@inproceedings{1748ad8ec0cb47f391349d72755009b4,
title = "Application of Optimization for Daily Scheduling of Renewable Distributed Generations Considering Market Profits in Distribution Networks",
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.",
author = "Paul Okunade and Meisam Ansari and Arash Asrari and Javad Khazaei",
year = "2019",
month = jan,
day = "2",
doi = "10.1109/NAPS.2018.8600654",
language = "English (US)",
series = "2018 North American Power Symposium, NAPS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 North American Power Symposium, NAPS 2018",
address = "United States",
note = "2018 North American Power Symposium, NAPS 2018 ; Conference date: 09-09-2018 Through 11-09-2018",
}