Energy management of virtual power plant to participate in the electricity market using robust optimization

Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine, flexible loads, and locational marginal prices (LMPs) in order to obtain prof...

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Main Authors: M. Mohebbi-Gharavanlou, S. Nojavan, K. Zareh
Format: Article
Language:English
Published: University of Mohaghegh Ardabili 2020-02-01
Series:Journal of Operation and Automation in Power Engineering
Subjects:
Online Access:http://joape.uma.ac.ir/article_782_813cd196462cb7cc483f4362ddf6ddb0.pdf
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spelling doaj-25d4aa5abb3b480ca3451eac6cbc46892020-11-25T01:31:55ZengUniversity of Mohaghegh ArdabiliJournal of Operation and Automation in Power Engineering2322-45762020-02-0181435610.22098/joape.2019.5362.1400782Energy management of virtual power plant to participate in the electricity market using robust optimizationM. Mohebbi-Gharavanlou0S. Nojavan1K. Zareh2Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.Department of Electrical Engineering, University of Bonab, Bonab, Iran.Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine, flexible loads, and locational marginal prices (LMPs) in order to obtain profit. VPP should propose bidding/offering curves to buy/sell from/to day-ahead market. In this paper, robust optimization approach is proposed to achieve the optimal offering and bidding curves which should be submitted to the day-ahead market. This paper uses mixed-integer linear programming (MILP) model under GAMS software based on robust optimization approach to make appropriate decision on uncertainty to get profit which is resistance versus price uncertainty. The offering and bidding curves of VPP are obtained based on derived data from results. The proposed method, due to less computing, is also easy to trace the problem for the VPP operator. Finally, the price curves are obtained in terms of power for each hour, which operator uses the benefits of increasing or decreasing market prices for its plans. Also, results of comparing deterministic and RO cases are presented. Results demonstrate that profit amount in maximum robustness case is reduced 25.91 % and VPP is resisted against day-ahead market price uncertainty.http://joape.uma.ac.ir/article_782_813cd196462cb7cc483f4362ddf6ddb0.pdfvirtual power plantelectricity market uncertaintyrobust optimization approachbidding ‎and offering curvesdistributed energy resources ‎
collection DOAJ
language English
format Article
sources DOAJ
author M. Mohebbi-Gharavanlou
S. Nojavan
K. Zareh
spellingShingle M. Mohebbi-Gharavanlou
S. Nojavan
K. Zareh
Energy management of virtual power plant to participate in the electricity market using robust optimization
Journal of Operation and Automation in Power Engineering
virtual power plant
electricity market uncertainty
robust optimization approach
bidding ‎and offering curves
distributed energy resources ‎
author_facet M. Mohebbi-Gharavanlou
S. Nojavan
K. Zareh
author_sort M. Mohebbi-Gharavanlou
title Energy management of virtual power plant to participate in the electricity market using robust optimization
title_short Energy management of virtual power plant to participate in the electricity market using robust optimization
title_full Energy management of virtual power plant to participate in the electricity market using robust optimization
title_fullStr Energy management of virtual power plant to participate in the electricity market using robust optimization
title_full_unstemmed Energy management of virtual power plant to participate in the electricity market using robust optimization
title_sort energy management of virtual power plant to participate in the electricity market using robust optimization
publisher University of Mohaghegh Ardabili
series Journal of Operation and Automation in Power Engineering
issn 2322-4576
publishDate 2020-02-01
description Virtual power plant (VPP) can be studied to investigate how energy is purchased or sold in the presence of electricity market price uncertainty. The VPP uses different intermittent distributed sources such as wind turbine, flexible loads, and locational marginal prices (LMPs) in order to obtain profit. VPP should propose bidding/offering curves to buy/sell from/to day-ahead market. In this paper, robust optimization approach is proposed to achieve the optimal offering and bidding curves which should be submitted to the day-ahead market. This paper uses mixed-integer linear programming (MILP) model under GAMS software based on robust optimization approach to make appropriate decision on uncertainty to get profit which is resistance versus price uncertainty. The offering and bidding curves of VPP are obtained based on derived data from results. The proposed method, due to less computing, is also easy to trace the problem for the VPP operator. Finally, the price curves are obtained in terms of power for each hour, which operator uses the benefits of increasing or decreasing market prices for its plans. Also, results of comparing deterministic and RO cases are presented. Results demonstrate that profit amount in maximum robustness case is reduced 25.91 % and VPP is resisted against day-ahead market price uncertainty.
topic virtual power plant
electricity market uncertainty
robust optimization approach
bidding ‎and offering curves
distributed energy resources ‎
url http://joape.uma.ac.ir/article_782_813cd196462cb7cc483f4362ddf6ddb0.pdf
work_keys_str_mv AT mmohebbigharavanlou energymanagementofvirtualpowerplanttoparticipateintheelectricitymarketusingrobustoptimization
AT snojavan energymanagementofvirtualpowerplanttoparticipateintheelectricitymarketusingrobustoptimization
AT kzareh energymanagementofvirtualpowerplanttoparticipateintheelectricitymarketusingrobustoptimization
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