Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market
Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a...
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Format: | Article |
Language: | English |
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MDPI AG
2012-11-01
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Series: | Energies |
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Online Access: | http://www.mdpi.com/1996-1073/5/11/4804 |
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author | Xiaolin Liu Kun Liu Jiang Wu Haifeng Zhang Feng Gao |
author_facet | Xiaolin Liu Kun Liu Jiang Wu Haifeng Zhang Feng Gao |
author_sort | Xiaolin Liu |
collection | DOAJ |
description | Wind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS), the chance-constrained programming-based strategy (CPS) and the multi-objective bidding strategy (ECPS). Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets. |
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id | doaj.art-01f178cdc8334c80a3d9a61c6685fb0a |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-04-11T13:12:10Z |
publishDate | 2012-11-01 |
publisher | MDPI AG |
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series | Energies |
spelling | doaj.art-01f178cdc8334c80a3d9a61c6685fb0a2022-12-22T04:22:29ZengMDPI AGEnergies1996-10732012-11-015114804482310.3390/en5114804Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity MarketXiaolin LiuKun LiuJiang WuHaifeng ZhangFeng GaoWind Power Producers (WPPs) seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS), the chance-constrained programming-based strategy (CPS) and the multi-objective bidding strategy (ECPS). Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets.http://www.mdpi.com/1996-1073/5/11/4804wind powerbiddingday-ahead electricity marketriskchance-constrained programmingmulti-objective optimization |
spellingShingle | Xiaolin Liu Kun Liu Jiang Wu Haifeng Zhang Feng Gao Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market Energies wind power bidding day-ahead electricity market risk chance-constrained programming multi-objective optimization |
title | Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market |
title_full | Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market |
title_fullStr | Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market |
title_full_unstemmed | Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market |
title_short | Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market |
title_sort | optimal bidding strategies for wind power producers in the day ahead electricity market |
topic | wind power bidding day-ahead electricity market risk chance-constrained programming multi-objective optimization |
url | http://www.mdpi.com/1996-1073/5/11/4804 |
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