Published February 2019 | Version v1
Journal article

Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources

  • 1. Metro College, University of Applied Science and Technology, Tehran (Iran, Islamic Republic of)
  • 2. Power Control Center (PCC), Tehran Metro, Tehran Urban and Suburban Railway Operation Co (TUSRC), Tehran (Iran, Islamic Republic of)

Description

Highlights: • A comprehensive analysis on new structures of AC and DC systems is provided. • An intelligent method based on multi-objective particle swarm optimization is used. • To increase the availability and reduce network costs, the capacity of a smart microgrid with hybrid RESs is determined. • Optimal design of an AC-DC hybrid microgrid is presented. -- Abstract: Hybrid renewable system is a particular type of energy systems which can be used as Distributed Generation (DG) resources to reduce network losses and increase its efficiency. Overall, at design phase, there are two major constraints: first, availability, and second, the cost of equipment. In this paper, considering these constraints and using DGs as Renewable Energy Sources (RES) including wind turbines and photovoltaics, an intelligent method based on multi-objective particle swarm optimization is utilized. Besides, battery bank has been used as a backup unit and energy storage of the hybrid system to reduce the volatility of RESs. The purposes of this paper are: to provide a comprehensive analysis on new structures of AC and DC systems, and then, to determine the capacity and optimal design with hybrid RESs in a smart microgrid to increase the availability and reduce network costs. In order to demonstrate the possibility of proposed approach, an optimized method is designed and implemented in two scenarios (Basic, and Maximum Renewable). Effectiveness of the proposed approach is applied over a real study case. By comparing the proposed method with multi-objective genetic algorithm, simulation results show that the proposed method has effective performance in reducing costs and improving availability.

Additional details

Identifiers

DOI
10.1016/j.energy.2018.12.083;
PII
S0360544218324496;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
169
Journal Page Range
p. 496-507
ISSN
0360-5442
CODEN
ENEYDS

Optional Information

Copyright
Copyright (c) 2018 Elsevier Ltd. All rights reserved.