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Efficient Algorithms for Renewable Energy Allocation to Delay Tolerant Consumers

机译:延迟容忍消费者可再生能源分配的高效算法

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We investigate the problem of allocating energy from renewable sources to flexible consumers in electricity markets. We assume there is a renewable energy supplier that provides energy according to a time-varying (and possibly unpredictable) supply process. The plant must serve consumers within a specified delay window, and incurs a cost of drawing energy from other (possibly non-renewable) sources if its own supply is not sufficient to meet the deadlines. We formulate two stochastic optimization problems: The first seeks to minimize the time average cost of using the other sources (and hence strives for the most efficient utilization of the renewable source). The second allows the renewable source to dynamically set a price for its service, and seeks to maximize the resulting time average profit. These problems are solved via the Lyapunov optimization technique. Our resulting algorithms do not require knowledge of the statistics of the time-varying supply and demand processes and are robust to arbitrary sample path variations.
机译:我们调查从可再生资源分配能源到电力市场中的灵活消费者的问题。我们假设有一种可再生能源供应商,可根据时变(可能是不可预测的)供应过程提供能量。该工厂必须在指定的延迟窗口内为消费者提供服务,如果其自身的供应不足以满足截止日期,则将消费者从其他(可能是不可再生)的来源中汲取能源。我们制定了两个随机优化问题:首先试图最大限度地减少使用其他来源的时间平均成本(因此,努力为可再生资源的最有效利用)。第二种允许可再生源动态设置其服务的价格,并寻求最大化所产生的时间平均利润。这些问题通过Lyapunov优化技术解决了。我们的所产生的算法不需要了解时变送和需求过程的统计数据,并且对任意样本路径变化具有稳健。

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