Optimal participation and risk mitigation of wind generators in an electricity market

Forecasted output of wind electric generators (WEGs) in a 24-h horizon has large uncertainties. These uncertainties pose a challenge while computing optimal bids necessary for participating in the day-ahead unit commitment process (DACP) thus limiting their integration and success. This study propos...

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Published in:IET renewable power generation Vol. 4; no. 2; pp. 165 - 175
Main Authors: Dukpa, A., Duggal, I., Venkatesh, B., Chang, L.
Format: Journal Article
Language:English
Published: Stevenage The Institution of Engineering & Technology 01.03.2010
Subjects:
Electric generators
Energy reserves
Energy storage
Markets
Mathematical models
Optimization
Reserves
Risk
Risk reduction
Strategy
Uncertainty
Wind power
Wind power generation
ISSN:1752-1416, 1752-1424
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Abstract Forecasted output of wind electric generators (WEGs) in a 24-h horizon has large uncertainties. These uncertainties pose a challenge while computing optimal bids necessary for participating in the day-ahead unit commitment process (DACP) thus limiting their integration and success. This study proposes a new optimal participation strategy for a WEG that employs an energy storage device (ESD) for participating in the DACP. The WEG is modelled to function as a price-taker. The proposed formulation has two objectives: (a) maximise returns from the market considering the best forecast; and (b) minimise risks considering the forecast uncertainties. Risk in the participation strategy is quantified by computing expected energy not served (EENS). The multiobjective mixed integer linear programming formulation is transformed into a fuzzy optimisation problem and solved. Through suitable examples, the ESD is shown to play two important roles: (a) it helps to shift wind energy produced during hours with low marginal prices to those hours with higher marginal prices by appropriately storing and releasing it. This shift can be forward or backward in time, (b) The second crucial role played by ESD, upon minimising EENS, is to maintain an energy reserve akin to spinning reserve such that the risk of the optimal participation schedule is the least.
AbstractList Forecasted output of wind electric generators (WEGs) in a 24-h horizon has large uncertainties. These uncertainties pose a challenge while computing optimal bids necessary for participating in the day-ahead unit commitment process (DACP) thus limiting their integration and success. This study proposes a new optimal participation strategy for a WEG that employs an energy storage device (ESD) for participating in the DACP. The WEG is modelled to function as a price-taker. The proposed formulation has two objectives: (a) maximise returns from the market considering the best forecast; and (b) minimise risks considering the forecast uncertainties. Risk in the participation strategy is quantified by computing expected energy not served (EENS). The multiobjective mixed integer linear programming formulation is transformed into a fuzzy optimisation problem and solved. Through suitable examples, the ESD is shown to play two important roles: (a) it helps to shift wind energy produced during hours with low marginal prices to those hours with higher marginal prices by appropriately storing and releasing it. This shift can be forward or backward in time, (b) The second crucial role played by ESD, upon minimising EENS, is to maintain an energy reserve akin to spinning reserve such that the risk of the optimal participation schedule is the least.
This study proposes a new optimal participation strategy for a wind electric generators (WEG) that employs an energy storage device (ESD) for participating in the day-ahead unit commitment process (DACP). The WEG is modelled to function as a price-taker. The proposed formulation aims to maximise returns from the market considering the best forecast; and minimise risks considering the forecast uncertainties. Risk in the participation strategy is quantified by computing expected energy not served (EENS). The multiobjective mixed integer linear programming formulation is transformed into a fuzzy optimisation problem and solved. The ESD helps to shift wind energy produced during hours with low marginal prices to those hours with higher marginal prices by appropriately storing and releasing it. This shift can be forward or backward in time. The ESD also maintains an energy reserve akin to spinning reserve such that the risk of the optimal participation schedule is the least.
Author Venkatesh, B.
Duggal, I.
Dukpa, A.
Chang, L.
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  surname: Chang
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Snippet This study proposes a new optimal participation strategy for a wind electric generators (WEG) that employs an energy storage device (ESD) for participating in...
Forecasted output of wind electric generators (WEGs) in a 24-h horizon has large uncertainties. These uncertainties pose a challenge while computing optimal...
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SubjectTerms Electric generators
Energy reserves
Energy storage
Markets
Mathematical models
Optimization
Reserves
Risk
Risk reduction
Strategy
Uncertainty
Wind power
Wind power generation
Title Optimal participation and risk mitigation of wind generators in an electricity market
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