Complementary‐based coalition formation for energy microgrids. (25th March 2018)

• Record Type: Journal Article
• Authors: Yasir, Muhammad; Purvis, Martin; Purvis, Maryam; Savarimuthu, Bastin Tony Roy
• Is Part Of: Computational intelligence. Volume 34:Number 2(2018)
• Page Start: 679
• Page End: 712
• Publication Date: 2018-03-25
• Subjects: coalition formation -- microgrids -- renewable energy -- multiagent systems; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12171
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: In recent years, the notion of electrical energy microgrids (MGs), in which communities share their locally generated power, has gained increasing interest. Typically, the energy generated comes from renewable resources, which means that its availability is variable, ie, sometimes there may be energy surpluses and at other times energy deficits. This energy variability can be ameliorated by trading energy with a connected electricity grid. However, since main electricity grids are subject to faults or other outages, it can be advantageous for energy MGs to form coalitions and share their energy among themselves. In this work, we present our model for the dynamic formation of such MG coalitions. In our model, MGs form coalitions on the basis of complementary weather patterns. Our agent‐based model, which is scalable and affords autonomy among the MGs participating in the coalition (agents can join and depart from coalitions at any time), features methods to reduce overall "discomfort" so that, even when all participating MGs in a coalition experience deficits, they can share energy so that their overall discomfort is reduced. We demonstrate the efficacy of our model by showing empirical studies conducted with real energy production and consumption data.