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A privacy-preserving and aggregate load controlling decentralized energy consumption scheduling scheme

机译:隐私保护和总负载控制的分散能耗调度方案

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In this manuscript, a decentralized and heuristic energy consumption scheduling scheme is proposed for implementing the day-ahead price-based demand side management program in a power distribution network. A customer, who participates in the proposed scheme, profits by minimizing his consumption cost and taking into account his own financial benefits and operational needs. This is done for each customer without a need for iterative interaction and other customers' consumption information. Also, the supplier takes advantage of this scheme, by controlling the aggregate network consumption peak through solving a simplified optimization problem, which needs less information about customers' consumption. The customers' privacy is preserved in this scheme, because no individual behaviour, in the forthcoming scheduling time horizon, can be extracted from the data sent to the supplier. Besides, in one sense it is a fair solution because the less customer's consumption peak is, the more relative financial benefit he gets. In our simulated case study, the proposed scheme was compared to the most related scheme, where the Commonwealth Edison company day-ahead pricing data-set is employed. The results show that the aggregate network consumption peak of our scheme is controllable, even when the percentage of the participant customers increases.
机译:在此手稿中,提出了一种分散式启发式能耗调度方案,用于在配电网中实施基于日价格的基于需求的需求侧管理程序。参与提议的方案的客户通过最小化其消费成本并考虑到自己的财务利益和运营需求来获利。这是为每个客户完成的,不需要迭代交互和其他客户的消费信息。此外,供应商通过解决简化的优化问题来控制总的网络消耗峰值,从而利用了该方案,该问题所需的客户消费信息较少。此方案保留了客户的隐私,因为在即将到来的调度时间范围内,无法从发送给供应商的数据中提取个人行为。此外,从某种意义上说,这是一个公平的解决方案,因为客户的消费高峰越少,他获得的相对财务利益就越多。在我们的模拟案例研究中,将提议的方案与使用英联邦爱迪生公司日前定价数据集的最相关方案进行了比较。结果表明,即使参与客户的百分比增加,我们的方案的总网络消耗峰值也是可控的。

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