Risk Measure Based Robust Bidding Strategy for Arbitrage Using a Wind Farm and Energy Storage
This paper proposes the use of a risk measure based robust optimization bidding strategy for dispatching a wind farm in combination with energy storage. Through coordination with energy storage devices, variable wind generators can be utilized as dispatchable energy producers in the deregulated elec...
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Veröffentlicht in: | IEEE transactions on smart grid 2013-12, Vol.4 (4), p.2191-2199 |
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creator | Thatte, Anupam A. Le Xie Viassolo, Daniel E. Singh, Sunita |
description | This paper proposes the use of a risk measure based robust optimization bidding strategy for dispatching a wind farm in combination with energy storage. Through coordination with energy storage devices, variable wind generators can be utilized as dispatchable energy producers in the deregulated electricity market. The total profit from sale of electricity can be increased by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices in the day ahead market. A case study is presented to show that as the forecast error in electricity price increases, the robust optimization based bidding strategy has an increasing probability of yielding better economic performance than a deterministic optimization based bidding strategy. The uncertainty set for robust optimization is selected based on the coherent risk measure conditional value at risk (CVaR). Uncertainties in electricity price forecasting and wind power forecasting are considered. The resulting robust optimization based bidding strategy is evaluated using Monte Carlo simulation for different choices of uncertainty sets. |
doi_str_mv | 10.1109/TSG.2013.2271283 |
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Through coordination with energy storage devices, variable wind generators can be utilized as dispatchable energy producers in the deregulated electricity market. The total profit from sale of electricity can be increased by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices in the day ahead market. A case study is presented to show that as the forecast error in electricity price increases, the robust optimization based bidding strategy has an increasing probability of yielding better economic performance than a deterministic optimization based bidding strategy. The uncertainty set for robust optimization is selected based on the coherent risk measure conditional value at risk (CVaR). Uncertainties in electricity price forecasting and wind power forecasting are considered. The resulting robust optimization based bidding strategy is evaluated using Monte Carlo simulation for different choices of uncertainty sets.</description><identifier>ISSN: 1949-3053</identifier><identifier>EISSN: 1949-3061</identifier><identifier>DOI: 10.1109/TSG.2013.2271283</identifier><identifier>CODEN: ITSGBQ</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Bidding strategy ; Electric utilities ; Electricity ; electricity market ; Energy storage ; Monte Carlo simulation ; Optimization ; risk measure ; robust optimization ; Robustness ; Uncertainty ; uncertainty set ; Wind farms ; Wind forecasting ; wind power</subject><ispartof>IEEE transactions on smart grid, 2013-12, Vol.4 (4), p.2191-2199</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-189bbc792ca53985420c5e047dda23c44e4e8d17d35af8bfd5e769179c3ed34d3</citedby><cites>FETCH-LOGICAL-c291t-189bbc792ca53985420c5e047dda23c44e4e8d17d35af8bfd5e769179c3ed34d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6596522$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6596522$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Thatte, Anupam A.</creatorcontrib><creatorcontrib>Le Xie</creatorcontrib><creatorcontrib>Viassolo, Daniel E.</creatorcontrib><creatorcontrib>Singh, Sunita</creatorcontrib><title>Risk Measure Based Robust Bidding Strategy for Arbitrage Using a Wind Farm and Energy Storage</title><title>IEEE transactions on smart grid</title><addtitle>TSG</addtitle><description>This paper proposes the use of a risk measure based robust optimization bidding strategy for dispatching a wind farm in combination with energy storage. Through coordination with energy storage devices, variable wind generators can be utilized as dispatchable energy producers in the deregulated electricity market. The total profit from sale of electricity can be increased by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices in the day ahead market. A case study is presented to show that as the forecast error in electricity price increases, the robust optimization based bidding strategy has an increasing probability of yielding better economic performance than a deterministic optimization based bidding strategy. The uncertainty set for robust optimization is selected based on the coherent risk measure conditional value at risk (CVaR). Uncertainties in electricity price forecasting and wind power forecasting are considered. The resulting robust optimization based bidding strategy is evaluated using Monte Carlo simulation for different choices of uncertainty sets.</description><subject>Bidding strategy</subject><subject>Electric utilities</subject><subject>Electricity</subject><subject>electricity market</subject><subject>Energy storage</subject><subject>Monte Carlo simulation</subject><subject>Optimization</subject><subject>risk measure</subject><subject>robust optimization</subject><subject>Robustness</subject><subject>Uncertainty</subject><subject>uncertainty set</subject><subject>Wind farms</subject><subject>Wind forecasting</subject><subject>wind power</subject><issn>1949-3053</issn><issn>1949-3061</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kM1LAzEQxYMoWLR3wUvA89Z8bDabY1vaKlSEfuBJQnYzW1Ltbk12D_3vzdLSucwM83tv4CH0RMmIUqJeN-vFiBHKR4xJynJ-gwZUpSrhJKO311nwezQMYU9icc4zpgboe-XCD_4AEzoPeGICWLxqii60eOKsdfUOr1tvWtidcNV4PPaFi_sO8Db0R4O_XG3x3PgDNnGY1eAjum6bHnpEd5X5DTC89Ae0nc8207dk-bl4n46XSckUbROaq6IopWKlEVzlImWkFEBSaa1hvExTSCG3VFouTJUXlRUgM0WlKjlYnlr-gF7Ovkff_HUQWr1vOl_Hl5pKoQSJrjRS5EyVvgnBQ6WP3h2MP2lKdJ-jjjnqPkd9yTFKns8SBwBXPBMqE4zxf3AibUU</recordid><startdate>20131201</startdate><enddate>20131201</enddate><creator>Thatte, Anupam A.</creator><creator>Le Xie</creator><creator>Viassolo, Daniel E.</creator><creator>Singh, Sunita</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Through coordination with energy storage devices, variable wind generators can be utilized as dispatchable energy producers in the deregulated electricity market. The total profit from sale of electricity can be increased by exploiting arbitrage opportunities available due to the inter-temporal variation of electricity prices in the day ahead market. A case study is presented to show that as the forecast error in electricity price increases, the robust optimization based bidding strategy has an increasing probability of yielding better economic performance than a deterministic optimization based bidding strategy. The uncertainty set for robust optimization is selected based on the coherent risk measure conditional value at risk (CVaR). Uncertainties in electricity price forecasting and wind power forecasting are considered. 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subjects | Bidding strategy Electric utilities Electricity electricity market Energy storage Monte Carlo simulation Optimization risk measure robust optimization Robustness Uncertainty uncertainty set Wind farms Wind forecasting wind power |
title | Risk Measure Based Robust Bidding Strategy for Arbitrage Using a Wind Farm and Energy Storage |
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