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On the complexity of energy storage problems

机译:论能量储存问题的复杂性

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We analyze the computational complexity of the problem of optimally managing a storage device connected to a source of renewable energy, the power grid, and a household (or some other form of energy demand) in the presence of uncertainty. We provide a mathematical formulation for the problem as a Markov decision process following other models appearing in the literature, and study the complexity of determining a policy to achieve the maximum profit that can be attained over a finite time horizon, or simply the value of such profit. We show that if the problem is deterministic, i.e.?there is no uncertainty on prices, energy production, or demand, the problem can be solved in strongly polynomial time. This is also the case in the stochastic setting if energy can be sold and bought for the same price on the spot market. If the sale and buying price are allowed to be different, the stochastic version of the problem is #P-hard, even if we are only interested in determining whether there exists a policy that achieves positive profit. Furthermore, no constant-factor approximation algorithm is possible in general unless P = NP. However, we provide a Fully Polynomial-Time Approximation Scheme (FPTAS) for the variant of the problem in which energy can only be bought from the grid, which is #P-hard.
机译:我们分析了在存在不确定性的情况下最佳地管理连接到可再生能量,电网和家庭(或某种其他形式的能量需求的存储设备的存储设备的问题的计算复杂性。我们为该问题提供了一个数学制定,因为在文献中出现的其他模型之后的马尔可夫决策过程,并研究确定策略以实现可以在有限时间范围内实现的最大利润的复杂性,或者简单地获得利润。我们表明,如果问题是确定性的,即在价格,能源生产或需求上没有不确定性,可以在强大的多项式时间内解决问题。如果可以在现货市场上以相同的价格销售能量,这也是随机设置中的情况。如果允许销售和购买价格是不同的,问题的随机版本的问题是#P-Hard,即使我们只对确定是否存在实现积极利润的政策感兴趣。此外,除非p = np,否则通常不允许恒因子近似算法。然而,我们提供了一个完全多项式近似方案(FPTA),用于唯一可以从网格中购买的问题的变体,这是#P-Hard的能量。

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