A New Method for Stability Improvement of DC microgrids using Multi-Objective Particle Swarm Optimization

  • سال انتشار: 1395
  • محل انتشار: چهارمین کنفرانس ملی و دومین کنفرانس بین المللی پژوهش های کاربردی در مهندسی برق، مکانیک و مکاترونیک
  • کد COI اختصاصی: ELEMECHCONF04_465
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 334
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نویسندگان

Reza Mosallanezhad

Faculty of engineering, Yazd University

Zohreh Beheshtipour

Faculty of engineering, Yazd University

چکیده

In this paper, a new method for reduction of dc voltage oscillation in DC microgrids using multi-objective particle swarm optimisation is presented. Nowadays, distributed generations play an important role in supplying the energy of consumers connected to the distribution network. The distribution networks that have distributed power generation are called microgrids. Photovoltaic solar panels, wind turbines, electric vehicles are the most important distributed generations so far. The microgrids are developed in AC power transmissions. Considering that almost all the DGs such as PV panels, generate DC electric power and loads like LED can be operated with DC power, DC microgrids in which the power is transmitted as Direct Current are recommended for replacing AC microgrids. Developments in power electronic devices make the DC microgrids feasible. DC microgrids have some advantages over AC microgrids such as eliminating control of reactive power, frequency, transition lines capacitance charging impact, and skin effect. The most important pollution for dc microgrids power quality is dc voltage ripples. In this paper, a method for minimizing the DC voltage ripple through multi-objective particle swarm optimization is proposed. Considering the storage devices in the converters connected to the DC microgrids, the voltage ripple can be minimized through designating optimum size for the DC microgrid storages. Simulation results verify the effectiveness of the proposed method for voltage ripple minimization of the DC microgrids

کلیدواژه ها

DC microgrid, multi-objective particle swarm optimization

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