Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions

This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain el...

Full description

Bibliographic Details
Main Authors: K. Masoudi, H. Abdi
Format: Article
Language:English
Published: University of Mohaghegh Ardabili 2020-08-01
Series:Journal of Operation and Automation in Power Engineering
Subjects:
Online Access:http://joape.uma.ac.ir/article_827_dd28618d6d36b20ccc578245aeae9ab7.pdf
id doaj-0ee167b65d734cfaa7e1c45bb039b4b9
record_format Article
spelling doaj-0ee167b65d734cfaa7e1c45bb039b4b92020-11-25T04:03:33ZengUniversity of Mohaghegh ArdabiliJournal of Operation and Automation in Power Engineering2322-45762020-08-018214115110.22098/joape.2019.6204.1470827Multi-Objective Stochastic Programming in Microgrids Considering Environmental EmissionsK. Masoudi0H. Abdi1Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah, Iran.Electrical Engineering Department, Engineering Faculty, Razi University, Kermanshah, Iran.This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, due to intrinsically stochastic weather changes, were also considered in the proposed method. To cope with uncertainties, the scenario-based stochastic approach was utilized, and the reduction of the environmental emissions generated by the power resources was regarded as the second objective, besides the cost of units’ operation. The ɛ-constraint method was employed to deal with the presented multi-objective optimization problem, and the simulations were performed on a sample MG with one month of real data. The results demonstrated the applicability and effectiveness of the proposed techniques in real-world conditions.http://joape.uma.ac.ir/article_827_dd28618d6d36b20ccc578245aeae9ab7.pdfmicrogridstochastic schedulinguncertaintypower market pricepollutant emission
collection DOAJ
language English
format Article
sources DOAJ
author K. Masoudi
H. Abdi
spellingShingle K. Masoudi
H. Abdi
Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
Journal of Operation and Automation in Power Engineering
microgrid
stochastic scheduling
uncertainty
power market price
pollutant emission
author_facet K. Masoudi
H. Abdi
author_sort K. Masoudi
title Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
title_short Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
title_full Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
title_fullStr Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
title_full_unstemmed Multi-Objective Stochastic Programming in Microgrids Considering Environmental Emissions
title_sort multi-objective stochastic programming in microgrids considering environmental emissions
publisher University of Mohaghegh Ardabili
series Journal of Operation and Automation in Power Engineering
issn 2322-4576
publishDate 2020-08-01
description This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, due to intrinsically stochastic weather changes, were also considered in the proposed method. To cope with uncertainties, the scenario-based stochastic approach was utilized, and the reduction of the environmental emissions generated by the power resources was regarded as the second objective, besides the cost of units’ operation. The ɛ-constraint method was employed to deal with the presented multi-objective optimization problem, and the simulations were performed on a sample MG with one month of real data. The results demonstrated the applicability and effectiveness of the proposed techniques in real-world conditions.
topic microgrid
stochastic scheduling
uncertainty
power market price
pollutant emission
url http://joape.uma.ac.ir/article_827_dd28618d6d36b20ccc578245aeae9ab7.pdf
work_keys_str_mv AT kmasoudi multiobjectivestochasticprogramminginmicrogridsconsideringenvironmentalemissions
AT habdi multiobjectivestochasticprogramminginmicrogridsconsideringenvironmentalemissions
_version_ 1724439728595402752