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Towards price-based predictive control of a small-scale electricity network

机译:走向基于价格的小型电网预测控制

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With the increasing deployment of battery storage devices in residential electricity networks, it is essential that the charging and discharging of these devices be scheduled so as to avoid adverse impacts on the electricity distribution network. In this paper, we propose a non-cooperative, price-based hierarchical distributed optimisation approach that provably recovers the centralised, or cooperative, optimal performance from the point of view of the network operator. The distributed optimisation algorithm provides important insights into the appropriate design of contracts between an energy provider and their associated residential customers, who can themselves act as energy providers as well as consumers (e.g. due to rooftop solar photovoltaics and batteries) depending on the time of the day and on real-time prices. To make the presentation self-contained, and to highlight key properties of the price-based optimisation algorithm, the dual ascent method and its convergence properties are reviewed. The performance of the proposed price-based optimisation algorithm is validated on recent measurement taken from an Australian electricity distribution company, Ausgrid. In addition to analysing the results of the open loop solution, we investigate the effect of real-time prices in the closed loop using a model predictive control framework.
机译:随着居民电力网络中的电池存储装置的越来越大,必须调度这些设备的充电和放电,以避免对电力分配网络的不利影响。在本文中,我们提出了一种非合作,基于价格的分布式优化优化方法,可从网络运营商的角度来看,可证明恢复集中或合作,最佳性能。分布式优化算法在能量提供者及其相关住宅客户之间的适当设计方面提供了重要的见解,他们本身可以充当能源提供者以及消费者(例如由于屋顶太阳能光伏和电池),这取决于时间的时间一天和实时价格。为了使演示文稿自包含,并突出显示基于价格的优化算法的关键属性,综述了双上升方法及其收敛性。拟议的基于价格的优化算法的性能是在近期从澳大利亚电力分配公司Ausgrid造成的近期测量的验证。除了分析开环解决方案的结果外,我们还使用模型预测控制框架调查闭环中实时价格的效果。

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