Multi-Agent-Based Forecast Update Methods for Profit Enhancement of Intermittent Distributed Generators in a Smart Microgrid

Ashish Patel, H. S.V.S. Kumar Nunna, Suryanarayana Doolla

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Uncertainty in generation from intermittent sources makes a strong case to have effective forecasting methods. However, errors in forecast lead to losses to the distributed generation (DG) owners. In this article, multi-agent-based forecast update methods are proposed which minimize the forecast errors. The effectiveness of the proposed methods in enhancing the profit of intermittent generators and microgrid operational cost is analyzed using a microgrid with two scenarios, namely simple ownership and multiple ownership. A modified IEEE 13 bus system is used as the case study system and the system simulation for the microgrid is performed on the OpenDSS platform and the proposed multi-agent system is developed using JAVA Agent DEvelopment (JADE) framework. From the simulation results, the proposed approaches are found effective in increasing profit margins for the investors or owners of the DGs.

Original languageEnglish
Pages (from-to)1782-1794
Number of pages13
JournalElectric Power Components and Systems
Volume46
Issue number16-17
DOIs
Publication statusPublished - Oct 21 2018

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Keywords

  • distributed generators (DGs)
  • forecasting
  • local electricity markets
  • microgrid
  • renewable sources

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Electrical and Electronic Engineering

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