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Risk Measure Based Robust Bidding Strategy for Arbitrage Using a Wind Farm and Energy Storage

机译:使用风电场和储能的基于风险度量的套利鲁棒投标策略

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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.
机译:本文提出了一种基于风险度量的鲁棒优化投标策略,用于结合风能存储的风电场调度。通过与储能设备的配合,可变风力发电机可以在放松管制的电力市场中用作可调度的能源生产者。通过利用由于在前一天市场中电价的跨时间变化而产生的套利机会,可以增加售电的总利润。案例研究表明,随着电价的预测误差的增加,与基于确定性优化的竞标策略相比,基于鲁棒优化的竞标策略具有更高的经济绩效概率。基于一致的风险度量条件风险值(CVaR)选择为鲁棒优化设置的不确定性。考虑了电价预测和风能预测的不确定性。对于不确定性集的不同选择,使用蒙特卡洛模拟评估了基于鲁棒优化的结果出价策略。

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