A multiagent modeling and investigation of smart homes with power generation, storage, and trading features

Salman Kahrobaee, Rasheed A. Rajabzadeh, Leen-Kiat Soh, Sohrab Asgarpoor

Research output: Contribution to journalArticle

60 Scopus citations

Abstract

Smart homes, as active participants in a smart grid, may no longer be modeled by passive load curves; because their interactive communication and bidirectional power flow within the smart grid affects demand, generation, and electricity rates. To consider such dynamic environmental properties, we use a multiagent-system-based approach in which individual homes are autonomous agents making rational decisions to buy, sell, or store electricity based on their present and expected future amount of load, generation, and storage, accounting for the benefits each decision can offer. In the proposed scheme, home agents prioritize their decisions based on the expected utilities they provide. Smart homes' intention to minimize their electricity bills is in line with the grid's aim to flatten the total demand curve. With a set of case studies and sensitivity analyses, we show how the overall performance of the home agents converges-as an emergent behavior-to an equilibrium benefiting both the entities in different operational conditions and determines the situations in which conventional homes would benefit from purchasing their own local generation-storage systems.

Original languageEnglish (US)
Article number6338331
Pages (from-to)659-668
Number of pages10
JournalIEEE Transactions on Smart Grid
Volume4
Issue number2
DOIs
StatePublished - Jan 1 2013

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Keywords

  • Energy storage
  • load management
  • multiagent systems
  • smart grids
  • wind power generation

ASJC Scopus subject areas

  • Computer Science(all)

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