4.7 Article

A multi-agent decentralized energy management system based. on distributed intelligence for the design and control of autonomous polygeneration microgrids

期刊

ENERGY CONVERSION AND MANAGEMENT
卷 103, 期 -, 页码 166-179

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2015.06.021

关键词

Microgrids; Polygeneration; Multi agent systems; Decentralized energy management; Fuzzy Cognitive Maps

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The autonomous polygeneration microgrid topology has been developed in order to cover holistically needs in a remote area such as electrical energy, space heating and cooling, potable water through desalination and hydrogen as fuel for transportation. The existence of an advanced energy management system is essential for the operation of an autonomous polygeneration microgrid. So far, energy management systems based on a centralized management and control have been developed for the autonomous polygeneration microgrid topology based on computational intelligence approaches. A decentralized management and control energy management system can have important benefits, when taking into consideration the autonomous character of these microgrids. This paper presents the design and investigation of a decentralized energy management system for the autonomous polygeneration microgrid topology. The decentralized energy management system gives the possibility to control each unit of the microgrid independently. The most important advantage of using a decentralized architecture is that the managed microgrid has much higher chances of partial operation in cases when malfunctions occur at different parts of it, instead of a complete system breakdown. The designed system was based on a multi-agent system and employed Fuzzy Cognitive Maps for its implementation. It was then compared through a case study with an existing centralized energy Management system. The technical performance of the decentralized solution performance is on par with the existing centralized one, presenting improvements in financial and operational terms for the implementation and operation of an autonomous polygeneration microgrid. (C) 2015 Elsevier Ltd. All rights reserved.

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