Profit-based optimal generation scheduling of a microgrid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The paper proposes a formulation for profit-based optimal generation scheduling by a microgrid (μgrid). Current methods normally assume either islanded operation, or utilitygrid connected μgrid but lacking in market participation elements. The paper addresses this gap whereby the formulated objective function allows for autonomous decision-making to determine the hour by hour optimal dispatch of generators subject to system constraints including market parameters. The distributed generations in the modelled μgrid consist of wind turbines, microturbines and photovoltaic arrays while the system inputs are based on tropical conditions. A case study on the difference between grid-connected and islanded operation is presented. The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem.

Original languageEnglish
Title of host publicationPEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts
Pages232-237
Number of pages6
DOIs
Publication statusPublished - 22 Oct 2010
Event4th International Power Engineering and Optimization Conference, PEOCO 2010 - Shah Alam, Malaysia
Duration: 23 Jun 201024 Jun 2010

Publication series

NamePEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts

Other

Other4th International Power Engineering and Optimization Conference, PEOCO 2010
CountryMalaysia
CityShah Alam
Period23/06/1024/06/10

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Control and Optimization

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  • Cite this

    Muhamad Razali, N. M., & Hashim, A. H. (2010). Profit-based optimal generation scheduling of a microgrid. In PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts (pp. 232-237). [5559244] (PEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts). https://doi.org/10.1109/PEOCO.2010.5559244