Distributed multi-agent algorithm for residential energy management in smart grids

Kevin Mets, M. Strobbe, Tom Verschueren, Thomas Roelens, F. Turck, Chris Develder
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引用次数: 29

Abstract

Distributed renewable power generators, such as solar cells and wind turbines are difficult to predict, making the demand-supply problem more complex than in the traditional energy production scenario. They also introduce bidirectional energy flows in the low-voltage power grid, possibly causing voltage violations and grid instabilities. In this article we describe a distributed algorithm for residential energy management in smart power grids. This algorithm consists of a market-oriented multi-agent system using virtual energy prices, levels of renewable energy in the real-time production mix, and historical price information, to achieve a shifting of loads to periods with a high production of renewable energy. Evaluations in our smart grid simulator for three scenarios show that the designed algorithm is capable of improving the self consumption of renewable energy in a residential area and reducing the average and peak loads for externally supplied power.
智能电网住宅能源管理的分布式多智能体算法
分布式可再生能源发电机,如太阳能电池和风力涡轮机,很难预测,这使得供需问题比传统的能源生产方案更加复杂。它们还会在低压电网中引入双向能量流动,可能导致电压违规和电网不稳定。本文介绍了一种用于智能电网住宅能源管理的分布式算法。该算法由一个以市场为导向的多智能体系统组成,利用虚拟能源价格、实时生产组合中的可再生能源水平和历史价格信息,实现负荷向可再生能源高产时段的转移。在智能电网模拟器上对三种场景的评估表明,所设计的算法能够提高居民区可再生能源的自用,降低外供电的平均负荷和峰值负荷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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