Real-time multi-agent support for decentralized management of electric power
Real-time multi-agent support for decentralized management of electric power
复制标题
实时多智能体支持电力分散管理
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
O. Krause
中科院分区：
文献类型：
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作者：
H. Wedde;S. Lehnhoff;E. Handschin;O. Krause
建立清洁或可再生能源涉及对联网电源的适当管理问题，特别是因为生产者同时也是消费者，反之亦然。我们描述的第一阶段的联合研发项目DEZENT之间的计算机科学学院和电气工程学院在多特蒙德大学，致力于分散和自适应的电力管理，通过分布式实时多代理体系结构。在分布式控制或地方自治下，不可预测的消费者要求或生产者问题将是主要的新奇事物。我们提出了一个分布式实时谈判算法，涉及代理商在不同层次的谈判，代表生产者和消费者的电能。尽管缺乏全球性的概述，我们能够证明，在我们的模型中，没有恶意用户的联盟可以利用极端的情况下，如从丰富的任何（人为）电力短缺，是典型的问题，在“自由”或放松管制的市场。我们的多代理系统表现出非常高的鲁棒性，对电源故障相比，集中控制的架构。在广泛的实验中，我们展示了如何在德国电力系统结构的实际设置中，新的算法可以以非常灵活和自适应的方式科普不可预见的需求和生产细节，照顾大多数潜在的硬截止日期已经在本地组级别（对应于一个小的细分）。我们进一步证明，在我们的分散化方法下，客户支付的费用低于任何传统的（全球）管理政策或结构
Establishing clean or renewable energy sources involves the problem of adequate management for the networked power sources, in particular since producers are at the same time also consumers, and vice versa. We describe the first phases of the joint R&D project DEZENT between the School of Computer Science and the College of Electrical Engineering at the University of Dortmund, devoted to decentralized and adaptive electric power management through a distributed real-time multi-agent architecture. Unpredictable consumer requests or producer problems, under distributed control or local autonomy will be the major novelty. We present a distributed real-time negotiation algorithm involving agents on different levels of negotiation, on behalf of producers and consumers of electric energy. Despite the lack of global overview we are able to prove that in our model no coalition of malicious users could take advantage of extreme situations like arising from an abundance as much as from any (artificial) shortage of electric power that are typical problems in "free" or deregulated markets. Our multi-agent system exhibits a very high robustness against power failures compared to centrally controlled architectures. In extensive experiments we demonstrate how, in realistic settings of the German power system structure, the novel algorithms can cope with unforeseen needs and production specifics in a very flexible and adaptive way, taking care of most of the potentially hard deadlines already on the local group level (corresponding to a small subdivision). We further demonstrate that under our decentralized approach customers pay less than under any conventional (global) management policy or structure