Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks

Paul Okunade, Meisam Ansari, Arash Asrari, Javad Khazaei

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

4 Scopus citations

Abstract

In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.

Original languageEnglish (US)
Title of host publication2018 North American Power Symposium, NAPS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538671382
DOIs
StatePublished - Jan 2 2019
Event2018 North American Power Symposium, NAPS 2018 - Fargo, United States
Duration: Sep 9 2018Sep 11 2018

Publication series

Name2018 North American Power Symposium, NAPS 2018

Conference

Conference2018 North American Power Symposium, NAPS 2018
CountryUnited States
CityFargo
Period9/9/189/11/18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Control and Optimization

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