Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties

Nowadays renewable energy sources, such as wind and solar, whether independently or integrated with other resources, are considered in power system, specifically self-scheduling, bidding and offering strategy problems. However, the uncertain nature of these sources has turned out the greatest challe...

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Main Authors: Mehrnoosh Khaji, maghsoud amiri, Mohammad taghi Taghavifard
Format: Article
Language:fas
Published: Semnan University 2023-12-01
Series:مجله مدل سازی در مهندسی
Subjects:
Online Access:https://modelling.semnan.ac.ir/article_7792_d41d8cd98f00b204e9800998ecf8427e.pdf
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author Mehrnoosh Khaji
maghsoud amiri
Mohammad taghi Taghavifard
author_facet Mehrnoosh Khaji
maghsoud amiri
Mohammad taghi Taghavifard
author_sort Mehrnoosh Khaji
collection DOAJ
description Nowadays renewable energy sources, such as wind and solar, whether independently or integrated with other resources, are considered in power system, specifically self-scheduling, bidding and offering strategy problems. However, the uncertain nature of these sources has turned out the greatest challenge for their owners, which makes the bidding and offering in the restructured electricity market more complicated because wind energy generation may cause penalty fees for its generation mismatches. Hence, the primary objective of this paper is to suggest a novel bidding strategy framework based on fuzzy random variable for a wind-thermal system in the electricity market for the first time. The uncertainties associated with day ahead energy, spinning reserve market prices and imbalance prices, are characterized by random fuzzy variables and the uncertainties associated with wind power outputs are modeled as a LR fuzzy numbers. The proposed self-scheduling model maximizes the expected profits while it controls the risk by providing different possibility and probability levels for decision makers.A mathematical modeling approach is applied in this research by using a mixed-integer non-linear programming model which is implemented in Lingo software in a case study of thermal generation unit to investigate the efficiency of the proposed model. A sensitivity analysis is applied to validate the performance of the proposed model. Numerical results reveal that taking advantage of wind power generation alongside with thermal generation will substantially increase the profitability of the integrated generation company.
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spelling doaj.art-598a5468a6c742f2bea3f6f8367c5ba62024-02-23T19:11:15ZfasSemnan Universityمجله مدل سازی در مهندسی2008-48542783-25382023-12-01217510.22075/jme.2023.29307.23767792Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertaintiesMehrnoosh Khaji0maghsoud amiri1Mohammad taghi Taghavifard2management faculty , Allame Tabataba'e University, Tehran, Iran.Industrial Management Dept, Faculty of Management and Accounting , Allameh Tabataba’i University, Tehran, IranAssociate Professor , Department of Management and Accounting , Allameh Tabataba’i University, Tehran, IranNowadays renewable energy sources, such as wind and solar, whether independently or integrated with other resources, are considered in power system, specifically self-scheduling, bidding and offering strategy problems. However, the uncertain nature of these sources has turned out the greatest challenge for their owners, which makes the bidding and offering in the restructured electricity market more complicated because wind energy generation may cause penalty fees for its generation mismatches. Hence, the primary objective of this paper is to suggest a novel bidding strategy framework based on fuzzy random variable for a wind-thermal system in the electricity market for the first time. The uncertainties associated with day ahead energy, spinning reserve market prices and imbalance prices, are characterized by random fuzzy variables and the uncertainties associated with wind power outputs are modeled as a LR fuzzy numbers. The proposed self-scheduling model maximizes the expected profits while it controls the risk by providing different possibility and probability levels for decision makers.A mathematical modeling approach is applied in this research by using a mixed-integer non-linear programming model which is implemented in Lingo software in a case study of thermal generation unit to investigate the efficiency of the proposed model. A sensitivity analysis is applied to validate the performance of the proposed model. Numerical results reveal that taking advantage of wind power generation alongside with thermal generation will substantially increase the profitability of the integrated generation company.https://modelling.semnan.ac.ir/article_7792_d41d8cd98f00b204e9800998ecf8427e.pdfcoordinated bidding strategyelectricity marketwind farmuncertaintyfuzzy random variablepossibility theory
spellingShingle Mehrnoosh Khaji
maghsoud amiri
Mohammad taghi Taghavifard
Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
مجله مدل سازی در مهندسی
coordinated bidding strategy
electricity market
wind farm
uncertainty
fuzzy random variable
possibility theory
title Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
title_full Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
title_fullStr Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
title_full_unstemmed Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
title_short Co-optimized bidding strategy of an integrated wind-thermal system in electricity day ahead and reserve market under uncertainties
title_sort co optimized bidding strategy of an integrated wind thermal system in electricity day ahead and reserve market under uncertainties
topic coordinated bidding strategy
electricity market
wind farm
uncertainty
fuzzy random variable
possibility theory
url https://modelling.semnan.ac.ir/article_7792_d41d8cd98f00b204e9800998ecf8427e.pdf
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AT maghsoudamiri cooptimizedbiddingstrategyofanintegratedwindthermalsysteminelectricitydayaheadandreservemarketunderuncertainties
AT mohammadtaghitaghavifard cooptimizedbiddingstrategyofanintegratedwindthermalsysteminelectricitydayaheadandreservemarketunderuncertainties