Local Energy Marketplace Agents-Based Analysis

Ameni Boumaiza, Antonio Sanfilippo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This research shows that prosumer consortium transactive models are useful for lowering the price of energy and increasing the stability and reliability of power in localized areas. The decentralized nature of blockchain and solar power prediction helps keep control within local areas, such as Education City Community Housing (ECCH), where many households have access to resources that would otherwise be expensive or otherwise impossible to manage. This could ultimately lead to the wider adoption of such models to reduce energy costs and create energy-conscious communities. Overall, prosumer consortium energy transactive models can create a win-win situation for the parties involved. Increasing communication between the participants, lowering costs, and eliminating intermediary organizations, allows prosumers to take control of their electricity usage, become self-sufficient, and contribute to an economy powered by distributed energy generation. Furthermore, it also allows institutions to become more sustainable, better manage their energy demand, and enjoy more reliable energy with reduced costs.

Original languageEnglish
Title of host publicationIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798350331820
DOIs
Publication statusPublished - 2023
Event49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore
Duration: 16 Oct 202319 Oct 2023

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/TerritorySingapore
CitySingapore
Period16/10/2319/10/23

Keywords

  • Prosumer consortium
  • artificial intelligence
  • blockchain
  • energy trading
  • solar predictions

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