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Communication-Efficient Distributed Demand Response: A Randomized ADMM Approach

机译:高效通信的分布式需求响应:随机ADMM方法

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In this paper, we consider the distributed demand response (DDR) problem for achieving the real-time power balance in a neighborhood with a large number of load customers and renewable energy sources (RES). While most of the existing DDR schemes require iterative information exchange between the customers and the load aggregator through two-way communications, this paper studies the DDR schemes that rely on neighbor-wise communication between customers only. Such DDR schemes can be realized by low-cost wireless networks. To this end, we propose the use of a randomized alternating direction method of multipliers to develop a fully DDR algorithm. Notably, the proposed DDR algorithm is communication-efficient because it can yield promising power balance performance using a few times of neighbor-wise message exchanges. Moreover, the proposed DDR algorithm does not need synchronization between customers and is robust against random communication errors. For performing online demand response control, we combine the proposed DDR algorithm with the rolling-window-based model-predictive control method, and simple load and RES forecasting methods. By using real solar power data, we demonstrate via simulations that the proposed DDR algorithm improves the real-time power balance substantially and outperforms the existing DDR schemes that use the subgradient method for optimization.
机译:在本文中,我们考虑在具有大量负载客户和可再生能源(RES)的社区中实现实时电力平衡的分布式需求响应(DDR)问题。尽管大多数现有的DDR方案都需要通过双向通信在客户与负载聚合器之间进行迭代的信息交换,但本文研究的DDR方案仅依赖于客户之间的邻居通信。可以通过低成本无线网络来实现这种DDR方案。为此,我们建议使用乘数的随机交替方向方法来开发完全DDR算法。值得注意的是,提出的DDR算法具有很高的通信效率,因为它可以使用几次邻居消息交换来产生有希望的功率平衡性能。此外,所提出的DDR算法不需要客户之间的同步并且对于随机通信错误具有鲁棒性。为了执行在线需求响应控制,我们将提出的DDR算法与基于滚动窗口的模型预测控制方法以及简单的负荷和RES预测方法相结合。通过使用真实的太阳能数据,我们通过仿真证明了所提出的DDR算法大大改善了实时功率平衡,并且优于使用次梯度法进行优化的现有DDR方案。

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