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Adaptive Trading in Continuous Intraday Electricity Markets for a Storage Unit

机译:用于存储单元的连续盘中电力市场的自适应交易

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The increasing integration of renewable resources in electricity markets has increased the need for producers to correct their trading position close to real time in order to avoid volatile real-time prices. The closest option to delivery time in European markets is to trade in the continuous intraday market. This market is therefore an attractive trading outlet for assets that target at extracting value from their flexibility. Trading in this market is challenging due to the multistage nature of the problem, its high uncertainty and the fact that decisions need to be reached rapidly, in order to lock in profitable trades. We model the trading problem of a storage unit in the Markov Decision Process framework. We present an approach based on policy function approximation for tackling the problem. We provide relevant parameters for defining our policy, and demonstrate the effectiveness of our approach by comparing it to the rolling intrinsic policy on real historical data. Our proposed approach outperforms the rolling intrinsic policy, which is commonly employed in practice for storage units, by increasing profitability by on out-of-sample testing for a storage with perfect round-trip efficiency and by for a storage unit with a round-trip efficiency of 81%.
机译:越来越多的可再生资源在电力市场上的一体化增加了生产者需要纠正其近期交易位置的必要性,以避免挥发性的实时价格。欧洲市场的交货时间最近的选择是在不断的盘中市场进行交易。因此,该市场是一个有吸引力的交易直销,用于从其灵活性提取价值的资产。由于问题的多级性质,这一市场的交易是挑战,其高度不确定性以及需要迅速达到决策的事实,以便锁定有利可图的交易。我们在马尔可夫决策过程框架中模拟存储单元的交易问题。我们提出了一种基于策略函数近似来解决问题的方法。我们为定义我们的政策提供相关参数,并通过将其与实际历史数据的滚动内在政策进行比较来展示我们方法的有效性。我们所提出的方法优于滚动内在政策,这在储存单位的实践中通常通过提高采用完善往返效率的存储空间测试和具有往返存储单元的存储单元的盈利能力来实现盈利能力效率为81%。

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