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Energies 2017, 10(1), 45;

Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid

Department of Information Technology Engineering, Sookmyung Women’s University, Seoul 04310, Korea
Department of Electrical Engineering, Incheon National University, Incheon 22012, Korea
Author to whom correspondence should be addressed.
Academic Editor: Paras Mandal
Received: 3 August 2016 / Revised: 29 December 2016 / Accepted: 29 December 2016 / Published: 3 January 2017
(This article belongs to the Special Issue Smart Microgrids: Developing the Intelligent Power Grid of Tomorrow)
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A microgrid (MG) is a discrete energy system that can operate either in parallel with or independently from a main power grid. It is designed to enhance reliability, carbon emission reduction, diversification of energy sources, and cost reduction. When a power fault occurs in a grid, an MG operates in an islanded manner from the grid and protects its power generations and loads from disturbance by means of intelligent load shedding. A load shedding is a control procedure that results in autonomous decrease of the power demands of loads in an MG. In this study, we propose a load shedding algorithm for the optimization problem to maximize the satisfaction of system components. The proposed algorithm preferentially assigns the power to the subdemand with a high preference to maximize the satisfaction of power consumers. In addition, the algorithm assigns the power to maximize the power sale and minimize the power surplus for satisfaction of power suppliers. To verify the performance of our algorithm, we implement a multi-agent system (MAS) on top of a conventional development framework and assess the algorithm’s adaptability, satisfaction metric, and running time. View Full-Text
Keywords: load shedding; microgrid (MG); multi-agent system (MAS); optimization algorithm load shedding; microgrid (MG); multi-agent system (MAS); optimization algorithm

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Choi, Y.; Lim, Y.; Kim, H.-M. Optimal Load Shedding for Maximizing Satisfaction in an Islanded Microgrid. Energies 2017, 10, 45.

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