2 results for Load Management
IoT Based Load Management of a Micro-Grid Using Arduino and HMAS
M. Mozaffari Legha, E. Farjah,
Volume 16, Issue 2 (6-2020)
Abstract
This paper aims to establish an Arduino and IoT-based Hierarchical Multi-Agent System (HMAS) for management of loads’ side with incentive approach in a micro-grid. In this study, the performance of the proposed algorithm in a micro-grid has been verified. The micro-grid contains a battery energy storage system (BESS) and different types of loads known as residential consumer (RC), commercial consumer (CC), and industrial consumer (IC). The user interface on a smartphone directly communicates with the load management system via an integrated Ethernet Shield server which uses Wi-Fi communication protocol. Also, the communication between the Ethernet Shield and the Arduino microcontroller is based on Wi-Fi communication. A simulation model is developed in Java Agent Development Environment (JADE) for dynamic and effective energy administration, which takes an informed decision and chooses the most feasible action to stabilize, sustain, and enhance the micro-grid. Further, the environment variable is sensed through the Arduino microcontroller and sensors, and then given to the MAS agents in the IoT environment. The test results indicated that the system was able to effectively control and regulate the energy in the micro-grid.

Enhancing Voltage Regulation in DC Microgrids Using a Price Incentive Load Management Approach
A. Karimpour, A. M. Amani, M. Karimpour, M. Jalili,
Volume 17, Issue 4 (12-2021)
Abstract
This paper studies the voltage regulation problem in DC microgrids in the presence of variable loads. DC microgrids generally include several Distributed Generation Units (DGUs), connected to electrical loads through DC power lines. The variable nature of loads at each spot, caused for example by moving electric vehicles, may cause voltage deregulation in the grid. To reduce this undesired effect, this study proposes an incentive-based load management strategy to balance the loads connected to the grid. The electricity price at each node of the grid is considered to be dependent on its voltage. This guide moving customers to connect to cheaper connection points, and ultimately results in even load distribution. Simulations show the improvement in the voltage regulation, power loss, and efficiency of the grid even when only a small portion of customers accept the proposed incentive.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.