Improving offering strategies for wind farms enhanced with storage capability

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedings – Annual report year: 2015Researchpeer-review

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Due to the flexible charging and discharging capability, energy storage system (ESS) is thought of as a promising complement to wind farms (WF) in participating into electricity markets. This paper proposes a reserve-based real-time operation strategy of ESS to make arbitrage and to alleviate the wind power deviation from day-ahead contracts. Taking into account the operation strategy as well as two-price balancing market rules, a day-ahead bidding strategy of WF-ESS system is put forward and formulated. A modified gradient descent algorithm is described to solve the formulations. In the case studies, the computational efficiency of the algorithm is validated firstly. Moreover, a number of scenarios with/without considering the temporal dependence of wind power forecast error are designed and employed to compare the proposed strategy with other common ones in terms of profit.
Original languageEnglish
Title of host publicationProceedings of 2015 IEEE Eindhoven PowerTech
Publication date2015
ISBN (Print)9781479976935
Publication statusPublished - 2015
Event2015 IEEE Eindhoven PowerTech - Eindhoven, Netherlands
Duration: 29 Jun 20152 Jul 2015


Conference2015 IEEE Eindhoven PowerTech
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • energy storage, gradient methods, power markets, wind power plants, Power, Energy and Industry Applications, Artificial intelligence, Bidding strategy, day-ahead bidding strategy, day-ahead contracts, electricity markets, energy storage system, ESS, gradient descent algorithm, operation strategy, real-time operation, storage capability, two-price balancing market rules, wind farm, wind farms, wind power deviation, wind power forecast error
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